DOCKET NO.: 348358.12702 COMBINATION IMMUNOTHERAPY The present application clams the benefit of U.S. provisional application 63/326,221 filed March 31, 2022, which is incorporated herein by reference in its entirety. BACKGROUND [0001] The efficacy of PD(L)-1 blocking agents is predicated upon CD8 T-cell-mediated anti-tumor immunity ¹ . While early studies focused on tumor-associated antigens, recent work has shifted attention to T-cell recognition of mutation associated neoantigens (MANA), owing to the large numbers of somatic mutations acquired by many cancers during their development ⁴ . The association of improved anti-PD(L)-1 clinical responses with high mutational burden tumors ⁵ strongly suggests that MANA are important targets of anti-tumor immunity induced by PD-1 blockade. [0002] Despite the significant success of ICB in improving clinical outcomes, most cancers still do not respond ⁶ . Improving ICB response rates will require an understanding of the functional state of tumor-specific T-cells, particularly in the tumor microenvironment. However, a fundamental limitation in the current understanding of the T-cell functional programs underpinning response to ICB has been the absence of transcriptional profiling of true MANA- specific TIL. A related problem is the paucity of information regarding the differences between MANA-specific TIL in ICB responsive vs resistant tumors. Indeed, MANA-specific T-cells represent a small fraction of total TIL ^2,7 , particularly in lung cancer, where they have been shown to selectively upregulate CD39. This highlights the challenges confronting characterization of the cells responsible for the activity of T-cell-targeting immunotherapies. SUMMARY [0003] Provided herein are compositions comprising checkpoint modulating agents and methods of treatment. [0004] Accordingly, in certain embodiments, a method of treating cancer comprises administering to a subject a composition comprising a therapeutically effective amount of: a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and a second agent comprising at least one of: a checkpoint antagonist, an IL- 7 receptor agonist or soluble IL-7. In certain embodiments, the composition comprises a therapeutically effective amount of (i) the first agent and (ii) a second agent comprising an IL-7 receptor agonist, soluble IL-7 or the combination thereof. [0005] In embodiments, suitably, the first agent is administered in conjunction with or in combination with the second agent. For example, a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof may be administered to a patient in conjection with or in combination with a second agent comprising at least one of: a checkpoint antagonist, an IL-7 receptor agonist or soluble IL-7. [0006] In certain embodiments, the composition comprises a therapeutically effective amount of (i) the first agent and (ii) a second agent comprising at least one of: a LAYN antagonist, an A-kinase anchoring protein 5 (AKAP5) antagonist, a FAM3 Metabolism Regulating Signaling Molecule C (FAM3C) antagonist, a KLRD1 (Killer Cell Lectin Like Receptor D1, CD94) antagonist, a KLRC2 (Killer Cell Lectin Like Receptor C2, CD159c) antagonist, an XB130 (AFAP1L2) antagonist or combinations thereof. In certain embodiments, the method of treatment further comprises administering to the subject an immunotherapeutic agent, a chemotherapeutic agent or the combination thereof. In certain embodiments, the immunotherapeutic agent comprises a tumor vaccine, adoptive cellular therapy or the combination thereof. In certain embodiments, the tumor vaccine comprises whole tumor cell vaccines, peptides, recombinant tumor associated antigen vaccines, nucleic acids or combinations thereof. In certain embodiments, the adoptive cells comprise: T cells, natural killer cells, TILs, LAK cells or combinations thereof. Again, in embodiments, suitably, the first agent is administered in conjreciton with or in combination with the second agent. [0007] In certain embodiments, an inhibitor of the first or second agent comprises: an antibody or antigen binding fragments thereof, small molecule compounds, antisense oligonucleotides, siRNA reagents, microRNAs, gene-editing agents, Fv fragments, single chain antibodies, antibody mimetics, peptoids, aptamers; enzymes, peptides organic or inorganic molecules, natural or synthetic compounds. In certain embodiments, an inhibitor of PD-1 comprises: nivolimumab, pembrolizumab, atezolizumab, durvalumab, avelumab, envafolimab, BMS-936559, CK-301, CS-1001, SHR-1316 (HTI-1088), CBT-502 (TQB-2450), BGB-A333 or combinations thereof. In certain embodiments, an inhibitor of PD-1 comprises: nivolimumab, pembrolizumab, atezolizumab, durvalumab, avelumab, envafolimab, BMS-936559, CK-301, CS- 1001, SHR-1316 (HTI-1088), CBT-502 (TQB-2450), BGB-A333 or combinations thereof. In certain embodiments, an antagonist of LAYN comprises: an anti-LAYN antibody [EPR11875(2)], aptamer, siRNA, a small molecule or combinations thereof. In certain embodiments, an antagonist of AKAP5 comprises: an anti-AKAP5 antibody, aptamer, siRNA, a small molecule or combinations thereof. In certain embodiments, an antagonist of FAM3C comprises: an anti-FAM3C antibody, aptamer, siRNA, a small molecule or combinations thereof. In certain embodiments, an antagonist of KLRD1 comprises: an anti-KLRD1 antibody, aptamer, siRNA, a small molecule or combinations thereof. In certain embodiments, an antagonist of KLRC2 comprises: an anti-KLRC2 antibody, aptamer, siRNA, a small molecule or combinations thereof. In certain embodiments, an antagonist of XB130 comprises: an anti- XB130 antibody, aptamer, siRNA, a small molecule or combinations thereof. [0008] In certain embodiments, a method of treating cancer comprises administering to a subject a composition comprising a therapeutically effective amount of: an agent which modulates expression, function or receptor-ligand binding of at least two or more of: programmed death 1 (PD-1), LAYN, AKAP5, FAM3C, KLRD1 (CD94), KLRC2 (CD159c), XB130 (AFAP1L2), IL-7 receptor or IL-7. In certain embodiments, at least one of the agents is a modulator of PD-1 expression, function or receptor-ligand binding. In certain embodiments, the agent inhibits expression, function or receptor-ligand binding of at least two or more of: programmed death 1 (PD-1), LAYN, AKAP5, FAM3C, KLRD1 (CD94), KLRC2 (CD159c), XB130 (AFAP1L2) or the combinations thereof. In certain embodiments, the method further comprises administering to the subject an immunotherapeutic agent, a chemotherapeutic agent or the combination thereof. In certain embodiments, the immunotherapeutic agent comprises a tumor vaccine, adoptive cellular therapy or the combination thereof. In certain embodiments, the tumor vaccine comprises whole tumor cell vaccines, peptides, recombinant tumor associated antigen vaccines, nucleic acids or combinations thereof. In certain embodiments, the adoptive cells comprise: T cells, natural killer cells, TILs, LAK cells or combinations thereof. In certain embodiments, the agent which modulates expression, function or receptor-ligand binding of programmed death 1 (PD-1), LAYN, AKAP5, FAM3C, KLRD1 (CD94), KLRC2 (CD159c), XB130 (AFAP1L2), IL-7 receptor or IL-7, comprises: an antibody or antigen binding fragments thereof, small molecule compounds, antisense oligonucleotides, siRNA reagents, microRNAs, gene-editing agents, Fv fragments, single chain antibodies, antibody mimetics, peptoids, aptamers; enzymes, peptides organic or inorganic molecules, natural or synthetic compounds. [0009] In certain embodiments, pharmaceutical composition comprises a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and a second agent comprising at least one of: a LAYN antagonist, an AKAP5 antagonist, a FAM3C antagonist, a KLRD1 (CD94) antagonist, a KLRC2 (CD159c) antagonist, an XB130 (AFAP1L2), an IL-7 receptor agonist or soluble IL-7. In certain embodiments, the pharmaceutical composition comprises a therapeutically effective amount of (i) the first agent and (ii) a second agent comprising an IL-7 receptor agonist, soluble IL-7 or the combination thereof. In certain embodiments, the composition comprises a therapeutically effective amount of (i) the first agent and (ii) a second agent comprising at least one of: a LAYN antagonist, an A- kinase anchoring protein 5 (AKAP5) antagonist, a FAM3 Metabolism Regulating Signaling Molecule C (FAM3C) antagonist, a KLRD1 (Killer Cell Lectin Like Receptor D1, CD94) antagonist, a KLRC2 (Killer Cell Lectin Like Receptor C2, CD159c) antagonist, an XB130 (AFAP1L2) antagonist or combinations thereof. In certain embodiments, an antagonist of the first or second agent comprises: an antibody or antigen binding fragments thereof, small molecule compounds, antisense oligonucleotides, siRNA reagents, microRNAs, gene-editing agents, Fv fragments, single chain antibodies, antibody mimetics, peptoids, aptamers; enzymes, peptides organic or inorganic molecules, natural or synthetic compounds. [00010] Definitions [00011] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. [00012] As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, to the extent that the terms “including”, “includes”, “having”, “has”, “with”, or variants thereof are used in either the detailed description and/or the claims, such terms are intended to be inclusive in a manner similar to the term “comprising.” [00013] The term “about” or “approximately” means within an acceptable error range for the particular value as determined by one of ordinary skill in the art, which will depend in part on how the value is measured or determined, i.e., the limitations of the measurement system. For example, “about” can mean within 1 or more than 1 standard deviation, per the practice in the art. Alternatively, “about” can mean a range of up to 20%, up to 10%, up to 5%, or up to 1% of a given value or range. Alternatively, particularly with respect to biological systems or processes, the term can mean within an order of magnitude within 5-fold, and also within 2-fold, of a value. Where particular values are described in the application and claims, unless otherwise stated the term “about” meaning within an acceptable error range for the particular value should be assumed. [00014] The term “antibody” is used interchangeably with the term “immunoglobulin” herein, and includes intact antibodies, fragments of antibodies, e.g., Fab, F(ab')2 fragments, and intact antibodies and fragments that have been mutated either in their constant and/or variable region (e.g., mutations to produce chimeric, partially humanized, or fully humanized antibodies, as well as to produce antibodies with a desired trait, e.g., enhanced binding and/or reduced FcR binding). The term “fragment” refers to a part or portion of an antibody or antibody chain comprising fewer amino acid residues than an intact or complete antibody or antibody chain. Fragments can be obtained via chemical or enzymatic treatment of an intact or complete antibody or antibody chain. Fragments can also be obtained by recombinant means. Exemplary fragments include Fab, Fab', F(ab')2, Fabc, Fd, dAb, VHH and scFv and/or Fv fragments. It is intended that the term “antibody” encompass any Ig class or any Ig subclass (e.g. the IgG1, IgG2, IgG3, and IgG4 subclasses of IgG) obtained from any source (e.g., humans and non- human primates, and in rodents, lagomorphs, caprines, bovines, equines, ovines, etc.). The term “antibody” is inclusive of all species, including human and humanized antibodies and the antigenic target, can be from any species. Thus, an antibody, for example, which binds to an antigen “X” can be mouse anti-human X, human anti-human X; humanized anti-human X, goat anti-human X; goat anti-mouse X; rat anti-human X; mouse anti-rat X and the like. The combinations of antibody generated in a certain species against an antigen target, e.g. “X”, from another species, or in some instances the same species(for example, in autoimmune or inflammatory response) are limitless and all species are embodied in this disclosure. The term antibody is used in the broadest sense and includes fully assembled antibodies, monoclonal antibodies (including human, humanized or chimeric antibodies), polyclonal antibodies, multispecific antibodies (e.g., bispecific antibodies), and antibody fragments that can bind antigen (e.g., Fab', F'(ab)2, Fv, single chain antibodies, diabodies), comprising complementarity determining regions (CDRs) of the foregoing as long as they exhibit the desired biological activity. [00015] As used herein, an antibody that “specifically binds” to a target is intended to refer to a targeting ligand, e.g. an antibody that binds to a target with a K _D of 1×10 ^-7 M or less, more preferably 5×10 ^-8 M or less, more preferably 3×10 ^-8 M or less, more preferably 1×10 ^-8 M or less, even more preferably 5×10 ^-9 M or less. [00016] The term “antigen-binding fragment” refers to a polypeptide fragment of an immunoglobulin or antibody that binds antigen or competes with intact antibody (i.e., with the intact antibody from which they were derived) for antigen binding (i.e., specific binding). As such these antibodies or fragments thereof are included in the scope of the disclosure, provided that the antibody or fragment binds specifically to a target molecule. [00017] The term “cancer” as used herein is meant, a disease, condition, trait, genotype or phenotype characterized by unregulated cell growth or replication as is known in the art; including lung cancer (including non-small cell lung cancer (NSCLC)), gastric cancer, colorectal cancer, as well as, for example, leukemias, e.g., acute myelogenous leukemia (AML), chronic myelogenous leukemia (CML), acute lymphocytic leukemia (ALL), and chronic lymphocytic leukemia, AIDS related cancers such as Kaposi's sarcoma; breast cancers; bone cancers such as Osteosarcoma, Chondrosarcomas, Ewing's sarcoma, Fibrosarcomas, Giant cell tumors, Adamantinomas, and Chordomas; Brain cancers such as Meningiomas, Glioblastomas, Lower- Grade Astrocytomas, Oligodendrocytomas, Pituitary Tumors, Schwannomas, and Metastatic brain cancers; cancers of the head and neck including various lymphomas such as mantle cell lymphoma, non-Hodgkins lymphoma, adenoma, squamous cell carcinoma, laryngeal carcinoma, gallbladder and bile duct cancers, cancers of the retina such as retinoblastoma, cancers of the esophagus, gastric cancers, multiple myeloma, ovarian cancer, uterine cancer, thyroid cancer, testicular cancer, endometrial cancer, melanoma, bladder cancer, prostate cancer, pancreatic cancer, sarcomas, Wilms' tumor, cervical cancer, head and neck cancer, skin cancers, nasopharyngeal carcinoma, liposarcoma, epithelial carcinoma, renal cell carcinoma, gallbladder adeno carcinoma, parotid adenocarcinoma, endometrial sarcoma, multidrug resistant cancers; and proliferative diseases and conditions, such as neovascularization associated with tumor angiogenesis. [00018] As used herein, the terms “comprising,” “comprise” or “comprised,” and variations thereof, in reference to defined or described elements of an item, composition, apparatus, method, process, system, etc. are meant to be inclusive or open ended, permitting additional elements, thereby indicating that the defined or described item, composition, apparatus, method, process, system, etc. includes those specified elements--or, as appropriate, equivalents thereof--and that other elements can be included and still fall within the scope/definition of the defined item, composition, apparatus, method, process, system, etc. [00019] “Diagnostic” or “diagnosed” means identifying the presence or nature of a pathologic condition. Diagnostic methods differ in their sensitivity and specificity. The “sensitivity” of a diagnostic assay is the percentage of diseased individuals who test positive (percent of “true positives”). Diseased individuals not detected by the assay are “false negatives.” Subjects who are not diseased and who test negative in the assay, are termed “true negatives.” The “specificity” of a diagnostic assay is 1 minus the false positive rate, where the “false positive” rate is defined as the proportion of those without the disease who test positive. While a particular diagnostic method may not provide a definitive diagnosis of a condition, it suffices if the method provides a positive indication that aids in diagnosis. [00020] An “effective amount” as used herein, means an amount which provides a therapeutic or prophylactic benefit. [00021] The term “Ig class” or “immunoglobulin class”, as used herein, refers to the five classes of immunoglobulin that have been identified in humans and higher mammals, IgG, IgM, IgA, IgD, and IgE. The term “Ig subclass” refers to the two subclasses of IgM (H and L), three subclasses of IgA (IgA1, IgA2, and secretory IgA), and four subclasses of IgG (IgG1, IgG2, IgG3, and IgG4) that have been identified in humans and higher mammals. The antibodies can exist in monomeric or polymeric form; for example, IgM antibodies exist in pentameric form, and IgA antibodies exist in monomeric, dimeric or multimeric form. [00022] The term “IgG subclass” refers to the four subclasses of immunoglobulin class IgG--IgG1, IgG2, IgG3, and IgG4 that have been identified in humans and higher mammals by the heavy chains of the immunoglobulins. The term “single-chain immunoglobulin” or “single- chain antibody” (used interchangeably herein) refers to a protein having a two-polypeptide chain structure consisting of a heavy and a light chain, said chains being stabilized, for example, by interchain peptide linkers, which has the ability to specifically bind antigen. The term “domain” refers to a globular region of a heavy or light chain polypeptide comprising peptide loops (e.g., comprising 3 to 4 peptide loops) stabilized, for example, by β pleated sheet and/or intrachain disulfide bond. Domains are further referred to herein as “constant” or “variable”, based on the relative lack of sequence variation within the domains of various class members in the case of a “constant” domain, or the significant variation within the domains of various class members in the case of a “variable” domain. Antibody or polypeptide “domains” are often referred to interchangeably in the art as antibody or polypeptide “regions”. The “constant” domains of an antibody light chain are referred to interchangeably as “light chain constant regions”, “light chain constant domains”, “CL” regions or “CL” domains. The “constant” domains of an antibody heavy chain are referred to interchangeably as “heavy chain constant regions”, “heavy chain constant domains”, “CH” regions or “CH” domains). The “variable” domains of an antibody light chain are referred to interchangeably as “light chain variable regions”, “light chain variable domains”, “VL” regions or “VL” domains). The “variable” domains of an antibody heavy chain are referred to interchangeably as “heavy chain constant regions”, “heavy chain constant domains”, “VH” regions or “VH” domains). [00023] As used herein “immune checkpoint inhibition” refers to cancer immunotherapy. The therapy targets immune checkpoints, key regulators of the immune system that stimulate or inhibit its actions, which tumors can use to protect themselves from attacks by the immune system. Checkpoint therapy can block inhibitory checkpoints, activate stimulatory functions, thereby restoring immune system function. [00024] As used herein, the term “immune checkpoint modulator” refers to an agent that interacts directly or indirectly with an immune checkpoint. In some embodiments, an immune checkpoint modulator increases an immune effector response (e.g., cytotoxic T cell response), for example by stimulating a positive signal for T cell activation. In some embodiments, an immune checkpoint modulator increases an immune effector response (e.g., cytotoxic T cell response), for example by inhibiting a negative signal for T cell activation (e.g. disinhibition). In some embodiments, an immune checkpoint modulator interferes with a signal for T cell anergy. In some embodiments, an immune checkpoint modulator reduces, removes, or prevents immune tolerance to one or more antigens. [00025] The term “immune effector cell,” as used herein, refers to a cell that is involved in an immune response, e.g., in the promotion of an immune effector response. Examples of immune effector cells include T cells, e.g., alpha/beta T cells and gamma/delta T cells, tumor infiltrating lymphocytes (TIL), B cells, natural killer (NK) cells, natural killer T (NK-T) cells, mast cells, and myeloic-derived phagocytes. “Immune effector function or immune effector response,” as that term is used herein, refers to function or response, e.g., of an immune effector cell, that enhances or promotes an immune attack of a target cell. E.g., an immune effector function or response refers a property of a T or NK cell that promotes killing or the inhibition of growth or proliferation, of a target cell. In the case of a T cell, primary stimulation and co- stimulation are examples of immune effector function or response. [00026] As used in this specification and the appended claims, the term “or” is generally employed in its sense including “and/or” unless the content clearly dictates otherwise. [00027] “Parenteral” administration of an immunogenic composition includes, e.g., subcutaneous (s.c.), intravenous (i.v.), intramuscular (i.m.), or intrasternal injection, or infusion techniques. [00028] The terms “patient” or “individual” or “subject” are used interchangeably herein, and refers to a mammalian subject to be treated, with human patients being preferred. In some embodiments, the methods of the invention find use in experimental animals, in veterinary application, and in the development of animal models for disease, including, but not limited to, rodents including mice, rats, and hamsters, and primates. [00029] The term “region” can also refer to a part or portion of an antibody chain or antibody chain domain (e.g., a part or portion of a heavy or light chain or a part or portion of a constant or variable domain, as defined herein), as well as more discrete parts or portions of said chains or domains. For example, light and heavy chains or light and heavy chain variable domains include “complementarity determining regions” or “CDRs” interspersed among “framework regions” or “FRs”, as defined herein. [00030] As defined herein, a “therapeutically effective” amount of a compound or agent (i.e., an effective dosage) means an amount sufficient to produce a therapeutically (e.g., clinically) desirable result. The compositions can be administered from one or more times per day to one or more times per week; including once every other day. The skilled artisan will appreciate that certain factors can influence the dosage and timing required to effectively treat a subject, including but not limited to the severity of the disease or disorder, previous treatments, the general health and/or age of the subject, and other diseases present. Moreover, treatment of a subject with a therapeutically effective amount of the compounds of the invention can include a single treatment or a series of treatments. [00031] “Treating” or “treatment” covers the treatment of a disease-state in a mammal, and includes: (a) preventing the disease-state from occurring in a mammal, in particular, when such mammal is predisposed to the disease-state but has not yet been diagnosed as having it; (b) inhibiting the disease-state, e.g., arresting it development; and/or (c) relieving the disease-state, e.g., causing regression of the disease state until a desired endpoint is reached. Treating also includes the amelioration of a symptom of a disease (e.g., lessen the pain or discomfort), wherein such amelioration may or may not be directly affecting the disease (e.g., cause, transmission, expression, etc). [00032] Ranges: throughout this disclosure, various aspects of the invention can be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 2.7, 3, 4, 5, 5.3, and 6. This applies regardless of the breadth of the range. [00033] Any compositions or methods provided herein can be combined with one or more of any of the other compositions and methods provided herein. BRIEF DESCRIPTION OF THE DRAWINGS [00034] The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. [00035] FIGS.1A-1F show the profiling single T-cells in NSCLC treated with neoadjuvant PD-1 blockade. Twenty patients with resectable NSCLC were treated with two doses of PD-1 blockade prior to surgical resection. FIG.1A: An overall schematic of the clinical trial, biospecimen collection (top), and study design (bottom). Coupled single-cell (sc) RNA-seq/ TCR-seq was performed on T-cells isolated from resected tumor (n=15), adjacent normal lung (NL; n=12), tumor draining lymph node (TDLN; n=3), and a resected brain metastasis (n=1) from NSCLC patients treated with two doses of neoadjuvant anti-PD-1 (bottom). The MANAFEST and ViraFEST assay was performed to identify mutation associated neoantigen (MANA)-, EBV-, and influenza-specific T-cell receptors (TCRs). FIG.1B: 2D UMAP projection of the expression profiles of the 560,916 T-cells that passed QC. Immune cell subsets, defined by 15 unique clusters, are annotated and marked by color code. FIG.1C: Relative expression of the top 5 most differential genes.5,000 cells (or all cells in the cluster if cluster size <5,000 cells) were randomly sampled from each cluster for visualization. FIG.1D: Expression of T-cell subset-defining, T-cell subset selective genes and major T-cell checkpoints. FIG.1E: Principal component analysis (PCA) of cell cluster-level pseudobulk gene expression for individual samples for tumor (yellow, n=15) and adjacent NL (dark blue, n=12). P-value was obtained using a one-sided permutation test. FIG.1F: PCA analysis of cell cluster-level pseudobulk gene expression for non-MPR (red, n=9) and MPR (light blue, n=6) tumors. P-value was obtained using a one-sided permutation test. [00036] FIGS.2A-2H show the characterization of antigen specific T-cells in NSCLC treated with neoadjuvant PD-1 blockade. The MANAFEST assay was performed on 4 MPRs and 5 non-MPRs. Results are shown in FIG.6. FIG.2A: Four TCRs recognizing p53 R248L-derived MD01-004-MANA12 were identified in non-MPR MD01-004. Their frequency was tracked in serial peripheral blood. FIG.2B: Refined clustering was performed on 235,851 CD8 ⁺ T-cells from tumor (n=15), adjacent NL (n=12), TDLN (n=3), and one resected brain metastasis (MD043-011). Fourteen unique clusters were visualized and were using T-cell gene programs described in prior studies ¹⁶ . Cluster-defining genes are shown in FIG.9A. FIG.2C: MANA- (red), flu- (blue), and EBV-specific (purple) clonotypes were visualized on the CD8 UMAP. FIG.2D: Antigen-specific gene programs in the TIL were visualized as a heatmap. Comparisons were performed at the individual cell level using a two-sided Wilcoxon rank sum test with p- value adjustment using bonferroni correction. FIG.2E: Expression levels of key markers are shown. FIG.2F: Transcriptional programs between flu-specific and MANA-specific TIL were compared. The top 10 genes significantly upregulated in flu-specific T-cells (blue) and in MANA-specific T-cells (yellow) are shown. FIG.2G: TIL from MD01-004 were cultured with MD01-004-MANA-12 or flu peptide and titrating concentrations of IL7, followed by scRNAseq/TCRseq. In total, 814 flu-specific (410 co-cultured with flu peptide, 404 co-cultured with MANA peptide) and 581 MANA-specific TIL (366 co-cultured with flu peptide, 215 co- cultured with MANA peptide) were detected from a single experiment and were analyzed. Composite expression of an IL7 gene-set by flu-specific and MANA-specific TIL (as determined by their TCR Vβ CDR3) was analyzed. Dose response curve of the mean (+/- standard error) IL7-upregulated gene set-score is shown. FIG.2H: TCRs corresponding to seven MANA- specific clonotypes from two non-MPR (red lines), 3 MANA-specific clonotypes from an MPR (yellow lines), two flu-specific TCRs, and one EBV-specific TCR (orange lines) were tested for ligand-dependent TCR signaling capacity. [00037] FIGS.3A-3E demonstrate the differential gene expression programs of MANA- specific CD8 T-cells in MPR vs. non-MPR. Seven unique MANA-specific clonotypes, representing 45 total transcriptomes, were identified in MPR TIL: 39 from MD01-005, 2 from MD043-003, and 4 from NY016-025. In non-MPR TIL, 16 unique clonotypes, representing 885 total transcriptomes, were identified: 782 from MD043-011, 62 from MD01-004, and 22 from NY016-014. Differential gene expression analysis was performed on the MANA-specific T-cells detected in MPR (n=3) and non-MPR (n=3) tumors. FIG.3A: The top differential genes and selective immune markers of tumor infiltrating MANA-specific T-cells from MPRs and non- MPRs. Comparisons were performed at the individual cell level using two-sided Wilcoxon rank sum test. P-value adjustment was performed using Bonferroni correction. Side bar shows the adjusted p-value (green scale) and response status (red: TIL from MPR, light blue: TIL from non-MPR). FIG.3B: Histograms show the expression of key genes among MANA-specific T- cells from MPR (light blue) and non-MPR (red) tumors. FIG.3C: A violin plot shows IL7R expression by each MANA-specific CD8 T-cell in MPR (red) and non-MPR (light blue) tumors. Comparisons were performed at the individual cell level using two-sided Wilcoxon rank sum test. FIG.3D: A T-cell immune checkpoint score was calculated for each MANA-specific CD8 T-cell detected in MPR (red) and non-MPR (light blue) tumors. This checkpoint score was compared between MPR and non-MPR using two-sided Wilcoxon rank sum test. FIG.3E: The relative correlation coefficient (MPR MANA-specific TIL vs non-MPR MANA-specific TIL) with the immune checkpoint score is shown for genes more highly correlated in non-MPR (yellow) and MPR (blue). ****: P< 0.0001. [00038] FIGS.4A-4H demonstrate that neoadjuvant PD-1 blockade promotes systemic transcriptional re-programming in MANA-specific T-cells from a patient with complete pathologic response. FIG.4A: Longitudinal PBMC were collected from complete pathologic responder MD01-005 (0% residual tumor) during treatment and in post-surgery follow up. Peripheral blood CD8 ⁺ T-cells were FACS sorted based on expression of TCR Vβ2, which corresponds to the MANA-specific CDR3 CASNKLGYQPQHF as identified via the MANAFEST assay (FIG.6). scTCR-seq/RNA-seq was performed on the sorted population from each timepoint. FIG.4B: 2D UMAP projection of expression profiles of 4,409 peripheral blood CD8 ⁺ Vβ2 ⁺ T-cells using UMAP. FIG.4C: Heatmap of the top 5 differential genes, ranked by average fold change, for each T-cell cluster. FIG.4D: 2D UMAP projection of MANA-specific T-cells, identified via the CASNKLGYQPQHF/CASSLLENQPQHF Vβ CDR3, is shown for each timepoint. Clusters were colored using the same color schema as in (FIG.4B). MANA- specific T-cells were highlighted as triangles. FIG.4E: The proportion (%) of cells within each T-cell cluster among all MANA-specific cells identified at W2 and W4 was compared (p values obtained from two-sided Fisher’s exact test and a two-sided test accounting for background cell proportion, both smaller than 0.021, see Methods). FIG.4F: Diffusion plot with RNA velocity for clusters in which MANA-specific T-cells were detected. Cells were randomly downsampled to 100 cells (or all cells in the cluster if cluster size <100 cells) for each cluster for visualization. FIG.4G: Heatmap of the top differential genes along the pseudotime trajectory from Tmem(3) to T _eff (3). FIG.4H: Pseudo-temporal expression of genes that significantly change along the pseudotime from Tmem(3) to Teff(3). Red curves represent the mean temporal function estimates of the three samples in this patient (see Methods). Cells with gene expression > top 1 percentile were removed as outliers. [00039] FIGS.5A-5F define the CD3 ⁺ T cell subsets in non-small cell cancer patients treated with anti-PD1. FIG.5A: FACS gating strategy for sorting CD3 ⁺ T cells. The gating strategy is shown for sorting live CD3 ⁺ T cells from tumor, normal lung, lymph node, or metastasis, when available, on a BD FACSAria™. FIG.5B: Patient and tissue compartment variability across clusters on UMAP. Single-cell RNA-seq/TCR-seq was performed on available resected biospecimens (tumor, adjacent NL, TDLN, and a brain metastasis) from 16 patients treated with neoadjuvant PD-1 blockade. CD3 ⁺ T cells stratified by patient are visualized using UMAP. Each cluster is annotated and marked by color code. FIG.5C: Barplots show the proportion of each T cell cluster in the TDLN, brain metastasis, tumor, and adjacent NL of each patient. Each cluster as shown on the UMAP is denoted by color code. No clusters were driven by a particular patient based. FIG.5D: A density plot of all CD3 ⁺ T cells on the UMAP, stratified by tissue compartment, is shown. Cells were obtained from 15 tumors, 12 adjacent NL specimens, and 3 TDLN. Because a metastasis was sequenced in only one patient, this specimen is not included in this analysis. FIG.5E: The proportion (%) of total CD3 ⁺ T cells made up by each T cell cluster was compared between tumor (n=15 biologically independent samples), adjacent NL (n=12 biologically independent samples), and TDLN (n=3 biologically independent samples). p-values were obtained using Kruskal-Wallis Test and were adjusted for multiple comparisons using Benjamini-Hochberg method. Each dot represents a patient and all data points are shown. Individual data points are superimposed over a Box and Whiskers plot summarizing the data. The middle bar shows the median, with the lower and upper hinges corresponding to the 25 ^th and 75 ^th percentiles, respectively (interquartile range, IQR). The upper whisker extends from the hinge to the largest value no further than 1.5 * IQR from the hinge. The lower whisker extends from the hinge to the smallest value at most 1.5 * IQR of the hinge. FIG.5F: Tissue resident defining genes and core TRM gene set signature on different T cell cluster. The top and middle violin plots show the expression of TRM-defining genes (ITGAE, ZNF683) by each cell in each cluster. The dashed line indicates the mean expression of the respective gene among all CD3 ⁺ T cells. Expression values were log10 transformed for visualization. The bottom violin plot shows the TRM gene-set score for each cluster. This gene-set is comprised of TRM-associated genes. The dashed line shows the mean TRM gene-set score among all T cells. Because the proliferating cluster is driven by proliferation-associated genes and is comprised of mixed cell types, this cluster was not shown in the violin plots. [00040] FIG.6 show the MANA-specific TCRs detected in non-MPR patient MD01-004 using the MANAFEST/ViraFEST assay. Antigen-specific responses identified using the MANAFEST assay are shown for non-MPR MD01-004. Each antigen-specific clonotypic expansion is color coded to indicate if the clone was not detected in the single cell data (blue), detected in the single cell data but not tested via TCR cloning (green), or detected in the single cell data and validated with TCR cloning (red). Data are shown as the percent of MANAFEST ⁺ clonotypes among CD8 ⁺ T cells after 10 day culture. [00041] FIGS.7A-7G show the peripheral dynamics and cross-compartment representation of antigen-specific T cells. Bulk TCRseq was performed on pre- and post- treatment tissue (left panels) and peripheral blood (right panels) for each patient in whom antigen-specific TCRs were identified by ViraFEST/MANAFEST (as shown in FIG.6). Data are shown as the frequency of each flu-, CEF-, and MANA-specific TCR clonotype among all TCRs detected by bulk TCR sequencing of the indicated tissue or peripheral blood timepoint. Antigen- specific clonotypes were not detected by bulk TCRseq of any available tissue/peripheral blood timepoint in patient NY016-025. TDLN, tumor draining lymph node; DLN, draining lymph node. [00042] FIGS.8A-8E demonstrating the TCR cloning validation of MANA-specific TCRs and MANA binding kinetics. Ten TCRs identified via the MANAFEST assay were selected for TCR cloning and transfer into our NFAT/luciferase Jurkat reporter system. Seven of these TCRs recognized the cognate MANA. FIG.8A: In MD01-005, three TCR Vβ clonotypes recognizing the ARVCF H497L-derived EVIVPLSGW MANA were identified by MANAFEST. Single cell analysis determined that the Vβ CDR3s CASNKLGYQPQHF and CASSLLENQPQHF were consistently detected in the same cell and paired with the same Vα CDR3, CALSMGGNEKLTF, likely the result of incomplete allelic exclusive at the beta locus. To validated that these TCRs recognized MD01-005-MANA7, and to determine which Vβ CDR3 was responsible for recognition in the case of incomplete allelic exclusion, all three TCRs were cloned into the Jurkat NFAT luciferase reporter system and tested against autologous LCL loaded with titrating concentrations of MD01-005-MANA7. Data are shown as relative luminescence units (RLU) for MD01-005-MANA7 (solid red square), the cognate wild-type peptide (open red square), or MD01-005-MANA8, which was predicted to bind A*25:01, for each individual TCR. FIG.8B: In non-MPR MD01-004, four TCRs recognizing the p53 R248L- derived NSSCMGGMNLR MANA (MD01-004-MANA12) were identified by MANAFEST and were detected in the single cell data. Each Vβ chain paired exclusively with a single Vα chain. These four TCRs were cloned into the Jurkat NFAT/luciferase reporter system and tested against autologous LCL loaded with titrating concentrations of MD01-004-MANA12. Data are shown as relatively luminescence units (RLU) in response to MD01-004-MANA12 (solid blue square) or the cognate wild-type peptide (open blue square). FIG.8C: In non-MPR MD043-011, a TCR recognizing the CARM1 R208W-derived FAAQAGAWKIY MANA (MD043-011-MANA36) was a candidate for positivity by MANAFEST and was detected in the single cell data. This Vβ chain paired exclusively with a single Vα chain. This TCR was cloned into the Jurkat NFAT/luciferase reporter system and tested against autologous LCL loaded with titrating concentrations of MD043-011-MANA36. Data are shown as relatively luminescence units (RLU) in response to MD01-004-MANA12 (solid green square) or the cognate wild-type peptide (open green square). FIG.8D: The affinity of MD01-005-MANA7 for HLA A*25:01 was assessed using a luminescent oxygen channeling immunoassay (LOCI, left). This is a proximity- based system using a “donor” and “acceptor” bead, each conjugated with an epitope tag. When the donor bead is excited with light at 650nm and can activate an acceptor bead, resulting in a signal at 520-620nm, which can be quantified per second as a surrogate of affinity. A higher number of counts per second indicates higher affinity of the peptide:HLA pair. Data are shown as the number of counts per second for titrating concentrations of MD01-005-MANA7 (solid blue square), the cognate wild-type (open blue square), MD01-005-MANA8, which is predicted to bind HLA A*68:01 (black circle), or no peptide (star). Stability of these same peptides in the HLA A*68:01 complex was also evaluated using a urea-based assay, whereby the stability of the peptide:HLA complex is measured at increasing concentrations of urea (right). Data are shown as the absorbance at 450nm. Data points represent the mean +/- SD of two independent experiments. FIG.8E: Binding (top left) and stability (top right) assays were conducted as in (b) for the p53 R248L-derived MD01-004-MANA12 (solid green square), the cognate wild-type peptide (open green square), a positive control peptide for HLA A*68:01 (orange diamond), the YTAVPLVYV peptide which is predicted to bind A*68:01 (black circle), or no peptide (black star). Data points represent the mean +/- SD of two independent experiments. To determine if MD01-004-MANA12 is endogenously processed and presented by HLA A*68:01, COS-7 cells were transfected with HLA-A*68:01 plasmid and p53 R248L mutant plasmid or p53 wild type plasmid. HLA- and p53-transfected COS-7 cells, autologous APC loaded with MD01-004- MANA12, and HLA-A*68:01-transfected COS-7 were co-cultured with CD8 ⁺ Jurkat reporter cells expressing the MD01-004-MANA12-reactive TCR, Vβ: CATTGGQNTEAFF, V ^^: CILSGANNLFF. Data are shown as relative luminescence units (RLU) for each condition (bottom). [00043] FIGS.9A-9F demonstrate the refined clustering on CD8 T cells. FIG.9A: A heatmap shows the top differential genes, ranked by average fold change, for each refined CD8 T cell cluster.5,000 cells (or all cells in the cluster if cluster size <5000 cells) were randomly sampled from each cluster for visualization (n=16 patients). FIG.9B: Violin plots show the log10 expression of the TRM-defining genes, ITGAE (top) and ZNF683 (HOBIT, middle), and a TRM gene-set score (bottom) for each CD8 T cell cluster. The dashed line indicates the mean expression of the respective gene or gene-set score among all CD8 T cells. Because the proliferating cluster is driven by proliferation-associated genes and represents mixed cell types, this cluster was not shown in the plot. FIG.9C: 2D UMAP red-scale projection of canonical T cell subset marker genes, cell subset selective genes, and immune checkpoints on CD8 T cell subsets. FIG.9D: A heatmap shows the proportion of each refined CD8 T cell cluster (FIG.2B) that is found within each global UMAP T cell cluster (FIG.1B). This enables visualization of the “parent” cluster for the refined CD8 T cell clusters. FIG.9E: A violin plot shows the exhaustion gene-set score, comprised of a published exhaustion gene list, for each refined CD8 T cell cluster. The dashed line shows the mean exhaustion gene-set score among all CD8 T cells. Because the proliferating cluster is driven by proliferation-associated genes and represents mixed cell types, this cluster was not shown in the plot. FIG.9F: CD8 ⁺ T cell clonotypic cluster composition. The top 50 CD8 ⁺ TCR clonotypes in the tumor are shown for each patient, and the proportion of each clonotype that was found within each cluster is designated by the color code. [00044] FIGS.10A-10F demonstrate the distinct phenotype of antigen-specific T cells. FIG.10A: Distribution of MANA-specific T cells on UMAP. Individual MANA-specific clonotypes are shown on the UMAP, stratified by tissue compartment and patient ID. Each color represents a unique MANA-specific clonotype, and each symbol represents a patient. FIG.10B: Distribution of EBV-specific T cells on UMAP. Individual EBV-specific clonotypes are shown on the UMAP, stratified by tissue compartment. Each color represents a unique EBV-specific clonotype and each symbol represents a patient. FIG.10C: Distribution of flu-specific T cells on UMAP. Individual flu-specific clonotypes are shown on the UMAP, stratified by tissue compartment and patient ID. Each color represents a unique flu-specific clonotype, and each symbol represents a patient. The CD8 T cell clusters are annotated according to the designation in FIG.2B. FIG.10D: The barplot (upper) shows the proportion of antigen-specific T cells among total CD8 T cells by tissue compartment (blue bar, adjacent NL; yellow bar, tumor). The dotplot (bottom) shows the proportion of antigen-specific T cells stratified by subset, with the size of the dot representing the proportion among total CD8 T cells (blue dot, adjacent NL; yellow dot, tumor). FIG.10E: TIL and adjacent NL CD8 T cells were downsampled to equal numbers of cells on UMAP before visualization of antigen-specific clonotypes in tumor (left) and adjacent normal lung (right). FIG.10F: The immune checkpoint score and exhaustion score of antigen-specific T cells. A violin plot shows a composite immune checkpoint score (left) and exhaustion score (right) for EBV(purple)-, flu(blue)-, and MANA(red)-specific T cells. [00045] FIGS.11A, 11B show the IL7-induced gene signature between MANA-specific and flu-specific TIL. TIL from patient MD01-004 were cultured with MD01-004-MANA-12 or influenza A peptide and titrating concentrations of recombinant human IL7, followed by coupled sc RNA-seq/TCR-seq. A total of 814 flu-specific (410 co-cultured with flu peptide, 404 co- cultured with MANA peptide) and 581 MANA-specific TIL (366 co-cultured with flu peptide, 215 co-cultured with MANA peptide) were detected in the single cell data from a single experiment and were analyzed. FIG.11A: Composite expression of an IL7 gene-set by flu- specific and MANA-specific TIL (as determined by their TCR Vβ CDR3) stimulated with cognate or non-cognate antigen is shown. FIG.11B: Dose-response curve showing the fold change of averaged expression of IL7-induced genes that significantly changed from baseline (no IL7 vs 0.1 ng/ml) in flu-specific (red) or MANA-specific (blue) T cells. Comparisons were performed using two-sided Wilcoxon rank sum test and adjusted for multiple comparisons using BH method. [00046] FIGS.12A-12E demonstrate the cloning and dose response of antigen-specific T cells. FIG.12A: Cloning and screening of TCRs corresponding to CD8 T cells with highly differential gene expression relative to flu-specific T cells. Seven TCRs were selected from the refined CD8 sc data based on highly differential gene expression relative to flu-specific T cells. These TCRs were cloned into the Jurkat/NFAT luciferase reporter system and first screened against autologous LCL pre-loaded with pools of putative MANA peptides (10μg/ml) based on the respective patient’s WES and MANA predictions. Three TCRs recognized a MANA peptide pool, one each from patients MD01-005 (FIG.12A), MD01-004 (FIG.12B), and MD043-011 (FIG.12C). The reactive MANA was then mapped from the reactive peptide pool by stimulating the TCR-transfected Jurkat cell with autologous LCL pre-loaded with 10μg/ml of each individual MANA within the reactive pool (center). Dose-response curves were then generated for each MANA-specific TCR (right). Data are shown as relative luminescence units. A (+) sign indicates the positive response. FIG.12D: Functional characterization of MANAFEST-identified and screening-identified TCRs.2D projection of clones identified from the MANAFEST assay (red) and clones identified via cloning of TCRs corresponding to T cells with differential gene expression relative to flu-specific T cells (green) is shown for patients MD01-004, MD01-005, and MD043-011. CD8 T cell clusters are marked with the same color code as FIG.2B. FIG. 12E: Viral-specific TCRs and MANA-specific TCRs from one MPR and two non-MPRs were cloned into the Jurkat reporter system and tested against titrating concentrations of relevant peptide. The average log10 relative luminescence of viral-specific TCRs (blue, 3 clonotypes from 3 different patients), MANA-specific MPR TCRs (green, 3 clonotypes from 1 MPR), and MANA-specific non-MPR TCRs (red, 7 clonotypes from 2 non-MPRs) was compared at each peptide titration. Data are shown as a Box and Whiskers plot. The middle bar shows the median, with the lower and upper hinges corresponding to the 25 ^th and 75 ^th percentiles, respectively (interquartile range, IQR). The upper whisker extends from the hinge to the largest value no further than 1.5 * IQR from the hinge. The lower whisker extends from the hinge to the smallest value at most 1.5 * IQR of the hinge. Comparisons of relative luminescence units for viral- specific vs MANA-specific T cell clonotypes at different titrations were performed using two- sided Wilcoxon rank sum test. ns: p>0.05; *, 0.01<p<0.05 [00047] FIGS.13A-13C show a patient representation of antigen-specific clonotypes. Barplots summarize the total number of unique tumor-infiltrating clonotypes (FIG.13A) and cells (FIG.13B), stratified by antigen specificity and method of detection (MANAFEST or based on the TRM gene signature and cloning/peptide screen). Different colors represent the patient identity. FIG.13C: Visualization of clonotypes included in the MANA-specific analysis. The individual UMAP projections of clonotypes that were validated (left) and were not validated (right) by TCR cloning are shown. Of the cells that corresponded to a MANAFEST-identified, MANA-specific clonotype that was detected in the single cell data, >94% were validated by the Jurkat/luciferase TCR cloning system. [00048] FIGS.14A-14G show the signatures of MANA-specific T cells according to response and tissue compartment. FIG.14A: Exhaustion score and co-expression of immune checkpoints/effector/memory function gene on MANA-specific TIL. Violin plot shows the exhaustion gene-set score of MANA-specific TIL of non-MPR (red, n=3) and MPR (light blue, n=3) tumors. Comparisons were performed at the individual cell level using two-sided Wilcoxon rank sum test without multiple comparison adjustment. FIG.14B: Heatmap shows co-expression of immune checkpoints and effector/memory genes on MANA-specific TIL. Each column represent a cell. The exhaustion score, response status, and patient IDs are designated by the relevant color bar. For visualization, MANA-specific T cells were downsampled to the same number of cells from MPR (n=3) and non-MPR (n=3). FIG.14C: Top ranked genes correlated with the immune checkpoint score in MANA-specific TIL. Barplots show the correlation coefficients of the top ranked genes highly correlated with the immune checkpoint score in MPR (left) and non-MPR (right) MANA-specific TIL. FIG.14D: MANA-specific T cells found in the tumor (red triangles) and TDLN (blue triangles) of patients MD01-004, MD01-005, and MD043- 011 were projected on the refined CD8 UMAP. FIG.14E: Expression of selective genes is shown for MANA-specific T cells in the tumor and TDLN (n=3). FIG.14F: MANA-specific T cells found in the tumor (red triangle) and brain metastasis (purple triangle) are shown on the UMAP for patient MD043-011. FIG.14G: The scatterplot shows the average expression of genes comparing all refined CD8 T cells from the primary tumor and metastatic brain resection in patient MD043-011. The top differential genes enriched in the brain metastasis are labeled in red. Comparisons were performed at the individual cell level using two-sided Wilcoxon rank sum test. P-value adjustment was performed using bonferroni correction. CD8 T cell clusters are marked by the same color code as FIG.2B. [00049] FIGS.15A-15D show the canonical correlations of CD8 T cell clusters with pathologic response. The canonical correlation between pathologic response status and CD8 T cell clusters vs. a MANA-specific T cell-enriched cluster was evaluated. FIG.15A: Selection of MANA-specific T cell enriched clusters (Proliferating, TRM(IV), TRM (V) and TRM (II)) based on > 2 fold change (red dotted line) of MANA-specific T cell frequency relative to random expectation. The above 4 clusters were combined as a ‘MANA-combined’ cluster. FIG.15B: Combined MANA-specific T cell enriched clusters showed the highest canonical correlation with pathologic response. FIG.15C: Principal component analysis (PCA) of pseudobulk gene expression from all CD8 T cell clusters for individual tumor samples (n=15, 6 MPRs and 9 non- MPRs), colored by response status (MPR as blue blue dots, non-MPR as red dots). FIG.15D: Principal component analysis (PCA) of pseudobulk gene expression from combined MANA enriched T cell cluster for individual tumor samples (n=15, 6 MPRs and 9 non-MPRs), colored by response status (MPR as light blue dots, non-MPR as red dots). P-values were obtained using a one-sided permutation test, without correction for multiple comparisons. [00050] FIGS.16A-16F show the phenotypic characteristics of FACS-sorted peripheral blood CD8 ⁺ /Vβ2 ⁺ T cells from MPR MD01-005. FIG.16A: Selective gene expression of 2D UMAP red-scale projection is shown of canonical T cell subset marker genes, cell subset selective genes, and immune checkpoints on CD8 T cell subsets sorted from longitudinal peripheral blood of one patient (MD01-005) with complete pathologic response. FIGS.16B- 16D: Pseudotime reconstruction and pseudo-temporal dynamic gene identification in peripheral blood CD8 T cells from a complete pathologic responder. Longitudinal PBMC were collected from complete pathologic responder MD01-005 (0% residual tumor) during treatment and in post-surgery follow up. Peripheral blood CD8 ⁺ T cells were FACS sorted based on expression of TCR Vβ2, which corresponds to the MANA-specific CDR3 CASNKLGYQPQHF as identified previously via the MANAFEST assay (FIG.6). scTCRseq/RNAseq was performed on the sorted population from each timepoint. FIG.16B: Constructing the pseudotime axis on the diffusion map from T _mem (3) to T _eff (3) as trajectory 1. FIG.16C: GO analysis for genes that significantly change along trajectory 1, ranked by FDR. FIG.16D: Constructing the pseudotime axis on the diffusion map from Tmem(3) to Tmem(2) as trajectory 2. FIG.16E: GO analysis for genes that significantly change along trajectory 2, ranked by FDR. FIG.16F: Heatmap showing genes that significantly change along trajectory 2 (FDR<0.05). DETAILED DESCRIPTION [00051] Blocking inhibitory receptors, such as PD-1 and CTLA-4, has revolutionized cancer therapy, leading to clinically durable reductions in tumor burden in multiple human cancers (Wei, S.C., et al.2018. Fundamental mechanisms of immune checkpoint blockade therapy. Cancer Discov.8:1069–1086). While the molecular pathways regulating inhibitory receptor expression and tumor-infiltrating lymphocyte (TIL) dysfunction are being actively investigated, less is known about the molecular pathways involved in maintaining the effector functions of these cells (Scott, A.C., et al.2019. TOX is a critical regulator of tumour-specific T cell differentiation. Nature.571:270–274; Khan, O., et al.2019. TOX transcriptionally and epigenetically programs CD8 ⁺ T cell exhaustion. Nature.571:211–218; Khan, O., et al.2019. TOX transcriptionally and epigenetically programs CD8 ⁺ T cell exhaustion. Nature.571:211– 218; Alfei, F., et al.2019. TOX reinforces the phenotype and longevity of exhausted T cells in chronic viral infection. Nature.571:265–269). [00052] T cell accumulation in tumors is a highly regulated multistep process. In addition to promoting a locally immunosuppressive environment that contributes to T cell dysfunction, some tumors actively exclude T cell entry (Peranzoni, E., et al.2018. Macrophages impede CD8 T cells from reaching tumor cells and limit the efficacy of anti-PD-1 treatment. Proc. Natl. Acad. Sci. USA.115:E4041–E4050; Mariathasan, S., et al.2018. TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature.554:544–548). Such exclusion produces an immune cell–poor profile correlating with reduced clinical responses to immunotherapy (Kather, J.N., et al.2018. Topography of cancer-associated immune cells in human solid tumors. eLife.7. e36967). Successful accumulation of T cells in tumors is dependent on expression of several cellular adhesion pathways, including integrins such as αeβ7 and αLβ2 (Park, S.L., et al.2019. Tissue-resident memory CD8 ⁺ T cells promote melanoma-immune equilibrium in skin. Nature.565:366–371; Harjunpää, H., et al.2019. Cell adhesion molecules and their roles and regulation in the immune and tumor microenvironment. Front. Immunol. 10:1078). The relative level of expression and activation state of these molecules on T cells mediates adhesion to, and movement within, the tumor microenvironment through direct interaction with ligands on tumor cells, stromal cells, and other immune cells (Hammer, J.A., et al. 2019. Origin, Organization, Dynamics, and Function of Actin and Actomyosin Networks at the T Cell Immunological Synapse. Annu. Rev. Immunol.37:201–224). Furthermore, LFA-1 directly contributes to the ability of T cells to kill tumor cells by facilitating formation of T cell– tumor cell immune synapses. LFA-1 itself is constitutively expressed on the cell surface in a low-affinity confirmation that demonstrates poor binding to its ligand, ICAM-1 (Sun, Z., M. Costell, and R. Fässler.2019. Integrin activation by talin, kindlin and mechanical forces. Nat. Cell Biol.21:25–31). However, upon stimulation, this integrin is induced to undergo a conformational change that dramatically increases ligand affinity (Walling, B.L., and M. Kim. 2018. LFA-1 in T cell migration and differentiation. Front. Immunol.9:952). Thus, the overall adhesive capacity of TILs is intricately linked with their ability to kill tumor cells. It is currently unknown how these processes are regulated in the tumor microenvironment (Kelly M. Mahuron et al.,. J Exp Med (2020) 217 (9): e20192080). [00053] Checkpoint Molecules [00054] Programmed death 1 (PD-1): PD-1 also known as CD279 is a 288-amino acid type I transmembrane protein receptor and is a negative regulator of immune responses (Akinleye, A., Rasool, Z. Immune checkpoint inhibitors of PD-L1 as cancer therapeutics. J Hematol Oncol 12, 92 (2019). doi.org/10.1186/s13045-019-0779-5). The protein is predominantly expressed on antigen-experienced memory T cells in peripheral tissues and less commonly on B cells, activated monocytes, dendritic cells (DCs), and natural killer (NK) cells (Keir ME, et al. PD-1 and its ligands in tolerance and immunity. Annu Rev Immunol. 2008;26:677–704; Ishida Y, et al. Induced expression of PD-1, a novel member of the immunoglobulin gene superfamily, upon programmed cell death. EMBO J.1992;11(11):3887– 95). It is encoded by the PDCD1 gene that maps to a 55-kDa DNA fragment that consists of 5 exons located on chromosome 2. PD-1 is homologous to the CD28 family of protein receptors and composed of immunoglobulin V (IgV)-like extracellular domain that shares sequences identical to other members of the CD28 family proteins, a transmembrane domain, and a cytoplasmic (intracellular) domain of approximately 95 residues that contains 2 phosphorylation sites located in an immunoreceptor tyrosine-based inhibitory motif (ITIM) and an immunoreceptor tyrosine-based switch motif, which, upon phosphorylation, negatively regulates T cell receptor (TCR) signals through phosphorylating Src homology phosphatase-1 (SHP-1) and SHP-22 (Keir ME, et al. Annu Rev Immunol.2008;26:677–704; Ishida Y, et al. EMBO J. 1992;11(11):3887–95). [00055] PD-L1 (also known as B7-H1 or CD274) and PD-L2 (also known as B7-DC or CD273) are the two ligands for PD-1 (Freeman GJ, et al. Engagement of the PD-1 immunoinhibitory receptor by a novel B7 family member leads to negative regulation of lymphocyte activation. J Exp Med.2000;192(7):1027–34). They are members of the B7 family of type I transmembrane protein receptors. Structurally, PD-L1 is a 290-amino acid protein receptor encoded by Cd274 gene, comprising of 7 exons, and located on chromosome 9 in humans (Keir ME, et al. Annu Rev Immunol.2008;26:677–704; Ishida Y, et al. EMBO J. 1992;11(11):3887–95; Freeman GJ, et al. J Exp Med.2000;192(7):1027–34). It is composed of 2 extracellular domains, IgV- and IgC-like domains; a transmembrane domain; and a cytoplasmic (intracellular) domain. The intracellular domain of PD-L1 is short comprising of 30 amino acids, and there is no known function for this domain. The protein is constitutively expressed on many cell types, including antigen-presenting cells (APCs), T cells, B cells, monocytes, and epithelial cells, and is upregulated in a number of cell types after the activation in response to proinflammatory cytokines such as IFNγ and IL4 through signal transducer and activator of transcription-1 (STAT1) and IFN regulatory factor-1 (IRF1). [00056] Evidence suggests that interaction of PD-L1/PD-1 in the tumor microenvironment promotes T cell dysfunction, exhaustion, apoptosis, neutralization, and elaboration of IL-10 in a tumor mass creating a state of resistance from cytotoxic T cell (CD8 ⁺ )-mediated tumor cell killing (Zou W, Chen L. Inhibitory B7-family molecules in the tumour microenvironment. Nat Rev Immunol.2008;8(6):467–77; Sun Z, et al. IL10 and PD-1 cooperate to limit the activity of tumor-specific CD8 ⁺ T cells. Cancer Res.2015;75(8):1635–44. It promotes cancer development and progression by enhancing tumor cell proliferation and survival. [00057] Immune checkpoint inhibitors, especially PD-1 and PD-L1 have shown clinical efficacies against many different solid and hematologic malignancies (Butte MJ, et al. Programmed death-1 ligand 1 interacts specifically with the B7-1 costimulatory molecule to inhibit T cell responses. Immunity.2007;27(1):111–22). Binding of PD-L1 to its receptor suppresses T cell migration, proliferation, and secretion of cytotoxic mediators, and restricts tumor cell killing. Inhibitors of PD-1 and PD-L1 disrupt PD-1 axis thereby reverses T cell suppression and enhances endogenous antitumor immunity to unleash long-term antitumor responses for patients with a wide range of cancers (Paterson AM, et al. The programmed death- 1 ligand 1:B7-1 pathway restrains diabetogenic effector T cells in vivo. J Immunol. 2011;187(3):1097–105). In addition to binding PD-1, PD-L1 also interacts with B7 (CD80, CD86) creating negative signals on T cells and dampens antitumor immunity. [00058] Layilin (LAYN): Layilin (LAYN), which was first reported in 1998, is a protein encoding-gene located on chromosome 11 (Borowsky ML, Hynes RO. Layilin, a novel talin- binding transmembrane protein homologous with C-type lectins, is localized in membrane ruffles. J Cell Biol. (1998) 143:429–42). Layilin, a 55-kDa transmembrane protein with homology to C-type lectin, is expressed in many cell types and organs. Moreover, LAYN proteins can act as a surface receptor for hyaluronan (HA). Thus, LAYN plays an important role in cell adhesion, motility, regulation of cell spreading and migration (Bono P, et al. Layilin, a novel integral membrane protein, is a hyaluronan receptor. Mol Biol Cell (2001) 12:891–900. doi: 10.1091/mbc.12.4.891; Weng L, et al. Molecular cloning and characterization of human chondrolectin, a novel type I transmembrane protein homologous to C-type lectins. Genomics (2002) 80:62–70. doi: 10.1006/geno.2002.6806). Previous studies (Adachi T, Arito M, Suematsu N, Kamijo-Ikemori A, Omoteyama K, Sato T, et al. Roles of layilin in TNF- alpha-induced epithelial-mesenchymal transformation of renal tubular epithelial cells. Biochem Biophys Res Commun. (2015) 467:63–9. doi: 10.1016/j.bbrc.2015.09.121) indicate that LAYN is involved in the tumor necrosis factor-α (TNF-α) induced epithelial-mesenchymal transition (EMT) of renal tubular epithelial cells as well as plays a critical role in HA35-induced intestinal epithelial tight junctions in inflammatory bowel disease (Kim Y, et al. Layilin is critical for mediating hyaluronan 35kDa-induced intestinal epithelial tight junction protein ZO-1 in vitro and in vivo. Matrix Biol. (2017) 66:93–109. doi: 10.1016/j.matbio.2017.09.003). LAYN was first shown to be associated with cancer in a report demonstrating that low levels of LAYN protein can reduce cell invasion and lymph node metastasis A549 lung cancer cells (Chen Z,et al. Down-regulation of layilin, a novel hyaluronan receptor, via RNA interference, inhibits invasion and lymphatic metastasis of human lung A549 cells. Biotechnol Appl Biochem. (2008) 50:89–96. doi: 10.1042/ba20070138). These findings suggest the LAYN plays an important role in cancer progression, invasion and metastasis. [00059] LAYN expression is a specific signature present in colorectal cancer (CRC) and non-small cell lung changer (NSCLC) infiltrating regulatory T lymphocytes (Treg) from CRC and NSCLC patient samples. In addition, high LAYN expression was related to poor prognosis in CRC and NSCLC patients (De Simone M, et al. Transcriptional landscape of human tissue lymphocytes unveils uniqueness of tumor-infiltrating T regulatory cells. Immunity (2016) 45:1135–47. doi: 10.1016/j.immuni.2016.10.021). A previous study (Zheng C, et al. Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing. Cell (2017) 169:1342– 56.e1316. doi: 10.1016/j.cell.2017.05.035) further found the LAYN is a crucial gene involved in liver cancer tumor-infiltrating lymphocytes. Single-cell RNA sequencing of T cells confirmed that LAYN was up regulated in activated CD8 ⁺ T and Treg cells and represses CD8 ⁺ T cell functions in vitro. These findings suggest that LAYN has multifaceted functional roles in Treg cells and tumor-infiltrating lymphocytes. [00060] Protein Kinase A Anchoring Proteins (AKAP): Protein kinase A anchoring proteins (AKAP) are a family of structurally diverse proteins, which share a common motif at their C terminus that binds to the regulatory subunits of the cyclic AMP-dependent protein kinase (PKA). In addition, AKAPs mediate signal integration through protein-protein binding domains that bind to other kinases, phosphatases, GPCR, effector enzymes, and channels (Klauck T.M. et al. Coordination of three signaling enzymes by AKAP79, a mammalian scaffold protein. Science.1996; 271: 1589-1592; Logue J.S., Scott J.D. Organizing signal transduction through A-kinase anchoring proteins (AKAPs). FEBS J.2010; 277: 4370-4375). By scaffolding these diverse but functionally complementary proteins, AKAPs form local signaling networks that can modulate the microenvironment, metabolism, and downstream signaling of cyclic AMP (Wong W., Scott J.D. AKAP signaling complexes: focal points in space and time. Nat. Rev. Mol. Cell Biol.2004; 5: 959-970). Gene knockdown and overexpression methodologies identified numerous functions for individual AKAP in regulating the signaling outputs of GPCRs. [00061] AKAP5 is a membrane-bound AKAP that, in addition to binding PKA, binds to PKC, calcineurin (PP2B), membrane-associated guanylate kinase protein SAP97, adenylyl cyclase V/VI, and other signaling and scaffolding proteins (Xin Li et al., Role of AKAP79/150 Protein in β1-Adrenergic Receptor Trafficking and Signaling in Mammalian Cells. Signal Transduction. Volume 288, issue 47, P33797-33812, November 2013). AKAP5-anchored complexes play a key role in regulating GPCR signaling in general and β-adrenergic signaling in particular. Disruption of AKAP-PKA interactions by the st-Ht31 peptide significantly increased the duration of plasma membrane-delineated cyclic AMP (Horvat S.J. et al., A-kinase anchoring proteins regulate compartmentalized cyclic AMP signaling in airway smooth muscle. FASEB J. 2012; 26: 3670-3679). [00062] FAM3C: FAM3C or ILEI is a secreted factor that contributes to the epithelial-to- mesenchymal transition (EMT), a cell biological process that confers metastatic properties to a tumor cell (Ken Noguchi et al. Interleukin-like EMT inducer regulates partial phenotype switching in MITF-low melanoma cell lines. PLOS One, doi.org/10.1371/journal.pone.0177830). FAM3C or ILEI was originally identified using a secondary structure-based prediction strategy to discover novel cytokines (Zhu Y, et al. Cloning, expression, and initial characterization of a novel cytokine-like gene family. Genomics.2002;80(2):14-50. Epub 2002/08/06. pmid:12160727). It was predicted that the FAM3 family of proteins would have secreted cytokine activity due to the presence of a four-helix-bundle commonly observed in the interleukin family of cytokines. Subsequently, ILEI has been described as an inducer of the epithelial-to-mesenchymal transition (Katahira T., et al. Secreted factor FAM3C (ILEI) is involved in retinal laminar formation. Biochemical and Biophysical Research Communications. 2010;392(3):301–6. pmid:20059962. Waerner T., et al. ILEI: a cytokine essential for EMT, tumor formation, and late events in metastasis in epithelial cells. Cancer Cell.2006;10(3):227– 39. Epub 2006/09/09. pmid:16959614; Lahsnig C, et al. ILEI requires oncogenic Ras for the epithelial to mesenchymal transition of hepatocytes and liver carcinoma progression. Oncogene. 2009;28(5):638–50. pmid:19015638; Csiszar A, et al. Breast Cancer Research: BCR. 2014;16(5):433-. pmid:25212966; Song Q, Sheng W, Zhang X, Jiao S, Li F. ILEI drives epithelial to mesenchymal transition and metastatic progression in the lung cancer cell line A549. Tumour Biol.2014;35(2):1377–82. Epub 2013/09/28. pmid:24072492). Regulators of ILEI include autophagy (Kraya AA, et al. Identification of secreted proteins that reflect autophagy dynamics within tumor cells. Autophagy.2015;11(1):60–74. Epub 2014/12/09. PubMed Central PMCID: PMC4502670. pmid:25484078), the ubiquitin/proteasome system (Sun Y, Jia X, Gao Q, Liu X, Hou L. The ubiquitin ligase UBE4A inhibits prostate cancer progression by targeting interleukin-like EMT inducer (ILEI). IUBMB life.2016. Epub 2016/11/20), and TGF- β/AKT2/hnRNP-E1 (Chaudhury A, et al. TGF-beta-mediated phosphorylation of hnRNP E1 induces EMT via transcript-selective translational induction of Dab2 and ILEI. Nature Cell Biology.2010;12(3):286–93. pmid:20154680; Hussey GS, et al. Identification of an mRNP complex regulating tumorigenesis at the translational elongation step. Molecular Cell. 2011;41(4):419–31. pmid:21329880). [00063] KLRD1 (CD94): CD94/NKG2 is a heterodimer expressed on natural killer (NK) and a small subset of T cells. This receptor varies in function as an inhibitor or activator depending on which isoform of NKG2 is expressed. The ligand for CD94/NKG2 is HLA-E in human and its homolog, Qa1 in mouse, which are both nonclassical class I molecules that bind leader peptides from other class I molecules. Although <5% of CD8 T cells express the receptor in a naïve mouse, its expression is upregulated upon specific recognition of antigen. Similar to NK cells, most CD8 T cells that express high levels of CD94 co-express NKG2A, the inhibitory isoform. The engagement of this receptor can lead to a blocking of cytotoxicity. However, these receptors have also been implicated in the cell survival of both NK and CD8T cells. The level of CD94 expression is inversely correlated with the level of apoptosis in culture. Thus, CD94/NKG2 receptors may regulate effector functions and cell survival of NK cells and CD8 T cells, thereby playing a crucial role in the innate and adaptive immune response to a pathogen (Gunturi, A., Berg, R.E. & Forman, J. The role of CD94/NKG2 in innate and adaptive immunity. Immunol Res 30, 29–34 (2004). doi.org/10.1385/IR:30:1:029). [00064] KLRC2: The CD94:NKG2 family of heterodimeric receptors, expressed on subsets of human natural killer (NK) and T lymphocytes, monitor the expression of HLA-E, presenting peptides mostly derived from the signal sequence of other HLA class I alpha chains. CD94:NKG2 heterodimers deliver inhibitory or activating signals, depending on the NKG2 subunit (mainly NKG2A and NKG2C, respectively). CD94 and all NKG2 subunits are type II membrane-integral glycoproteins of the C-type lectin-like superfamily, with 49%–94% identity in their coding sequence. Their genes are located in the Natural Killer gene Complex (NKC) on chromosome 12, which encompasses nearly 2 Mbp, and encodes additional homologs of the same family. [00065] The activating NKG2C (or CD159c) subunit is encoded by the KLRC2 gene, with a length of ca.6 kbp comprising a 696-bp coding sequence segmented into six exons (Asenjo J, et al. Complete genomic characterization of a new KLRC2 allele, NKG2C*03. HLA.2021;1–3. doi.org/10.1111/tan.14231). [00066] XB130 (AFAP1L2): XB130 is a novel adapter protein that behaves as a tumor promoter or suppressor mediating cell proliferation and metastasis in the development of different human tumors. Altered expression of XB130 has been verified in human non-small cell-lung cancer (NSCLC) (Wang Q, et al. XB130, regulated by miR-203, miR-219, and miR- 4782-3p, mediates the proliferation and metastasis of non-small-cell lung cancer cells. Mol Carcinog.2020 May;59(5):557-568. doi: 10.1002/mc.23180. Epub 2020 Mar 11. PMID: 32159887). XB130 is strongly expressed in the spleen and thyroid of humans, while it shows weak expression in the kidney, brain, lung, and pancreas (Xu J, et al. XB130, a novel adaptor protein for signal transduction. J Biol Chem.2007;282:16401–16412). XB130 has been detected in human esophageal squamous cell carcinoma (ESCC) (Shiozaki A, et al. XB130 as an Independent Prognostic Factor in Human Esophageal Squamous Cell Carcinoma. Ann Surg Oncol.2013;20:3140–50), follicular and papillary thyroid carcinoma, as well as in human lung carcinoma cell lines (Shiozaki A, et al. XB130, a novel adaptor protein, promotes thyroid tumor growth. Am J Pathol.2011;178:391–401). In ESCC cells, expression of XB130 may affect cell cycle progression and impact prognosis of patients with ESCC. In thyroid and lung cancer cells, XB130 has been implicated as a substrate and regulator of tyrosine kinase-mediated signaling and in controlling cell proliferation and apoptosis. In gastric cancer, reduced XB130 protein expression is a prognostic biomarker for shorter survival and a higher recurrence rate in patients with GC, as well as for the response to chemotherapy (Shi M, et al. Silencing of XB130 is associated with both the prognosis and chemosensitivity of gastric cancer. PLoS One. 2012;7:e41660). However, in patients with HCC, protein expression of XB130 is not associated with the postoperative prognosis of patients with HCC (Zuo Q, et al. Multivariate analysis of several molecular markers and clinicopathological features in postoperative prognosis of hepatocellular carcinoma. Anat Rec (Hoboken) 2012;295:423–31). [00067] XB130 has been found to promote growth of cancer cells by regulating expression of tumor suppressive miRNAs and their targeted genes (Takeshita H, et al. XB130, a new adaptor protein, regulates expression of tumor suppressive microRNAs in cancer cells. PLoS One.2013;8:e59057). XB130 can regulate cell proliferation and survival through modulating selected down-stream signals of PI3K/Akt pathway (Shiozaki A, et al. XB130 mediates cancer cell proliferation and survival through multiple signaling events downstream of Akt. PLoS One.2012;7:e43646). XB130 is also a novel Rac- and cytoskeleton-regulated and cytoskeleton- regulating adaptor protein that exhibits high affinity to lamellipodial (branched) F-actin and impacts motility and invasiveness of tumor cells (Lodyga M, et al. Adaptor protein XB130 is a Rac-controlled component of lamellipodia that regulates cell motility and invasion. J Cell Sci.2010;123:4156–69). [00068] XB130 silencing has been found to significantly inhibit cell growth, migration and invasion, and reverses EMT. Furthermore, XB130 is posttranscriptionally regulated by miR- 203, miR-219, and miR-4782-3p. Overexpression of miR-203, miR-219, or miR-4782-3p inhibits cell growth, migration and invasion, and reverses EMT, just like the role of XB130 in NSCLC cells, whereas the suppressive effects of microRNA (miRNA) overexpression were weakened by miRNA inhibitors or ectopic expression of XB130 in NSCLC cells (Wang Q, et al. Mol Carcinog.2020 May;59(5):557-568. doi: 10.1002/mc.23180. Epub 2020 Mar 11. PMID: 32159887). [00069] Checkpoint Inhibitors [00070] Immune checkpoints refer to inhibitory pathways of the immune system that are responsible for maintaining self-tolerance and modulating the duration and amplitude of physiological immune responses. [00071] Certain cancer cells thrive by taking advantage of immune checkpoint pathways as a major mechanism of immune resistance, particularly with respect to T cells that are specific for tumor antigens. For example, certain cancer cells may overexpress one or more immune checkpoint proteins responsible for inhibiting a cytotoxic T cell response. Thus, immune checkpoint modulators may be administered to overcome the inhibitory signals and permit and/or augment an immune attack against cancer cells. Immune checkpoint modulators may facilitate immune cell responses against cancer cells by decreasing, inhibiting, or abrogating signaling by negative immune response regulators (e.g. CTLA4), or may stimulate or enhance signaling of positive regulators of immune response (e.g. CD28). [00072] Immunotherapy agents targeted to immune checkpoint modulators may be administered to encourage immune attack targeting cancer cells. Immunotherapy agents may be or include antibody agents that target (e.g., are specific for) immune checkpoint modulators. Specific examples of antibody agents may include monoclonal antibodies. Certain monoclonal antibodies targeting immune checkpoint modulators are available. For instance, ipilumimab targets CTLA-4; tremelimumab targets CTLA-4; pembrolizumab targets PD-1, etc. [00073] Atezolizumab, formerly known as MPDL3280, is a fully humanized IgG1 monoclonal antibody that is engineered with a modification in the Fc domain that eliminates antibody-dependent cellular cytotoxicity to prevent depletion of T cells expressing PD-L1. The compound blocks the interaction of PD-L1, specifically on tumor cells and tumor-infiltrating immune cells, with both PD-1 and B7.1, but not the interaction of PD-L2. In preclinical studies, atezolizumab have shown an increased level of proliferating CD8 ⁺ T cells by inducing cytokine changes including transient increases in IL-18, IFNγ, and CXCL11, as well as transient decrease in IL-6 (Inman BA, et al. Atezolizumab: a PD-L1-blocking antibody for bladder cancer. Clin Cancer Res.2017;23(8):1886–90; Deng R, et al. Preclinical pharmacokinetics, pharmacodynamics, tissue distribution, and tumor penetration of anti-PD-L1 monoclonal antibody, an immune checkpoint inhibitor. MAbs.2016;8(3):593–603). Through the inhibition of PD-L1, atezolizumab reduces immunosuppressive signals found within the tumor microenvironment and consequently increases T cell-mediated immunity against tumors. [00074] Durvalumab, also known as MEDI4736, is a fully human IgG1 monoclonal antibody that binds with high affinity and specificity to PD-L1, blocking the interaction with PD- 1 and CD80 molecules (Mok, T., et al., J Thorac Oncol Vol.11, Suppl.4S (2016) S113–S142, 2016; Stewart R, et al. Cancer Immunol Res.2015;3(9):1052–62). The compound is uniquely engineered to prevent antibody-dependent cell-mediated cytotoxicity on T cells expressing PD- L1. Durvalumab is a potent inhibitor with subnanomolar activity [PD-1 (IC ₅₀  = 0.1 nM) and CD80 (IC ₅₀  = 0.04)] against PD-L1. [00075] Avelumab (MSB0010718C) is another fully human IgG1 monoclonal antibody that specifically binds to PD-L1, preventing the interaction between PD-L1 and the inhibitory T cell receptors, PD-1 and B7.1 resulting in T cell-mediated, adaptive antitumor immune responses and T cell reactivation and cytokine production (Butte MJ, et al. Programmed death-1 ligand 1 interacts specifically with the B7-1 costimulatory molecule to inhibit T cell responses. Immunity. 2007;27(1):111–22; Grenga I, et al. Clin Transl Immunol.2016;5(5):e8). Unlike atezolizumab and durvalumab, avelumab has a wild-type IgG1 crystallizable fragment (Fc) region, which enables the compound to engage with Fc-γ receptors on natural killer cells and induce tumor- directed antibody-dependent cell-mediated cytotoxicity (ADCC) in preclinical studies (Boyerinas B, et al. Cancer Immunol Res.2015;3(10):1148–57; Fujii R, et al. Oncotarget. 2016;7(23):33498–511). [00076] Envafolimab (also known as KN 035 and ASC 22) is a first-in-class nanobody (single domain antibody) created by a fusion of the of anti-PD-L1 domain with Fc fragment of human IgG1 antibody that binds with high affinity and specificity to PD-L1, blocking interaction with PD-1, and resulting in T cell-mediated immune response to neoplasms. In biochemical assays, envafolimab blocks interaction between PD-L1 and PD-1 with an IC ₅₀ value of 5.25 nm in a competitive ELISA (Zhang F, et al. Cell Discov.2017;3:17004). In contrast to other PD-L1 inhibitors, envafolimab is administered as a subcutaneous injection and demonstrates low immunogenicity and better penetration in tumor tissue in animal studies. In in vitro studies, the compound demonstrates dose- and time-dependent induction of T cell cytokine production in a mixed lymphocyte reaction. In xenograft models, envafolimab shows potent antitumor activity at comparable dosages (0.1–0.5 mg kg−1). In a phase I dose-escalation study, it was reported that envafolimab exhibited favorable safety profile and preliminary evidence of encouraging anti- tumor activity in patients with advanced solid tumors (Papadopoulos, K., et al., Annals of Oncology, Volume 29, Issue suppl_8, 1 October 2018, mdy288.013, 2018). The compound was given subcutaneously at a dosage of 0.01, 0.03, 0.1, 0.3, 1.0, 2.5, 5.0, and 10.0 mg/kg weekly. [00077] BMS-936559 (also known as MDX-1105) is a high-affinity fully humanized IgG4 monoclonal antibody that specifically inhibits PD-L1 binding to both PD-1 and CD80 (Brahmer JR, et al. Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. N Engl J Med.2012;366(26):2455–65). [00078] CK-301 is a fully human monoclonal antibody of IgG1 subtype that directly binds to PD-L1 and blocks its interactions with PD-1 and B7.1 receptors. Similar to avelumab, CK-301 has functional Fc domain and is capable of inducing ADCC and complement-dependent cytotoxicity (CDC)-mediated killing of PD-L1 ⁺ cell lines, including lymphoma cells. In the cellular assay, the compound exhibited subnanomolar binding affinity for PD-L1 with increased production interferon-gamma by primary human T cells in mixed lymphocyte reaction (MLR) culture (Gorelik, L., et al., Preclinical characterization of a novel fully human IgG1 anti-PD-L1 mAb CK-301 In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4606. doi:10.1158/1538-7445.AM2017-4606, 2017). [00079] As a novel, highly potent, first-in-class full-length IgG4 monoclonal antibody, CS-1001 selectively binds to PD-L1 and blocks interaction with PD-1, resulting in T cell- mediated antitumor immune responses. A phase I study examined the safety, tolerability, PK, and anti-tumor activity of CS-1001 in patients with advanced tumors. The compound was dosed every 3 weeks across five dose-escalating cohorts of 3 mg/kg, 10 mg/kg, 20 mg/kg, 40 mg/kg, and 1200 mg. It also exhibited antitumor activity with a disease control rate (DCR) of 58% (Shen, L., et al., Preliminary safety, pharmacokinetics (PK) and efficacy results from a phase I study of CS1001, an anti-programmed death ligand-1 (PD-L1) monoclonal antibody (mAb) in patients (pts) with advanced tumors. Annals of Oncology, Volume 29, Issue suppl_8, 2018, mdy288.038, 2018). [00080] SHR-1316, a fully humanized IgG4 monoclonal antibody, binds specifically to human PD-L1 and blocks the interaction of PD-L1 on cancer cells with its receptor PD-1 on T cells and mediating antitumor immune responses (Akinleye, A., Rasool, Z. Immune checkpoint inhibitors of PD-L1 as cancer therapeutics. J Hematol Oncol 12, 92 (2019). doi.org/10.1186/s13045-019-0779-5). [00081] CBT-502 is another novel, fully humanized IgG1 monoclonal antibody against PD-L1 developed by CBT Pharmaceuticals, Inc. In the cellular assay, the compound effectively blocked the interaction of PD-L1 with PD-1 and PD-L1 with CD80 at a concentration (IC ₅₀ ) of 47.97 pM and 1.09 nM, respectively, and strongly activated T cells by the production of IFN- gamma in a mixed lymphocyte reaction. In in vivo studies, CBT-502 showed potent antitumor activity in a dose-dependent manner in the MC-38/H-11 murine colon and A375 human melanoma animal models (Wei Z, et al. CBT-502 (TQB2450), a novel anti-PD-L1 antibody, demonstrates favorable activity in MC-38/H-11 murine colon and A375 human melanoma animal models. In: AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; October 26-30. Philadelphia, PA; 2017. p.2017). [00082] BGB-A333 is a fully humanized IgG1-variant monoclonal antibody that specifically target and binds to PD-L1, blocking interaction to its receptor, PD-1 on T cell, reversing T cell inactivation, and increases T cell expansion resulting in cytotoxic T cell- mediated antitumor immune response against PD-L1-expressing tumor cells. The compound also inhibits PD-L1-induced apoptosis of activated CD8 ⁺ T cells and increases T cell proliferation (Desai J, et al. Phase 1/2 study investigating safety, tolerability, pharmacokinetics, and preliminary antitumor activity of anti-PD-L1 monoclonal antibody bgb-A333 alone and in combination with anti-PD-1 monoclonal antibody tislelizumab in patients with advanced solid tumors. J Clin Oncol.2018;36(15_suppl):TPS3113). [00083] In certain embodiments, a checkpoint inhibitor comprises: an antibody or antigen binding fragments thereof, small molecule compounds, antisense oligonucleotides, siRNA reagents, microRNAs, gene-editing agents, antibodies, antibody fragments bearing epitope recognition sites, Fv fragments, single chain antibodies, antibody mimetics, peptoids, aptamers; enzymes, peptides organic or inorganic molecules, natural or synthetic compounds. [00084] In certain embodiments, the immune checkpoint targeted is the programmed death-1 (PD-1 or CD279), LAYN, AKAP5, FAM3C, KLRD1 (CD94), KLRC2 (CD159c), XB130 (AFAP1L2). In certain embodiments, the IL-7 receptor is targeted. In other embodiments, the immune checkpoint targeted is cytotoxic T-lymphocyte-associated antigen (CTLA-4). In additional embodiments, the immune checkpoint targeted is another member of the CD28 and CTLA4 Ig superfamily such as BTLA, LAG3, ICOS, PDL1 or KIR. In further additional embodiments, the immune checkpoint targeted is a member of the TNFR superfamily such as CD40, OX40, CD137, GITR, CD27 or TIM-3. [00085] Additional immune checkpoints include Src homology 2 domain-containing protein tyrosine phosphatase 1 (SHP-1) (Watson H A, et al., SHP-1: the next checkpoint target for cancer immunotherapy? Biochem Soc Trans.2016 Apr.15; 44(2):356-62). SHP-1 is a widely expressed inhibitory protein tyrosine phosphatase (PTP). In T-cells, it is a negative regulator of antigen-dependent activation and proliferation. It is a cytosolic protein, and therefore not amenable to antibody-mediated therapies, but its role in activation and proliferation makes it an attractive target for genetic manipulation in adoptive transfer strategies, such as chimeric antigen receptor (CAR) T cells. Immune checkpoints may also include T cell immunoreceptor with Ig and ITIM domains (TIGIT/Vstm3/WUCAM/VSIG9) and VISTA (Le Mercier I, et al., (2015) Beyond CTLA-4 and PD-1, the generation Z of negative checkpoint regulators. Front. Immunol. 6:418). [00086] In certain embodiments, gene editing of cells (such as by CRISPR/Cas), particularly cells intended for adoptive cell therapies, more particularly immunoresponsive cells such as T cells, may be performed to block an immune checkpoint, such as to knock-out or knock-down expression of an immune checkpoint protein or receptor in a cell. [00087] In certain embodiments, targets of gene editing may be at least one targeted locus involved in the expression of an immune checkpoint protein comprising programmed death-1 (PD-1 or CD279), LAYN, AKAP5, FAM3C, KLRD1 (CD94), KLRC2 (CD159c), XB130 (AFAP1L2). Other targets may include, but are not limited to CTLA4, PPP2CA, PPP2CB, PTPN6, PTPN22, PDCD1, ICOS (CD278), PDL1, KIR, LAG3, HAVCR2, BTLA, CD160, TIGIT, CD96, CRTAM, LAIR1, SIGLEC7, SIGLEC9, CD244 (2B4), TNFRSF10B, TNFRSF10A, CASP8, CASP10, CASP3, CASP6, CASP7, FADD, FAS, TGFβRII, TGFRβRI, SMAD2, SMAD3, SMAD4, SMAD10, SKI, SKIL, TGIF1, IL10RA, IL10RB, HMOX2, IL6R, IL6ST, EIF2AK4, CSK, PAG1, SIT1, FOXP3, PRDM1, BATF, VISTA, GUCY1A2, GUCY1A3, GUCY1B2, GUCY1B3, MT1, MT2, CD40, OX40, CD137, GITR, CD27, SHP-1, TIM-3, CEACAM-1, CEACAM-3, or CEACAM-5. [00088] Compositions [00089] In certain embodiments, a composition comprises a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to its ligands thereof, and a second agent comprising at least one of: a checkpoint antagonist, an IL-7 receptor agonist or soluble IL-7. [00090] In certain embodiments, a composition comprises a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and a second agent comprising an IL-7 receptor agonist, soluble IL-7 or the combination thereof. [00091] In certain embodiments, a composition comprises a therapeutically effective amount of (i) a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and (ii) a second agent comprising at least one of: a LAYN antagonist, an A-kinase anchoring protein 5 (AKAP5) antagonist, a FAM3 Metabolism Regulating Signaling Molecule C (FAM3C) antagonist, a KLRD1 (Killer Cell Lectin Like Receptor D1, CD94) antagonist, a KLRC2 (Killer Cell Lectin Like Receptor C2, CD159c) antagonist, an XB130 (AFAP1L2) antagonist or combinations thereof. [00092] In certain embodiments, a composition comprises a therapeutically effective amount of (i) a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and (ii) a second agent comprising two or more of: a LAYN antagonist, an A-kinase anchoring protein 5 (AKAP5) antagonist, a FAM3 Metabolism Regulating Signaling Molecule C (FAM3C) antagonist, a KLRD1 (Killer Cell Lectin Like Receptor D1, CD94) antagonist, a KLRC2 (Killer Cell Lectin Like Receptor C2, CD159c) antagonist, an XB130 (AFAP1L2) antagonist or combinations thereof. [00093] In certain embodiments, a composition comprises a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and a second agent comprising a LAYN antagonist. [00094] In certain embodiments, a composition comprises a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and a second agent comprising an A-kinase anchoring protein 5 (AKAP5) antagonist. [00095] In certain embodiments, a composition comprises a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and a second agent comprising a FAM3 Metabolism Regulating Signaling Molecule C (FAM3C) antagonist. [00096] In certain embodiments, a composition comprises a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and a second agent comprising a KLRD1 (Killer Cell Lectin Like Receptor D1, CD94) antagonist. [00097] In certain embodiments, a composition comprises a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and a second agent comprising a KLRC2 (Killer Cell Lectin Like Receptor C2, CD159c) antagonist. [00098] In certain embodiments, a composition comprises a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and a second agent comprising an XB130 (AFAP1L2) antagonist. [00099] In certain embodiments, a composition comprises a therapeutically effective amount of (i) a first agent which modulates programmed death 1 (PD-1) expression or function, or binding to ligands thereof, and (ii) a second agent comprising a modulator of at least one of: LAYN, A-kinase anchoring protein 5 (AKAP5), a FAM3 Metabolism Regulating Signaling Molecule C (FAM3C), KLRD1 (Killer Cell Lectin Like Receptor D1, CD94), KLRC2 (Killer Cell Lectin Like Receptor C2, CD159c), XB130 (AFAP1L2) or combinations thereof. [000100] In certain embodiments, a composition comprises a therapeutically effective amount of (i) a first agent which modulates programmed death 1 (PD-1) expression or function, or binding to ligands thereof, and (ii) a second agent comprising a modulator of two or more of: LAYN, A-kinase anchoring protein 5 (AKAP5), a FAM3 Metabolism Regulating Signaling Molecule C (FAM3C), KLRD1 (Killer Cell Lectin Like Receptor D1, CD94), KLRC2 (Killer Cell Lectin Like Receptor C2, CD159c), XB130 (AFAP1L2) or combinations thereof. [000101] As discussed in embodiments, in certain embodiments, a method of treating cancer comprises administering to a subject a composition comprising a therapeutically effective amount of: a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof, and a second agent comprising at least one of: a checkpoint antagonist, an IL-7 receptor agonist or soluble IL-7. In certain embodiments, the composition comprises a therapeutically effective amount of (i) the first agent and (ii) a second agent comprising an IL-7 receptor agonist, soluble IL-7 or the combination thereof. In embodiments, suitably, the first agent is administered in conjunction with or in combination with the second agent. For example, a first agent which inhibits programmed death 1 (PD-1) expression or function, or antagonizes binding to ligands thereof may be administered to a patient in conjection with or in combination with a second agent comprising at least one of: a checkpoint antagonist, an IL-7 receptor agonist or soluble IL-7. As used herein, the term “in combination” in the context of the administration of a therapy to a subject refers to the use of more than one therapy for therapeutic benefit. The term “in combination” in the context of the administration can also refer to the prophylactic use of a therapy to a subject when used with at least one additional therapy. The use of the term “in combination” does not restrict the order in which the therapies (e.g., a first agent and second agent) are administered to a subject. A first agent (e.g. a first agent which inhibits programmed death 1 (PD- 1) expression or function, or antagonizes binding to ligands thereof) can be administered prior to (e.g., 1 minute, 5 minutes, 15 minutes, 30 minutes, 45 minutes, 1 hour, 2 hours, 4 hours, 6 hours, 12 hours, 24 hours, 48 hours, 72 hours, 96 hours or up to about one 1 week before), concomitantly with, or subsequent to (e.g., 1 minute, 5 minutes, 15 minutes, 30 minutes, 45 minutes, 1 hour, 2 hours, 4 hours, 6 hours, 12 hours, 24 hours, 48 hours, 72 hours, 96 hours or up to about one 1 week after) the administration of a second agent (e.g. comprising at least one of: a checkpoint antagonist, an IL-7 receptor agonist or soluble IL-7) to a subject e.g. which had, has, or is susceptible to cancer, including a subject that has been diagnosed with a solid tumor. In embodiments, the first agent and second agent suitably are administered to a subject in a sequence and within a time interval such that the first agent and second agent can act together. In a particular embodiment, a first agent and a second agent are administered to a subject in a sequence and within a time interval such that they provide an increased benefit than if they were administered otherwise. Any additional therapy can be administered in any order with the other additional therapy. [000102] Methods of Treatment [000103] In certain embodiments, the present disclosure provides for modulating T cells responses in the treatment of cancer by modulating expression, activity or function of checkpoint molecules. As used herein, “modulating”, “to modulate”, “modifying” or “to modify” generally means either reducing or inhibiting the expression or activity of, or alternatively increasing the expression or activity of a target (e.g., PD-1). In particular, “modulating” or “to modulate” can mean either reducing or inhibiting the activity of, or alternatively increasing a (relevant or intended) biological activity of, a target or antigen as measured using a suitable in vitro, cellular or in vivo assay (which will usually depend on the target involved), by at least 5%, at least 10%, at least 25%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or more, compared to activity of the target in the same assay under the same conditions but without the presence of an agent. An “increase” or “decrease” refers to a statistically significant increase or decrease respectively. For the avoidance of doubt, an increase or decrease will be at least 10% relative to a reference, such as at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%, at least 97%, at least 98%, or more, up to and including at least 100% or more, in the case of an increase, for example, at least 2-fold, at least 3-fold, at least 4-fold, at least 5-fold, at least 6-fold, at least 7-fold, at least 8-fold, at least 9-fold, at least 10-fold, at least 50-fold, at least 100-fold, or more. “Modulating” can also involve effecting a change (which can either be an increase or a decrease) in affinity, avidity, specificity and/or selectivity of a target or antigen. “Modulating” can also mean effecting a change with respect to one or more biological or physiological mechanisms, effects, responses, functions, pathways or activities in which the target or antigen (or in which its substrate(s), ligand(s) or pathway(s) are involved, such as its signaling pathway or metabolic pathway and their associated biological or physiological effects) is involved. Again, as will be clear to the skilled person, such an action as an agonist or an antagonist can be determined in any suitable manner and/or using any suitable assay known or described herein (e.g., in vitro or cellular assay), depending on the target or antigen involved. [000104] Modulating can, for example, also involve allosteric modulation of the target and/or reducing or inhibiting the binding of the target to one of its substrates or ligands and/or competing with a natural ligand, substrate for binding to the target. Modulating can also involve activating the target or the mechanism or pathway in which it is involved. Modulating can, for example, also involve effecting a change in respect of the folding or confirmation of the target, or in respect of the ability of the target to fold, to change its conformation (for example, upon binding of a ligand), to associate with other (sub)units, or to disassociate. Modulating can, for example, also involve effecting a change in the ability of the target to signal, phosphorylate, dephosphorylate, and the like. [000105] Accordingly, in certain embodiments, a method of treating cancer comprises administering to a subject a composition comprising a therapeutically effective amount of: an agent which modulates expression, function or receptor-ligand binding of at least two or more of: Programmed death 1 (PD-1), LAYN, AKAP5, FAM3C, KLRD1 (CD94), KLRC2 (CD159c), XB130 (AFAP1L2), IL-7 receptor or IL-7. [000106] In certain embodiments, at least one of the agents is a modulator of PD-1 expression, function or receptor-ligand binding. In certain embodiments, at least one of the agents is a modulator of expression, function or receptor-ligand binding of: LAYN, AKAP5, FAM3C, KLRD1 (CD94), KLRC2 (CD159c), XB130 (AFAP1L2) or combinations thereof. In certain embodiments, the agent inhibits expression, function or receptor-ligand binding of at least two or more of: programmed death 1 (PD-1), LAYN, AKAP5, FAM3C, KLRD1 (CD94), KLRC2 (CD159c), XB130 (AFAP1L2) or the combinations thereof. [000107] In certain embodiments, the method of treating further comprises administering to the subject an immunotherapeutic agent, a chemotherapeutic agent or the combination thereof. In certain embodiments, the immunotherapeutic agent comprises a tumor vaccine, adoptive cellular therapy or the combination thereof. In certain embodiments, the tumor vaccine comprises whole tumor cell vaccines, peptides, recombinant tumor associated antigen vaccines, nucleic acids or combinations thereof. In certain embodiments, the adoptive cells comprise: T cells, natural killer cells, TILs, LAK cells or combinations thereof. In certain embodiments, the agent which modulates expression, function or receptor-ligand binding of programmed death 1 (PD-1), LAYN, AKAP5, FAM3C, KLRD1 (CD94), KLRC2 (CD159c), XB130 (AFAP1L2), IL-7 receptor or IL-7, comprises: an antibody or antigen binding fragments thereof, small molecule compounds, antisense oligonucleotides, siRNA reagents, microRNAs, gene-editing agents, Fv fragments, single chain antibodies, antibody-like protein scaffolds, antibody mimetics, peptoids, aptamers; enzymes, peptides organic or inorganic molecules, natural or synthetic compounds. [000108] Aptamers: In certain embodiments, the one or more agents is an aptamer. Nucleic acid aptamers are nucleic acid species that have been engineered through repeated rounds of in vitro selection or equivalently, SELEX (systematic evolution of ligands by exponential enrichment) to bind to various molecular targets such as small molecules, proteins, nucleic acids, cells, tissues and organisms. Nucleic acid aptamers have specific binding affinity to molecules through interactions other than classic Watson-Crick base pairing. Aptamers are useful in biotechnological and therapeutic applications as they offer molecular recognition properties similar to antibodies. In addition to their discriminate recognition, aptamers offer advantages over antibodies as they can be engineered completely in a test tube, are readily produced by chemical synthesis, possess desirable storage properties, and elicit little or no immunogenicity in therapeutic applications. In certain embodiments, RNA aptamers may be expressed from a DNA construct. In other embodiments, a nucleic acid aptamer may be linked to another polynucleotide sequence. The polynucleotide sequence may be a double stranded DNA polynucleotide sequence. The aptamer may be covalently linked to one strand of the polynucleotide sequence. The aptamer may be ligated to the polynucleotide sequence. The polynucleotide sequence may be configured, such that the polynucleotide sequence may be linked to a solid support or ligated to another polynucleotide sequence. [000109] Aptamers, like peptides generated by phage display or monoclonal antibodies (“mAbs”), are capable of specifically binding to selected targets and modulating the target's activity, e.g., through binding, aptamers may block their target's ability to function. A typical aptamer is 10-15 kDa in size (30-45 nucleotides), binds its target with sub-nanomolar affinity, and discriminates against closely related targets (e.g., aptamers will typically not bind other proteins from the same gene family). Structural studies have shown that aptamers are capable of using the same types of binding interactions (e.g., hydrogen bonding, electrostatic complementarity, hydrophobic contacts, steric exclusion) that drives affinity and specificity in antibody-antigen complexes. [000110] Aptamers have a number of desirable characteristics for use in research and as therapeutics and diagnostics including high specificity and affinity, biological efficacy, and excellent pharmacokinetic properties. In addition, they offer specific competitive advantages over antibodies and other protein biologics. Aptamers are chemically synthesized and are readily scaled as needed to meet production demand for research, diagnostic or therapeutic applications. Aptamers are chemically robust. They are intrinsically adapted to regain activity following exposure to factors such as heat and denaturants and can be stored for extended periods (>1 yr) at room temperature as lyophilized powders. Not being bound by a theory, aptamers bound to a solid support or beads may be stored for extended periods. [000111] Oligonucleotides in their phosphodiester form may be quickly degraded by intracellular and extracellular enzymes such as endonucleases and exonucleases. Aptamers can include modified nucleotides conferring improved characteristics on the ligand, such as improved in vivo stability or improved delivery characteristics. Examples of such modifications include chemical substitutions at the ribose and/or phosphate and/or base positions. SELEX identified nucleic acid ligands containing modified nucleotides are described, e.g., in U.S. Pat. No.5,660,985, which describes oligonucleotides containing nucleotide derivatives chemically modified at the 2' position of ribose, 5 position of pyrimidines, and 8 position of purines, U.S. Pat. No.5,756,703 which describes oligonucleotides containing various 2'-modified pyrimidines, and U.S. Pat. No.5,580,737 which describes highly specific nucleic acid ligands containing one or more nucleotides modified with 2'-amino (2'-NH2), 2'-fluoro (2'-F), and/or 2'-O-methyl (2'- OMe) substituents. Modifications of aptamers may also include, modifications at exocyclic amines, substitution of 4-thiouridine, substitution of 5-bromo or 5-iodo-uracil; backbone modifications, phosphorothioate or allyl phosphate modifications, methylations, and unusual base-pairing combinations such as the isobases isocytidine and isoguanosine. Modifications can also include 3' and 5' modifications such as capping. As used herein, the term phosphorothioate encompasses one or more non-bridging oxygen atoms in a phosphodiester bond replaced by one or more sulfur atoms. In further embodiments, the oligonucleotides comprise modified sugar groups, for example, one or more of the hydroxyl groups is replaced with halogen, aliphatic groups, or functionalized as ethers or amines. In one embodiment, the 2'-position of the furanose residue is substituted by any of an O-methyl, O-alkyl, O-allyl, S-alkyl, S-allyl, or halo group. Methods of synthesis of 2'-modified sugars are described, e.g., in Sproat, et al., Nucl. Acid Res. 19:733-738 (1991); Cotten, et al, Nucl. Acid Res.19:2629-2635 (1991); and Hobbs, et al, Biochemistry 12:5138-5145 (1973). Other modifications are known to one of ordinary skill in the art. In certain embodiments, aptamers include aptamers with improved off-rates as described in International Patent Publication No. WO 2009012418, “Method for generating aptamers with improved off-rates,” incorporated herein by reference in its entirety. In certain embodiments aptamers are chosen from a library of aptamers. Such libraries include, but are not limited to those described in Rohloff et al., “Nucleic Acid Ligands With Protein-like Side Chains: Modified Aptamers and Their Use as Diagnostic and Therapeutic Agents,” Molecular Therapy Nucleic Acids (2014) 3, e201. Aptamers are also commercially available (see, e.g., SomaLogic, Inc., Boulder, Colo.). In certain embodiments, the present disclosure may utilize any aptamer containing any modification as described herein. [000112] Small Molecules: In certain embodiments, the one or more agents is a small molecule. The term “small molecule” refers to compounds, preferably organic compounds, with a size comparable to those organic molecules generally used in pharmaceuticals. The term excludes biological macromolecules (e.g., proteins, peptides, nucleic acids, etc.). Preferred small organic molecules range in size up to about 5000 Da, e.g., up to about 4000, preferably up to 3000 Da, more preferably up to 2000 Da, even more preferably up to about 1000 Da, e.g., up to about 900, 800, 700, 600 or up to about 500 Da. In certain embodiments, the small molecule may act as an antagonist or agonist (e.g., blocking a receptor binding site or activating a receptor by binding to a ligand binding site). [000113] One type of small molecule applicable to the present disclosure is a degrader molecule (see, e.g., Ding, et al., Emerging New Concepts of Degrader Technologies, Trends Pharmacol Sci.2020 July; 41(7):464-474). The terms “degrader” and “degrader molecule” refer to all compounds capable of specifically targeting a protein for degradation (e.g., ATTEC, AUTAC, LYTAC, or PROTAC, reviewed in Ding, et al.2020). Proteolysis Targeting Chimera (PROTAC) technology is a rapidly emerging alternative therapeutic strategy with the potential to address many of the challenges currently faced in modern drug development programs. PROTAC technology employs small molecules that recruit target proteins for ubiquitination and removal by the proteasome (see, e.g., Zhou et al., Discovery of a Small-Molecule Degrader of Bromodomain and Extra-Terminal (BET) Proteins with Picomolar Cellular Potencies and Capable of Achieving Tumor Regression. J. Med. Chem.2018, 61, 462-481; Bondeson and Crews, Targeted Protein Degradation by Small Molecules, Annu Rev Pharmacol Toxicol.2017 Jan.6; 57: 107-123; and Lai et al., Modular PROTAC Design for the Degradation of Oncogenic BCR-ABL. Angew Chem Int Ed Engl.2016 Jan.11; 55(2): 807-810). In certain embodiments, LYTACs are particularly advantageous for cell surface proteins as described herein. [000114] Antibodies: In certain embodiments, the one or more agents is an antibody. Antibodies may act as agonists or antagonists of the recognized polypeptides. For example, the present disclosure includes antibodies which disrupt receptor/ligand interactions either partially or fully. The disclosure features both receptor-specific antibodies and ligand-specific antibodies. The disclosure also features receptor-specific antibodies which do not prevent ligand binding but prevent receptor activation. Receptor activation (i.e., signaling) may be determined by techniques described herein or otherwise known in the art. For example, receptor activation can be determined by detecting the phosphorylation (e.g., tyrosine or serine/threonine) of the receptor or of one of its down-stream substrates by immunoprecipitation followed by western blot analysis. In specific embodiments, antibodies are provided that inhibit ligand activity or receptor activity by at least 95%, at least 90%, at least 85%, at least 80%, at least 75%, at least 70%, at least 60%, or at least 50% of the activity in absence of the antibody. [000115] The disclosure also features receptor-specific antibodies which both prevent ligand binding and receptor activation as well as antibodies that recognize the receptor-ligand complex. Likewise, encompassed by the disclosure are neutralizing antibodies which bind the ligand and prevent binding of the ligand to the receptor, as well as antibodies which bind the ligand, thereby preventing receptor activation, but do not prevent the ligand from binding the receptor. Further included in the disclosure are antibodies which activate the receptor. These antibodies may act as receptor agonists, i.e., potentiate or activate either all or a subset of the biological activities of the ligand-mediated receptor activation, for example, by inducing dimerization of the receptor. The antibodies may be specified as agonists, antagonists or inverse agonists for biological activities comprising the specific biological activities of the peptides disclosed herein. The antibody agonists and antagonists can be made using methods known in the art. See, e.g., PCT publication WO 96/40281; U.S. Pat. No.5,811,097; Deng et al., Blood 92(6):1981-1988 (1998); Chen et al., Cancer Res.58(16):3668-3678 (1998); Harrop et al., J. Immunol.161(4):1786-1794 (1998); Zhu et al., Cancer Res.58(15):3209-3214 (1998); Yoon et al., J. Immunol.160(7):3170-3179 (1998); Prat et al., J. Cell. Sci. III (Pt2):237-247 (1998); Pitard et al., J. Immunol. Methods 205(2):177-190 (1997); Liautard et al., Cytokine 9(4):233-241 (1997); Carlson et al., J. Biol. Chem.272(17):11295-11301 (1997); Taryman et al., Neuron 14(4):755-762 (1995); Muller et al., Structure 6(9):1153-1167 (1998); Bartunek et al., Cytokine 8(1):14-20 (1996). [000116] The antibodies as defined for the present disclosure include derivatives that are modified, i.e., by the covalent attachment of any type of molecule to the antibody such that covalent attachment does not prevent the antibody from generating an anti-idiotypic response. For example, but not by way of limitation, the antibody derivatives include antibodies that have been modified, e.g., by glycosylation, acetylation, pegylation, phosphylation, amidation, derivatization by known protecting/blocking groups, proteolytic cleavage, linkage to a cellular ligand or other protein, etc. Any of numerous chemical modifications may be carried out by known techniques, including, but not limited to specific chemical cleavage, acetylation, formylation, metabolic synthesis of tunicamycin, etc. Additionally, the derivative may contain one or more non-classical amino acids. [000117] Simple binding assays can be used to screen for or detect agents that bind to a target protein, or disrupt the interaction between proteins (e.g., a receptor and a ligand). Because certain targets of the present disclosure are transmembrane proteins, assays that use the soluble forms of these proteins rather than full-length protein can be used, in some embodiments. Soluble forms include, for example, those lacking the transmembrane domain and/or those comprising the IgV domain or fragments thereof which retain their ability to bind their cognate binding partners. Further, agents that inhibit or enhance protein interactions for use in the compositions and methods described herein, can include recombinant peptido-mimetics. [000118] Detection methods useful in screening assays include antibody-based methods, detection of a reporter moiety, detection of cytokines as described herein, and detection of a gene signature as described herein. [000119] Another variation of assays to determine binding of a receptor protein to a ligand protein is through the use of affinity biosensor methods. Such methods may be based on the piezoelectric effect, electrochemistry, or optical methods, such as ellipsometry, optical wave guidance, and surface plasmon resonance (SPR). [000120] Antibody-like protein scaffolds: In certain embodiments, the agent is an antibody- like protein scaffold. The term “antibody-like protein scaffolds” or “engineered protein scaffolds” broadly encompasses proteinaceous non-immunoglobulin specific-binding agents, typically obtained by combinatorial engineering (such as site-directed random mutagenesis in combination with phage display or other molecular selection techniques). Usually, such scaffolds are derived from robust and small soluble monomeric proteins (such as Kunitz inhibitors or lipocalins) or from a stably folded extra-membrane domain of a cell surface receptor (such as protein A, fibronectin or the ankyrin repeat). [000121] Such scaffolds have been extensively reviewed in Binz et al. (Engineering novel binding proteins from nonimmunoglobulin domains. Nat Biotechnol 2005, 23:1257-1268), Gebauer and Skerra (Engineered protein scaffolds as next-generation antibody therapeutics. Curr Opin Chem Biol.2009, 13:245-55), Gill and Damle (Biopharmaceutical drug discovery using novel protein scaffolds. Curr Opin Biotechnol 2006, 17:653-658), Skerra (Engineered protein scaffolds for molecular recognition. J Mol Recognit 2000, 13:167-187), and Skerra (Alternative non-antibody scaffolds for molecular recognition. Curr Opin Biotechnol 2007, 18:295-304), and include without limitation affibodies, based on the Z-domain of staphylococcal protein A, a three-helix bundle of 58 residues providing an interface on two of its alpha-helices (Nygren, Alternative binding proteins: Affibody binding proteins developed from a small three-helix bundle scaffold. FEBS J 2008, 275:2668-2676); engineered Kunitz domains based on a small (ca.58 residues) and robust, disulphide-crosslinked serine protease inhibitor, typically of human origin (e.g. LACI-D1), which can be engineered for different protease specificities (Nixon and Wood, Engineered protein inhibitors of proteases. Curr Opin Drug Discov Dev 2006, 9:261- 268); monobodies or adnectins based on the 10th extracellular domain of human fibronectin III (10Fn3), which adopts an Ig-like beta-sandwich fold (94 residues) with 2-3 exposed loops, but lacks the central disulphide bridge (Koide and Koide, Monobodies: antibody mimics based on the scaffold of the fibronectin type III domain. Methods Mol Biol 2007, 352:95-109); anticalins derived from the lipocalins, a diverse family of eight-stranded beta-barrel proteins (ca.180 residues) that naturally form binding sites for small ligands by means of four structurally variable loops at the open end, which are abundant in humans, insects, and many other organisms (Skerra, Alternative binding proteins: Anticalins--harnessing the structural plasticity of the lipocalin ligand pocket to engineer novel binding activities. FEBS J 2008, 275:2677-2683); DARPins, designed ankyrin repeat domains (166 residues), which provide a rigid interface arising from typically three repeated beta-turns (Stumpp et al., DARPins: a new generation of protein therapeutics. Drug Discov Today 2008, 13:695-701); avimers (multimerized LDLR-A module) (Silverman et al., Multivalent avimer proteins evolved by exon shuffling of a family of human receptor domains. Nat Biotechnol 2005, 23:1556-1561); and cysteine-rich knottin peptides (Kolmar, Alternative binding proteins: biological activity and therapeutic potential of cystine- knot miniproteins. FEBS J 2008, 275:2684-2690). [000122] RNAi: In some embodiments, the genetic modulating agents may be interfering RNAs. In certain embodiments, diseases caused by a dominant mutation in a gene is targeted by silencing the mutated gene using RNAi. In some cases, the nucleotide sequence may comprise coding sequence for one or more interfering RNAs. In certain examples, the nucleotide sequence may be interfering RNA (RNAi). As used herein, the term “RNAi” refers to any type of interfering RNA, including but not limited to, siRNAi, shRNAi, endogenous microRNA and artificial microRNA. For instance, it includes sequences previously identified as siRNA, regardless of the mechanism of down-stream processing of the RNA (i.e. although siRNAs are believed to have a specific method of in vivo processing resulting in the cleavage of mRNA, such sequences can be incorporated into the vectors in the context of the flanking sequences described herein). The term “RNAi” can include both gene silencing RNAi molecules, and also RNAi effector molecules which activate the expression of a gene. [000123] In certain embodiments, a modulating agent may comprise silencing one or more endogenous genes. As used herein, “gene silencing” or “gene silenced” in reference to an activity of an RNAi molecule, for example a siRNA or miRNA refers to a decrease in the mRNA level in a cell for a target gene by at least about 5%, about 10%, about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, about 80%, about 90%, about 95%, about 99%, about 100% of the mRNA level found in the cell without the presence of the miRNA or RNA interference molecule. In one preferred embodiment, the mRNA levels are decreased by at least about 70%, about 80%, about 90%, about 95%, about 99%, about 100%. [000124] As used herein, a “siRNA” refers to a nucleic acid that forms a double stranded RNA, which double stranded RNA has the ability to reduce or inhibit expression of a gene or target gene when the siRNA is present or expressed in the same cell as the target gene. The double stranded RNA siRNA can be formed by the complementary strands. In one embodiment, a siRNA refers to a nucleic acid that can form a double stranded siRNA. The sequence of the siRNA can correspond to the full-length target gene, or a subsequence thereof. Typically, the siRNA is at least about 15-50 nucleotides in length (e.g., each complementary sequence of the double stranded siRNA is about 15-50 nucleotides in length, and the double stranded siRNA is about 15-50 base pairs in length, preferably about 19-30 base nucleotides, preferably about 20-25 nucleotides in length, e.g., 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 nucleotides in length). [000125] As used herein “shRNA” or “small hairpin RNA” (also called stem loop) is a type of siRNA. In one embodiment, these shRNAs are composed of a short, e.g. about 19 to about 25 nucleotide, antisense strand, followed by a nucleotide loop of about 5 to about 9 nucleotides, and the analogous sense strand. Alternatively, the sense strand can precede the nucleotide loop structure and the antisense strand can follow. [000126] The terms “microRNA” or “miRNA”, used interchangeably herein, are endogenous RNAs, some of which are known to regulate the expression of protein-coding genes at the posttranscriptional level. Endogenous microRNAs are small RNAs naturally present in the genome that are capable of modulating the productive utilization of mRNA. The term artificial microRNA includes any type of RNA sequence, other than endogenous microRNA, which is capable of modulating the productive utilization of mRNA. MicroRNA sequences have been described in publications such as Lim, et al., Genes & Development, 17, p.991-1008 (2003), Lim et al Science 299, 1540 (2003), Lee and Ambros Science, 294, 862 (2001), Lau et al., Science 294, 858-861 (2001), Lagos-Quintana et al, Current Biology, 12, 735-739 (2002), Lagos Quintana et al, Science 294, 853-857 (2001), and Lagos-Quintana et al, RNA, 9, 175-179 (2003), which are incorporated by reference. Multiple microRNAs can also be incorporated into a precursor molecule. Furthermore, miRNA-like stem-loops can be expressed in cells as a vehicle to deliver artificial miRNAs and short interfering RNAs (siRNAs) for the purpose of modulating the expression of endogenous genes through the miRNA and or RNAi pathways. [000127] As used herein, “double stranded RNA” or “dsRNA” refers to RNA molecules that are comprised of two strands. Double-stranded molecules include those comprised of a single RNA molecule that doubles back on itself to form a two-stranded structure. For example, the stem loop structure of the progenitor molecules from which the single-stranded miRNA is derived, called the pre-miRNA (Bartel et al.2004. Cell 116:281-297), comprises a dsRNA molecule. [000128] Adoptive Cell Transfer: In certain embodiments, the immunotherapeutic agent comprises adoptive cellular therapy. Immune effector cells are used for adoptive cell transfer (ACT). As used herein, "ACT", "adoptive cell therapy" and "adoptive cell transfer" may be used interchangeably. In certain embodiments, the immune effector cells are modified and expanded. In certain embodiments, cells with the desired phenotype are selected for and expanded. In certain embodiments, the immune effector cells are formulated into a pharmaceutical composition. The modified cells may be resistant to exhaustion induced by a tumor or tumor microenvironment and have enhanced anti-tumor activity. In other words, a tumor may target immune cells or the tumor microenvironment to induce a dysfunctional immune state. In certain embodiments, modulating one or more identified therapeutic targets in an immune cell shifts the immune cell to have increased effector function. In certain embodiments, the immune cells prevent an immune suppressive tumor microenvironment. Such immune cells may be used to increase the effectiveness of adoptive cell transfer. In certain embodiments, immune cells are modulated using a genetic modifying agent, antibody or small molecule, described further herein. [000129] Adoptive Cell Therapy (ACT) can refer to the transfer of cells to a patient with the goal of transferring the functionality and characteristics into the new host by engraftment of the cells (see, e.g., Mettananda et al., Editing an α-globin enhancer in primary human hematopoietic stem cells as a treatment for β-thalassemia, Nat Commun.2017 Sep.4; 8(1):424). As used herein, the term "engraft" or "engraftment" refers to the process of cell incorporation into a tissue of interest in vivo through contact with existing cells of the tissue. Adoptive Cell Therapy (ACT) can refer to the transfer of cells, most commonly immune-derived cells, back into the same patient or into a new recipient host with the goal of transferring the immunologic functionality and characteristics into the new host. If possible, use of autologous cells helps the recipient by minimizing GVHD issues. The adoptive transfer of autologous tumor infiltrating lymphocytes (TIL) (Zacharakis et al., (2018) Nat Med.2018 June; 24(6):724-730; Besser et al., (2010) Clin. Cancer Res 16 (9) 2646-55; Dudley et al., (2002) Science 298 (5594): 850-4; and Dudley et al., (2005) Journal of Clinical Oncology 23 (10): 2346-57.) or genetically re-directed peripheral blood mononuclear cells (Johnson et al., (2009) Blood 114 (3): 535-46; and Morgan et al., (2006) Science 314(5796) 126-9) has been used to successfully treat patients with advanced solid tumors, including melanoma, metastatic breast cancer and colorectal carcinoma, as well as patients with CD19-expressing hematologic malignancies (Kalos et al., (2011) Science Translational Medicine 3 (95): 95ra73). In certain embodiments, allogenic cells immune cells are transferred (see, e.g., Ren et al., (2017) Clin Cancer Res 23 (9) 2255-2266). As described further herein, allogenic cells can be edited to reduce alloreactivity and prevent graft-versus-host disease. Thus, use of allogenic cells allows for cells to be obtained from healthy donors and prepared for use in patients as opposed to preparing autologous cells from a patient after diagnosis. [000130] Aspects of the disclosure involve the adoptive transfer of immune system cells, such as T cells, specific for selected antigens, such as tumor associated antigens or tumor specific neoantigens (see, e.g., Maus et al., 2014, Adoptive Immunotherapy for Cancer or Viruses, Annual Review of Immunology, Vol.32: 189-225; Rosenberg and Restifo, 2015, Adoptive cell transfer as personalized immunotherapy for human cancer, Science Vol.348 no. 6230 pp.62-68; Restifo et al., 2015, Adoptive immunotherapy for cancer: harnessing the T cell response. Nat. Rev. Immunol.12(4): 269-281; and Jenson and Riddell, 2014, Design and implementation of adoptive therapy with chimeric antigen receptor-modified T cells. Immunol Rev.257(1): 127-144; and Rajasagi et al., 2014, Systematic identification of personal tumor- specific neoantigens in chronic lymphocytic leukemia. Blood.2014 Jul.17; 124(3):453-62). [000131] Immunotherapeutics, generally, rely on the use of immune effector cells and molecules to target and destroy cancer cells. The immune effector may be, for example, an antibody specific for some marker on the surface of a tumor cell. The antibody alone may serve as an effector of therapy or it may recruit other cells to actually effect cell killing. The antibody also may be conjugated to a drug or toxin (chemotherapeutic, radionuclide, ricin A chain, cholera toxin, pertussis toxin, etc.) and serve merely as a targeting agent. Alternatively, the effector may be a lymphocyte carrying a surface molecule that interacts, either directly or indirectly, with a tumor cell target. Various effector cells include cytotoxic T cells and NK cells as well as genetically engineered variants of these cell types modified to express chimeric antigen receptors. Mda-7 gene transfer to tumor cells causes tumor cell death and apoptosis. The apoptotic tumor cells are scavenged by reticuloendothelial cells including dendritic cells and macrophages and presented to the immune system to generate anti-tumor immunity. [000132] The immunotherapy may comprise suppression of T regulatory cells (Tregs), myeloid derived suppressor cells (MDSCs) and cancer associated fibroblasts (CAFs). In some embodiments, the immunotherapy is a tumor vaccine (e.g., whole tumor cell vaccines, peptides, and recombinant tumor associated antigen vaccines), or adoptive cellular therapies (ACT) (e.g., T cells, natural killer cells, TILs, and LAK cells). The T cells may be engineered with chimeric antigen receptors (CARs) or T cell receptors (TCRs) to specific tumor antigens. As used herein, a chimeric antigen receptor (or CAR) may refer to any engineered receptor specific for an antigen of interest that, when expressed in a T cell, confers the specificity of the CAR onto the T cell. Once created using standard molecular techniques, a T cell expressing a chimeric antigen receptor may be introduced into a patient, as with a technique such as adoptive cell transfer. In some aspects, the T cells are activated CD4 and/or CD8 T cells in the individual which are characterized by γ-IFN- producing CD4 and/or CD8 T cells and/or enhanced cytolytic activity relative to prior to the administration of the combination. The CD4 and/or CD8 T cells may exhibit increased release of cytokines selected from the group consisting of IFN-γ, TNF-α and interleukins. The CD4 and/or CD8 T cells can be effector memory T cells. In certain embodiments, the CD4 and/or CD8 effector memory T cells are characterized by having the expression of CD44 ^high CD62L ^low . [000133] In certain embodiments, an antigen to be targeted in adoptive cell therapy (such as particularly CAR or TCR T-cell therapy) of a disease (such as particularly of tumor or cancer) is a tumor-specific antigen (TSA). [000134] In certain embodiments, an antigen to be targeted in adoptive cell therapy (such as particularly CAR or TCR T-cell therapy) of a disease (such as particularly of tumor or cancer) is a neoantigen. [000135] In certain embodiments, an antigen to be targeted in adoptive cell therapy (such as particularly CAR or TCR T-cell therapy) of a disease (such as particularly of tumor or cancer) is a tumor-associated antigen (TAA). [000136] In certain embodiments, an antigen to be targeted in adoptive cell therapy (such as particularly CAR or TCR T-cell therapy) of a disease (such as particularly of tumor or cancer) is a universal tumor antigen. In certain preferred embodiments, the universal tumor antigen is selected from the group consisting of a human telomerase reverse transcriptase (hTERT), survivin, mouse double minute 2 homolog (MDM2), cytochrome P4501B 1 (CYP1B), HER2/neu, Wilms' tumor gene 1 (WT1), livin, alphafetoprotein (AFP), carcinoembryonic antigen (CEA), mucin 16 (MUC16), MUC1, prostate-specific membrane antigen (PSMA), p53, cyclin (Dl), and any combinations thereof. [000137] Various strategies may for example be employed to genetically modify T cells by altering the specificity of the T cell receptor (TCR) for example by introducing new TCRα and β chains with selected peptide specificity (see U.S. Pat. No.8,697,854; PCT Patent Publications: WO2003020763, WO2004033685, WO2004044004, WO2005114215, WO2006000830, WO2008038002, WO2008039818, WO2004074322, WO2005113595, WO2006125962, WO2013166321, WO2013039889, WO2014018863, WO2014083173; U.S. Pat. No.8,088,379). [000138] As an alternative to, or addition to, TCR modifications, chimeric antigen receptors (CARs) may be used in order to generate immunoresponsive cells, such as T cells, specific for selected targets, such as malignant cells, with a wide variety of receptor chimera constructs having been described (see U.S. Pat. Nos.5,843,728; 5,851,828; 5,912,170; 6,004,811; 6,284,240; 6,392,013; 6,410,014; 6,753,162; 8,211,422; and, PCT Publication WO9215322). [000139] In general, CARs are comprised of an extracellular domain, a transmembrane domain, and an intracellular domain, wherein the extracellular domain comprises an antigen- binding domain that is specific for a predetermined target. While the antigen-binding domain of a CAR is often an antibody or antibody fragment (e.g., a single chain variable fragment, scFv), the binding domain is not particularly limited so long as it results in specific recognition of a target. For example, in some embodiments, the antigen-binding domain may comprise a receptor, such that the CAR is capable of binding to the ligand of the receptor. Alternatively, the antigen- binding domain may comprise a ligand, such that the CAR is capable of binding the endogenous receptor of that ligand. [000140] The antigen-binding domain of a CAR is generally separated from the transmembrane domain by a hinge or spacer. The spacer is also not particularly limited, and it is designed to provide the CAR with flexibility. For example, a spacer domain may comprise a portion of a human Fc domain, including a portion of the CH3 domain, or the hinge region of any immunoglobulin, such as IgA, IgD, IgE, IgG, or IgM, or variants thereof. Furthermore, the hinge region may be modified so as to prevent off-target binding by FcRs or other potential interfering objects. For example, the hinge may comprise an IgG4 Fc domain with or without a S228P, L235E, and/or N297Q mutation (according to Kabat numbering) in order to decrease binding to FcRs. Additional spacers/hinges include, but are not limited to, CD4, CD8, and CD28 hinge regions. [000141] The transmembrane domain of a CAR may be derived either from a natural or from a synthetic source. Where the source is natural, the domain may be derived from any membrane bound or transmembrane protein. Transmembrane regions of particular use in this disclosure may be derived from CD8, CD28, CD3, CD45, CD4, CD5, CD5, CD9, CD 16, CD22, CD33, CD37, CD64, CD80, CD86, CD 134, CD137, CD 154, TCR. Alternatively, the transmembrane domain may be synthetic, in which case it will comprise predominantly hydrophobic residues such as leucine and valine. Preferably a triplet of phenylalanine, tryptophan and valine will be found at each end of a synthetic transmembrane domain. Optionally, a short oligo- or polypeptide linker, preferably between 2 and 10 amino acids in length may form the linkage between the transmembrane domain and the cytoplasmic signaling domain of the CAR. A glycine-serine doublet provides a particularly suitable linker. [000142] Chemotherapy: Cancer therapies in general also include a variety of combination therapies with both chemical and radiation based treatments. Combination chemotherapies include, for example, cisplatin (CDDP), carboplatin, procarbazine, mechlorethamine, cyclophosphamide, camptothecin, ifosfamide, melphalan, chlorambucil, busulfan, nitrosurea, dactinomycin, daunorubicin, doxorubicin, bleomycin, plicomycin, mitomycin, etoposide (VP16), tamoxifen, raloxifene, estrogen receptor binding agents, taxol, gemcitabien, navelbine, famesyl- protein transferase inhibitors, transplatinum, 5-fluorouracil, vincristine, vinblastine and methotrexate, Temazolomide (an aqueous form of DTIC), or any analog or derivative variant of the foregoing. The combination of chemotherapy with biological therapy is known as biochemotherapy. The chemotherapy may also be administered at low, continuous doses which is known as metronomic chemotherapy. [000143] Yet further combination chemotherapies include, for example, alkylating agents such as thiotepa and cyclosphosphamide; alkyl sulfonates such as busulfan, improsulfan and piposulfan; aziridines such as benzodopa, carboquone, meturedopa, and uredopa; ethylenimines and methylamelamines including altretamine, triethylenemelamine, trietylenephosphoramide, triethiylenethiophosphoramide and trimethylolomelamine; acetogenins (especially bullatacin and bullatacinone); a camptothecin (including the synthetic analogue topotecan); bryostatin; callystatin; CC-1065 (including its adozelesin, carzelesin and bizelesin synthetic analogues); cryptophycins (particularly cryptophycin 1 and cryptophycin 8); dolastatin; duocarmycin (including the synthetic analogues, KW-2189 and CB1-TM1); eleutherobin; pancratistatin; a sarcodictyin; spongistatin; nitrogen mustards such as chlorambucil, chlornaphazine, cholophosphamide, estramustine, ifosfamide, mechlorethamine, mechlorethamine oxide hydrochloride, melphalan, novembichin, phenesterine, prednimustine, trofosfamide, uracil mustard; nitrosureas such as carmustine, chlorozotocin, fotemustine, lomustine, nimustine, and ranimnustine; antibiotics such as the enediyne antibiotics (e.g., calicheamicin, especially calicheamicin gammall and calicheamicin omegall; dynemicin, including dynemicin A; bisphosphonates, such as clodronate; an esperamicin; as well as neocarzinostatin chromophore and related chromoprotein enediyne antiobiotic chromophores, aclacinomysins, actinomycin, authrarnycin, azaserine, bleomycins, cactinomycin, carabicin, carminomycin, carzinophilin, chromomycinis, dactinomycin, daunorubicin, detorubicin, 6-diazo-5-oxo-L-norleucine, doxorubicin (including morpholino-doxorubicin, cyanomorpholino-doxorubicin, 2-pyrrolino- doxorubicin and deoxydoxorubicin), epirubicin, esorubicin, idarubicin, marcellomycin, mitomycins such as mitomycin C, mycophenolic acid, nogalarnycin, olivomycins, peplomycin, potfiromycin, puromycin, quelamycin, rodorubicin, streptonigrin, streptozocin, tubercidin, ubenimex, zinostatin, zorubicin; anti-metabolites such as methotrexate and 5-fluorouracil (5- FU); folic acid analogues such as denopterin, pteropterin, trimetrexate; purine analogs such as fludarabine, 6-mercaptopurine, thiamiprine, thioguanine; pyrimidine analogs such as ancitabine, azacitidine, 6-azauridine, carmofur, cytarabine, dideoxyuridine, doxifluridine, enocitabine, floxuridine; androgens such as calusterone, dromostanolone propionate, epitiostanol, mepitiostane, testolactone; anti-adrenals such as mitotane, trilostane; folic acid replenisher such as frolinic acid; aceglatone; aldophosphamide glycoside; aminolevulinic acid; eniluracil; amsacrine; bestrabucil; bisantrene; edatraxate; defofamine; demecolcine; diaziquone; elformithine; elliptinium acetate; an epothilone; etoglucid; gallium nitrate; hydroxyurea; lentinan; lonidainine; maytansinoids such as maytansine and ansamitocins; mitoguazone; mitoxantrone; mopidanmol; nitraerine; pentostatin; phenamet; pirarubicin; losoxantrone; podophyllinic acid; 2-ethylhydrazide; procarbazine; PSK polysaccharide complex; razoxane; rhizoxin; sizofiran; spirogermanium; tenuazonic acid; triaziquone; 2,2',2''-trichlorotriethylamine; trichothecenes (especially T-2 toxin, verracurin A, roridin A and anguidine); urethan; vindesine; dacarbazine; mannomustine; mitobronitol; mitolactol; pipobroman; gacytosine; arabinoside (“Ara-C”); cyclophosphamide; taxoids, e.g., paclitaxel and docetaxel gemcitabine; 6- thioguanine; mercaptopurine; platinum coordination complexes such as cisplatin, oxaliplatin and carboplatin; vinblastine; platinum; etoposide (VP-16); ifosfamide; mitoxantrone; vincristine; vinorelbine; novantrone; teniposide; edatrexate; daunomycin; aminopterin; xeloda; ibandronate; irinotecan (e.g., CPT-11); topoisomerase inhibitor RFS 2000; difluorometlhylornithine (DMFO); retinoids such as retinoic acid; capecitabine; carboplatin, procarbazine, plicomycin, gemcitabien, navelbine, farnesyl-protein transferase inhibitors, transplatinum; and pharmaceutically acceptable salts, acids or derivatives of any of the above. In certain embodiments, the compositions provided herein may be used in combination with histone deacetylase inhibitors. In certain embodiments, the compositions provided herein may be used in combination with gefitinib. In other embodiments, the present embodiments may be practiced in combination with Gleevec (e.g., from about 400 to about 800 mg/day of Gleevec may be administered to a patient). In certain embodiments, one or more chemotherapeutic may be used in combination with the compositions provided herein. [000144] Radiotherapy: Other factors that cause DNA damage and have been used extensively include what are commonly known as y-rays, X-rays, and/or the directed delivery of radioisotopes to tumor cells. Other forms of DNA damaging factors are also known such as microwaves and UV-irradiation. It is most likely that all of these factors effect a broad range of damage on DNA, on the precursors of DNA, on the replication and repair of DNA, and on the assembly and maintenance of chromosomes. Dosage ranges for X-rays range from daily doses of 50 to 200 roentgens for prolonged periods of time (3 to 4 wk), to single doses of 2000 to 6000 roentgens. Dosage ranges for radioisotopes vary widely, and depend on the half-life of the isotope, the strength and type of radiation emitted, and the uptake by the neoplastic cells. [000145] Other Agents: It is contemplated that other agents may be used in combination with the compositions provided herein to improve the therapeutic efficacy of treatment. These additional agents include immunomodulatory agents, agents that affect the upregulation of cell surface receptors and GAP junctions, cytostatic and differentiation agents, inhibitors of cell adhesion, or agents that increase the sensitivity of the hyperproliferative cells to apoptotic inducers Immunomodulatory agents include tumor necrosis factor; interferon alpha, beta, and gamma; IL-2 and other cytokines; F42K and other cytokine analogs; or MIP-1, MIP-1beta, MCP-1, RANTES, and other chemokines. It is further contemplated that the upregulation of cell surface receptors or their ligands such as Fas/Fas ligand, DR4 or DR5/TRAIL would potentiate the apoptotic inducing abilities of the compositions provided herein by establishment of an autocrine or paracrine effect on hyperproliferative cells. Increases intercellular signaling by elevating the number of GAP junctions would increase the anti-hyperproliferative effects on the neighboring hyperproliferative cell population. In other embodiments, cytostatic or differentiation agents can be used in combination with the compositions provided herein to improve the anti-hyerproliferative efficacy of the treatments. Inhibitors of cell adhesion are contemplated to improve the efficacy of the present disclosure. Examples of cell adhesion inhibitors are focal adhesion kinase (FAKs) inhibitors and Lovastatin. It is further contemplated that other agents that increase the sensitivity of a hyperproliferative cell to apoptosis, such as the antibody c225, could be used in combination with the compositions provided herein to improve the treatment efficacy. [000146] In further embodiments, the other agents may be one or more oncolytic viruses, such as an oncolytic viruses engineered to express a gene other than p53 and/or IL24, such as a cytokine. Examples of oncolytic viruses include adenoviruses, adeno-associated viruses, retroviruses, lentiviruses, herpes viruses, pox viruses, vaccinia viruses, vesicular stomatitis viruses, polio viruses, Newcastle's Disease viruses, Epstein-Barr viruses, influenza viruses and reoviruses. In a particular embodiment, the other agent is talimogene laherparepvec (T-VEC) which is an oncolytic herpes simplex virus genetically engineered to express GM-CSF. Talimogene laherparepvec, HSV-1 [strain JS1] ICP34.5-/ICP47-/hGM-CSF, (previously known as OncoVEX ^GM GsF) is an intratumorally delivered oncolytic immunotherapy comprising an immune-enhanced HSV-1 that selectively replicates in solid tumors. (Lui et al., Gene Therapy, 10:292-303, 2003; U.S. Pat. No.7,223,593 and U.S. Pat. No.7,537,924; incorporated herein by reference). In October 2015, the US FDA approved T-VEC, under the brand name IMLYGIC ^TM , for the treatment of melanoma in patients with inoperable tumors. The characteristics and methods of administration of T-VEC are described in, for example, the IMLYGIC ^TM package insert (Amgen, 2015) and U.S. Patent Publication No. US2015/0202290; both incorporated herein by reference. For example, talimogene laherparepvec is typically administered by intratumoral injection into injectable cutaneous, subcutaneous, and nodal tumors at a dose of up to 4.0 ml of 10 ⁶ plaque forming unit/mL (PFU/mL) at day 1 of week 1 followed by a dose of up to 4.0 ml of 10 ⁸ PFU/mL at day 1 of week 4, and every 2 weeks (±3 days) thereafter. The recommended volume of talimogene laherparepvec to be injected into the tumor(s) is dependent on the size of the tumor(s) and should be determined according to the injection volume guideline. While T-VEC has demonstrated clinical activity in melanoma patients, many cancer patients either do not respond or cease responding to T-VEC treatment. Exemplary oncolytic viruses include, but are not limited to, Ad5-yCD/mutTKSR39rep-hIL12, Cavatak™, CG0070, DNX- 2401, G207, HF10, IMLYGIC™, JX-594, MG1-MA3, MV-NIS, OBP-301, Reolysin™, Toca 511, Oncorine, and RIGVIR. Other exemplary oncolytic viruses are described, for example, in International Patent Publication Nos. WO2015/027163, WO2014/138314, WO2014/047350, and WO2016/009017; all incorporated herein by reference. [000147] In certain embodiments, hormonal therapy may also be used in conjunction with the present embodiments or in combination with any other cancer therapy previously described. The use of hormones may be employed in the treatment of certain cancers such as breast, prostate, ovarian, or cervical cancer to lower the level or block the effects of certain hormones such as testosterone or estrogen. This treatment is often used in combination with at least one other cancer therapy as a treatment option or to reduce the risk of metastases. [000148] In some aspects, the additional anti-cancer agent is a protein kinase inhibitor or a monoclonal antibody that inhibits receptors involved in protein kinase or growth factor signaling pathways such as an EGFR, VEGFR, AKT, Erb1, Erb2, ErbB, Syk, Bcr-Abl, JAK, Src, GSK-3, PI3K, Ras, Raf, MAPK, MAPKK, mTOR, c-Kit, eph receptor or BRAF inhibitors. Nonlimiting examples of protein kinase or growth factor signaling pathways inhibitors include Afatinib, Axitinib, Bevacizumab, Bosutinib, Cetuximab, Crizotinib, Dasatinib, Erlotinib, Fostamatinib, Gefitinib, Imatinib, Lapatinib, Lenvatinib, Mubritinib, Nilotinib, Panitumumab, Pazopanib, Pegaptanib, Ranibizumab, Ruxolitinib, Saracatinib, Sorafenib, Sunitinib, Trastuzumab, Vandetanib, AP23451, Vemurafenib, MK-2206, GSK690693, A-443654, VQD-002, Miltefosine, Perifosine, CAL101, PX-866, LY294002, rapamycin, temsirolimus, everolimus, ridaforolimus, Alvocidib, Genistein, Selumetinib, AZD-6244, Vatalanib, P1446A-05, AG- 024322, ZD1839, P276-00, GW572016 or a mixture thereof. [000149] Administration of Pharmaceutical Compositions [000150] The pharmaceutical compositions embodied herein can, in one alternative, include a prodrug. When a pharmaceutical composition according to the present invention includes a prodrug, prodrugs and active metabolites of a compound may be identified using routine techniques known in the art. (See, e.g., Bertolini et al., J. Med. Chem., 40, 2011-2016 (1997); Shan et al., J. Pharm. Sci., 86 (7), 765-767; Bagshawe, Drug Dev. Res., 34, 220-230 (1995); Bodor, Advances in Drug Res., 13, 224-331 (1984); Bundgaard, Design of Prodrugs (Elsevier Press 1985); Larsen, Design and Application of Prodrugs, Drug Design and Development (Krogsgaard-Larsen et al., eds., Harwood Academic Publishers, 1991); Dear et al., J. Chromatogr. B, 748, 281-293 (2000); Spraul et al., J. Pharmaceutical & Biomedical Analysis, 10, 601-605 (1992); and Prox et al., Xenobiol., 3, 103-112 (1992)). [000151] The term "pharmaceutically acceptable" as used throughout this specification is consistent with the art and means compatible with the other ingredients of a pharmaceutical composition and not deleterious to the recipient thereof. [000152] As used herein, "carrier" or "excipient" includes any and all solvents, diluents, buffers (such as, e.g., neutral buffered saline or phosphate buffered saline), solubilizers, colloids, dispersion media, vehicles, fillers, chelating agents (such as, e.g., EDTA or glutathione), amino acids (such as, e.g., glycine), proteins, disintegrants, binders, lubricants, wetting agents, emulsifiers, sweeteners, colorants, flavorings, aromatizers, thickeners, agents for achieving a depot effect, coatings, antifungal agents, preservatives, stabilizers, antioxidants, tonicity controlling agents, absorption delaying agents, and the like. The use of such media and agents for pharmaceutical active components is well known in the art. Such materials should be non-toxic and should not interfere with the activity of the cells or active components. [000153] The precise nature of the carrier or excipient or other material will depend on the route of administration. For example, the composition may be in the form of a parenterally acceptable aqueous solution, which is pyrogen-free and has suitable pH, isotonicity and stability. For general principles in medicinal formulation, the reader is referred to Cell Therapy: Stem Cell Transplantation, Gene Therapy, and Cellular Immunotherapy, by G. Morstyn & W. Sheridan eds., Cambridge University Press, 1996; and Hematopoietic Stem Cell Therapy, E. D. Ball, J. Lister & P. Law, Churchill Livingstone, 2000. [000154] The pharmaceutical composition can be applied parenterally, rectally, orally or topically. Preferably, the pharmaceutical composition may be used for intravenous, intramuscular, subcutaneous, peritoneal, peridural, rectal, nasal, pulmonary, mucosal, or oral application. In a preferred embodiment, the pharmaceutical composition according to the invention is intended to be used as an infusion. The skilled person will understand that compositions which are to be administered orally or topically will usually not comprise cells, although it may be envisioned for oral compositions to also comprise cells, for example when gastro-intestinal tract indications are treated. Each of the cells or active components (e.g., immunomodulants) as discussed herein may be administered by the same route or may be administered by a different route. By means of example, and without limitation, cells may be administered parenterally and other active components may be administered orally. [000155] Liquid pharmaceutical compositions may generally include a liquid carrier such as water or a pharmaceutically acceptable aqueous solution. For example, physiological saline solution, tissue or cell culture media, dextrose or other saccharide solution or glycols such as ethylene glycol, propylene glycol or polyethylene glycol may be included. [000156] The composition may include one or more cell protective molecules, cell regenerative molecules, growth factors, anti-apoptotic factors or factors that regulate gene expression in the cells. Such substances may render the cells independent of their environment. [000157] Such pharmaceutical compositions may contain further components ensuring the viability of the cells therein. For example, the compositions may comprise a suitable buffer system (e.g., phosphate or carbonate buffer system) to achieve desirable pH, more usually near neutral pH, and may comprise sufficient salt to ensure isoosmotic conditions for the cells to prevent osmotic stress. For example, suitable solution for these purposes may be phosphate- buffered saline (PBS), sodium chloride solution, Ringer's Injection or Lactated Ringer's Injection, as known in the art. Further, the composition may comprise a carrier protein, e.g., albumin (e.g., bovine or human albumin), which may increase the viability of the cells. [000158] Further suitably pharmaceutically acceptable carriers or additives are well known to those skilled in the art and for instance may be selected from proteins such as collagen or gelatine, carbohydrates such as starch, polysaccharides, sugars (dextrose, glucose and sucrose), cellulose derivatives like sodium or calcium carboxymethylcellulose, hydroxypropyl cellulose or hydroxypropylmethyl cellulose, pregeletanized starches, pectin agar, carrageenan, clays, hydrophilic gums (acacia gum, guar gum, arabic gum and xanthan gum), alginic acid, alginates, hyaluronic acid, polyglycolic and polylactic acid, dextran, pectins, synthetic polymers such as water-soluble acrylic polymer or polyvinylpyrrolidone, proteoglycans, calcium phosphate and the like. [000159] In certain embodiments, a pharmaceutical cell preparation as taught herein may be administered in a form of liquid composition. In embodiments, the cells or pharmaceutical composition comprising such can be administered systemically, topically, within an organ or at a site of organ dysfunction or lesion. [000160] Preferably, the pharmaceutical compositions may comprise a therapeutically effective amount of the specified immune cells and/or other active components (e.g., immunomodulants). The term "therapeutically effective amount" refers to an amount which can elicit a biological or medicinal response in a tissue, system, animal or human that is being sought by a researcher, veterinarian, medical doctor or other clinician, and in particular can prevent or alleviate one or more of the local or systemic symptoms or features of a disease or condition being treated. [000161] It will be appreciated that administration of therapeutic entities in accordance with the invention will be administered with suitable carriers, excipients, and other agents that are incorporated into formulations to provide improved transfer, delivery, tolerance, and the like. A multitude of appropriate formulations can be found in the formulary known to all pharmaceutical chemists: Remington's Pharmaceutical Sciences (15th ed, Mack Publishing Company, Easton, Pa. (1975)), particularly Chapter 87 by Blaug, Seymour, therein. These formulations include, for example, powders, pastes, ointments, jellies, waxes, oils, lipids, lipid (cationic or anionic) containing vesicles (such as Lipofectin™), DNA conjugates, anhydrous absorption pastes, oil-in- water and water-in-oil emulsions, emulsions carbowax (polyethylene glycols of various molecular weights), semi-solid gels, and semi-solid mixtures containing carbowax. Any of the foregoing mixtures may be appropriate in treatments and therapies in accordance with the present invention, provided that the active ingredient in the formulation is not inactivated by the formulation and the formulation is physiologically compatible and tolerable with the route of administration. See also Baldrick P. "Pharmaceutical excipient development: the need for preclinical guidance." Regul. Toxicol Pharmacol.32(2):210-8 (2000), Wang W. "Lyophilization and development of solid protein pharmaceuticals." Int. J. Pharm.203(1-2):1-60 (2000), Charman W N "Lipids, lipophilic drugs, and oral drug delivery-some emerging concepts." J Pharm Sci.89(8):967-78 (2000), Powell et al. "Compendium of excipients for parenteral formulations" PDA J Pharm Sci Technol.52:238-311 (1998) and the citations therein for additional information related to formulations, excipients and carriers well known to pharmaceutical chemists. [000162] The medicaments of the invention are prepared in a manner known to those skilled in the art, for example, by means of conventional dissolving, lyophilizing, mixing, granulating or confectioning processes. Methods well known in the art for making formulations are found, for example, in Remington: The Science and Practice of Pharmacy, 20th ed., ed. A. R. Gennaro, 2000, Lippincott Williams & Wilkins, Philadelphia, and Encyclopedia of Pharmaceutical Technology, eds. J. Swarbrick and J. C. Boylan, 1988-1999, Marcel Dekker, New York. [000163] Administration of medicaments of the invention may be by any suitable means that results in a compound concentration that is effective for treating or inhibiting (e.g., by delaying) the development of a disease. The compound is admixed with a suitable carrier substance, e.g., a pharmaceutically acceptable excipient that preserves the therapeutic properties of the compound with which it is administered. One exemplary pharmaceutically acceptable excipient is physiological saline. The suitable carrier substance is generally present in an amount of 1-95% by weight of the total weight of the medicament. The medicament may be provided in a dosage form that is suitable for administration. Thus, the medicament may be in form of, e.g., tablets, capsules, pills, powders, granulates, suspensions, emulsions, solutions, gels including hydrogels, pastes, ointments, creams, plasters, drenches, delivery devices, injectables, implants, sprays, or aerosols. [000164] Administration can be systemic or local. In addition, it may be advantageous to administer the composition into the central nervous system by any suitable route, including intraventricular and intrathecal injection. Pulmonary administration may also be employed by use of an inhaler or nebulizer, and formulation with an aerosolizing agent. It may also be desirable to administer the agent locally to the area in need of treatment; this may be achieved by, for example, and not by way of limitation, local infusion during surgery, topical application, by injection, by means of a catheter, by means of a suppository, or by means of an implant. [000165] Various delivery systems are known and can be used to administer the pharmacological compositions including, but not limited to, encapsulation in liposomes, microparticles, microcapsules; minicells; polymers; capsules; tablets; and the like. In one embodiment, the agent may be delivered in a vesicle, in particular a liposome. In a liposome, the agent is combined, in addition to other pharmaceutically acceptable carriers, with amphipathic agents such as lipids which exist in aggregated form as micelles, insoluble monolayers, liquid crystals, or lamellar layers in aqueous solution. Suitable lipids for liposomal formulation include, without limitation, monoglycerides, diglycerides, sulfatides, lysolecithin, phospholipids, saponin, bile acids, and the like. Preparation of such liposomal formulations is within the level of skill in the art, as disclosed, for example, in U.S. Pat. Nos.4,837,028 and 4,737,323. In yet another embodiment, the pharmacological compositions can be delivered in a controlled release system including, but not limited to: a delivery pump (See, for example, Saudek, et al., New Engl. J. Med.321: 574 (1989) and a semi-permeable polymeric material (See, for example, Howard, et al., J. Neurosurg.71: 105 (1989)). Additionally, the controlled release system can be placed in proximity of the therapeutic target (e.g., a tumor), thus requiring only a fraction of the systemic dose. See, for example, Goodson, In: Medical Applications of Controlled Release, 1984. (CRC Press, Boca Raton, Fla.). [000166] The amount of the agents which will be effective in the treatment of a particular disorder or condition will depend on the nature of the disorder or condition and may be determined by standard clinical techniques by those of skill within the art. In addition, in vitro assays may optionally be employed to help identify optimal dosage ranges. The precise dose to be employed in the formulation will also depend on the route of administration, and the overall seriousness of the disease or disorder, and should be decided according to the judgment of the practitioner and each patient's circumstances. Ultimately, the attending physician will decide the amount of the agent with which to treat each individual patient. In certain embodiments, the attending physician will administer low doses of the agent and observe the patient's response. Larger doses of the agent may be administered until the optimal therapeutic effect is obtained for the patient, and at that point the dosage is not increased further. Effective doses may be extrapolated from dose-response curves derived from in vitro or animal model test systems. Ultimately the attending physician will decide on the appropriate duration of therapy using compositions of the present invention. Dosage will also vary according to the age, weight and response of the individual patient. [000167] There are a variety of techniques available for introducing nucleic acids into viable cells. The techniques vary depending upon whether the nucleic acid is transferred into cultured cells in vitro, or in vivo in the cells of the intended host. Techniques suitable for the transfer of nucleic acid into mammalian cells in vitro include the use of liposomes, electroporation, microinjection, cell fusion, DEAE-dextran, the calcium phosphate precipitation method, etc. The currently preferred in vivo gene transfer techniques include transfection with viral (typically retroviral) vectors and viral coat protein-liposome mediated transfection. [000168] EXAMPLES [000169] Example 1: Transcriptional Programs of Neoantigen-Specific TIL in Anti-PD1- Treated NSCLC. [000170] PD-1 blockade “unleashes” CD8 T-cells ¹ , including those specific for mutation- associated neoantigens (MANA), but factors in the tumor microenvironment can inhibit these T- cell responses. Single cell transcriptomics have revealed global T-cell dysfunction programs in tumor-infiltrating lymphocytes (TIL). However, the majority of TIL do not recognize tumor antigens ² and little is known about transcriptional programs of MANA-specific TIL. Here, MANA-specific T-cell clones were identified using the MANA functional expansion of specific T-cells (MANAFEST) assay ³ in neoadjuvant anti-PD-1-treated lung cancers. Their T-cell receptor (TCR) was used as a “barcode” to track and analyze their transcriptional programs in the tumor microenvironment using coupled single cell TCR sequencing/RNA sequencing. It was found that both MANA- and virus-specific clones in TIL, regardless of response, and MANA-, influenza (flu)-, and Epstein Barr Virus-specific TIL each have unique transcriptional programs. Despite exposure to cognate antigen, MANA-specific TIL express an incompletely activated cytolytic program. MANA-specific CD8 T-cells have hallmark transcriptional programs of tissue resident memory (TRM) cells, but low levels of IL7R and are functionally less responsive to IL7 compared with flu-specific TRM cells. Compared to those from responding tumors, MANA- specific clones from non-responding tumors express TCR with markedly lower ligand-dependent signaling, are largely confined to HOBIT ^hi TRM subsets, and coordinately up-regulate checkpoints, killer inhibitory receptors, and inhibitors of T-cell activation. These findings provide important insights for overcoming resistance to PD-1 blockade. [000171] Methods [000172] Patients and biospecimens: This study was approved by the Institutional Review Boards (IRB) at Johns Hopkins University (JHU) and Memorial Sloan Kettering Cancer Center and was conducted in accordance with the Declaration of Helsinki and the International Conference on Harmonization Good Clinical Practice guidelines. The patients described in this study provided written informed consent. All biospecimens were obtained from patients with stage I-IIIA NSCLC who were enrolled to a phase II clinical trial evaluating the safety and feasibility of administering two doses of anti-PD-1 (nivolumab) prior to surgical resection. Pathological response assessments of primary tumors were reported previously ^8,31 . Tumors with no more than 10% residual viable tumor cells were considered to have a major pathologic response. [000173] Single cell TCRseq/RNAseq: Cryobanked T-cells were thawed and washed twice with pre-warmed RPMI with 20% FBS and gentamicin. Cells were resuspended in PBS and stained with a viability marker (LIVE/DEAD™ Fixable Near-IR; ThermoFisher) for 15mins at RT in the dark. Cells were then incubated with FC block for 15 mins on ice and stained with antibody against CD3 (BV421, clone SK7) for 30mins on ice. After staining, highly viable CD3 ⁺ T-cells were sorted into 0.04% BSA in PBS using a BD FACSAria II Cell Sorter. Sorted cells were manually counted using a hemocytometer and prepared at the desired cell concentration (1000 cells/µl), when possible. The Single Cell 5’ V(D)J and 5’ DGE kits (10X Genomics) were used to capture immune repertoire information and gene expression from the same cell in an emulsion-based protocol at the single cell level. Cells and barcoded gel beads were partitioned into nanoliter scale droplets using the 10X Genomics Chromium platform to partition up to 10,000 cells per sample followed by RNA capture and cell-barcoded cDNA synthesis using the manufacturer’s standard protocols. Libraries were generated and sequenced on an Illumina NovaSeq instrument using 2x150bp paired end sequencing.5’ VDJ libraries were sequenced to a depth of ~5,000 reads per cell, for a total of 5 million to 25 million reads. The 5’ DGE libraries were sequenced to a target depth of ~50,000 reads per cell. [000174] Whole Exome Sequencing (WES), Mutation Calling, and Neoantigen Prediction:Genomic data for most patients in the study were reported previously ⁸ , and whole exome sequencing, variant calling, and neoantigen predictions for patients MD043-003 and NY016-025 were performed prospectively for the present study. Whole exome sequencing was performed on pre-treatment tumor unless otherwise noted (Table 4) and matched normal samples. DNA was extracted from patients’ tumors and matched peripheral blood using the Qiagen DNA kit (Qiagen, CA). Fragmented genomic DNA from tumor and normal samples was used for Illumina TruSeq library construction (Illumina, San Diego, CA) and exonic regions were captured in solution using the Agilent SureSelect v.4 kit (Agilent, Santa Clara, CA) according to the manufacturers’ instructions as previously described ³² . Paired-end sequencing, resulting in 100 bases from each end of the fragments for the exome libraries was performed using Illumina HiSeq 2000/2500 instrumentation (Illumina, San Diego, CA). The depth of total and distinct coverage is shown in Table 4. Somatic mutations, consisting of point mutations, insertions, and deletions across the whole exome were identified using the VariantDx custom software for identifying mutations in matched tumor and normal samples as previously described ^32,33 . Somatic mutations, consisting of nonsynonymous single base substitutions, insertions and deletions, were evaluated for putative MHC class I neoantigens using the ImmunoSelect-R pipeline (Personal Genome Diagnostics, Baltimore, MD) as previously described ³⁰ . Somatic sequence alterations are listed in Table 5. [000175] Identification of Neoantigen-Specific TCR Vβ CDR3 Clonotypes: The MANAFEST (Mutation Associated NeoAntigen Functional Expansion of Specific T-cells) assay ³ was used to evaluate T-cell responsiveness to MANA and viral antigens. Briefly, pools of MHC class I-restricted CMV, EBV, and flu peptide epitopes (CEFX, jpt Peptide Technologies), pools representing the matrix protein and nucleoprotein from H1N1 and H3N2 (jpt Peptide Technologies), and putative neoantigenic peptides defined by the ImmunoSelect-R pipeline (jpt Peptide Technologies; Table 6) were each used to stimulate 250,000 T-cells in vitro for 10 days as previously described ³ . The timepoint of peripheral blood collection used for each MANAFEST assay is described in Tables 2 and 7. Briefly, on day 0, T-cells were isolated from peripheral blood mononuclear cells (PBMC) by negative selection (EasySep; STEMCELL Technologies). The T-cell–negative fraction was co-cultured with an equal number of selected T- cells in culture medium (IMDM/5% human serum with 50 μg/mL gentamicin) with 1 μg/mL relevant neoantigenic peptide, 1 μg/mL of an MHC class I-restricted CMV, EBV, and flu peptide epitope pool (CEFX, jpt Peptide Technologies), 1 μg/mL of pools representing the matrix protein and nucleoprotein from H1N1 and H3N2 (jpt Peptide Technologies), or no peptide (to use as a reference for non-specific/background clonotypic expansion). On day 3, half the medium was replaced with fresh medium containing cytokines for a final concentration of 50 IU/ml IL-2 (Chiron), 25 ng/ml IL7 (Miltenyi), and 25 ng/ml IL-15 (PeproTech). On day 7, half the medium was replaced with fresh culture medium containing cytokines for a final concentration of 100 IU/mL IL-2 and 25 ng/mL IL7 and IL-15. On day 10, cells were harvested, washed twice with PBS, and the CD8 ⁺ fraction was isolated using a CD8 ⁺ negative enrichment kit (EasySep; STEMCELL Technologies). DNA was extracted from each CD8-enriched culture condition using the Qiamp micro-DNA kit according to the manufacturer’s instructions. T-cell receptor sequencing was performed on each individual peptide-stimulated T-cell culture using survey- level sequencing (max depth ~60,000 reads) by Adaptive Biotechnologies using their established platform ³⁴ or by the Sidney Kimmel Comprehensive Cancer Center FEST and TCR Immunogenomics Core (FTIC) facility using the Oncomine TCR Beta short-read assay (Illumina, Inc.) and sequenced on an Illumina iSeq 100 using unique dual indexes, for a maximum of ~40,000 reads/sample. [000176] Data pre-processing was performed to eliminate non-productive TCR sequences and to align and trim the nucleotide sequences to obtain only the CDR3 region. Sequences not beginning with “C” or ending with “F” or “W” and having less than 7 amino acids in the CDR3 were eliminated. TCR sequencing samples with less than 1,000 productive reads were excluded from downstream analysis. MD043-011-MANA_22 was the only such sample in the present study (see Table 7). Resultant processed data files were uploaded to our publicly available MANAFEST analysis web app (stat-apps.onc.jhmi.edu) to bioinformatically identify antigen- specific T-cell clonotypes. [000177] Bioinformatic analysis of productive clones was performed to identify antigen- specific T-cell clonotypes meeting the following criteria: 1) significant expansion (Fisher’s exact test with Benjamini-Hochberg correction for FDR, p<0.05) compared to T-cells cultured without peptide, 2) significant expansion compared to every other peptide-stimulated culture (FDR<0.05) except for conditions stimulated with similar neoantigens derived from the same mutation, 3) an odds ratio >5 compared to the “no peptide” control, and 4) present in at least 10% of the cultured wells to ensure adequate distribution among culture wells. A lower read threshold of 300 was used for assays sequenced by the FTIC and a lower threshold of 30 was used for samples sequenced by Adaptive Biotechnologies. In MANAFEST assays testing less than 10 peptides or peptide pools, cultures were performed in triplicate and reactive clonotypes were defined as being significantly expanded relative to T-cells cultured without peptide (FDR<0.05) in two out of three triplicates, and not significantly expanded in any other well tested. When available, TCRseq was also performed on DNA extracted from tumor, normal lung, and lymph node tissue obtained before treatment and at the time of surgical resection, as well as serial peripheral blood samples. The assays performed on each biospecimen are outlined in Table 2. [000178] Peptide Affinity and stability measurements: Peptide affinity for cognate HLA molecules was assessed using a luminescent oxygen channeling immunoassay (LOCI; AlphaScreen, Perkin Elmer) as previously described ³⁵ . This is a proximity-based system using a “donor” and “acceptor” bead, each conjugated with an epitope tag. When the donor bead is excited with light at 650nm and can activate an acceptor bead, resulting in a signal at 520- 620nm, which can be quantified per second as a surrogate of affinity. A higher number of counts per second indicates higher affinity of the peptide:HLA pair. The stability of peptide loaded complexes was measured by refolding MHC with peptide and subsequently challenging complexes with a titration of urea. The denaturation of MHC was monitored by ELISA as described previously ³⁶ . [000179] TCR reconstruction and cloning: Ten MANAFEST ⁺ TCR sequences for which the TCRα chain could be enumerated (>3 cells in single cell data with the same α/β pair) were selected for cloning. In addition, 7 clones (from 3 patients: MD01-004, MD01-005, MD043-011) that have high composite signature (using the AddModuleScore function) consisting of differential gene programs of MANA-specific T-cell relative to flu-specific T-cells in the TRM were selected for cloning. Relevant TCRs were analyzed with the IMGT/V-Quest database (imgt.org/IMGT). The database allows for the identification of the TRAV and TRBV families with the highest likelihood to contain the identified segments which match the sequencing data. To generate the TCRs, the identified TCRA V-J region sequences were fused to the human TRA constant chain, and the TCRB V-D-J regions to the human TRB constant chain. The full-length TCRA and TCRB chains were then synthesized as individual gene blocks (IDT) and cloned into the pCI mammalian expression vector, containing a CMV promoter, and transformed into competent E. coli cells according to manufacturer’s instructions (NEBuilder HiFi DNA Assembly, NEB). Post transformation and plasmid miniprep, the plasmids were sent for Sanger sequencing to ensure no mutations were introduced (Genewiz). [000180] T-cell transfection, transient TCR expression, and MANA recognition assays: To generate a Jurkat reporter cell in which the TCRs of interest could be transferred, the endogenous T-cell receptor (TCR) α and β chains were knocked out of a specific Jurkat line that contains a luciferase reporter driven by an NFAT-response element (Promega) using the Alt-R CRISPR system (Integrated DNA Technologies, IDT). Two sequential rounds of CRISPR knockout were performed using crDNA targeting the TCRα constant region (AGAGTCTCTCAGCTGGTACA) and the TCRβ constant region (AGAAGGTGGCCGAGACCCTC). Limiting dilution was then used to acquire single cell clones and clones with both TCRα and TCRβ knocked out, as confirmed by Sanger sequencing and restoration of CD3 expression only by the co-transfection of TCRα or TCRβ chains, were chose. CD8α and CD8β chains were then transduced into the TCRα-/β- Jurkat reporter cells using the MSCV retroviral expression system (Clontech). Jurkat reporter cells were then co-electroporated with the pCI vector encoding the TCRB and TCRA gene blocks, respectively, using ECM830 Square wave electroporation system (BTX) at 275volts for 10ms in OptiMem media in a 4mm cuvette. Post electroporation, cells were rested overnight by incubating in in RPMI 10% FBS at 37°C, 5% CO2. TCR expression was confirmed by flow cytometric staining for CD3 on a BD FACSCelesta and 50,000 CD3 ⁺ T-cells were plated in each well of a 96-well plate. Reactivity of the TCR-transduced Jurkat cells was assessed by co- culturing with 1 x 10 ⁵ autologous EBV-transformed B cells, loaded with titrating concentrations of MANA peptides, viral peptide pools, or negative controls. After overnight incubation, activation of the NFAT reporter gene was measured by the Bio-Glo Luciferase Assay per manufacturer’s instructions (Promega). Jurkat cells were routinely tested for mycoplasma contamination. No cell line authentication was performed. [000181] COS-7 transfection with HLA allele and p53 plasmids: gBlocks (IDT) encoding HLA A*6801, p53 R248L and p53 WT were cloned into pcDNA3.4 vector (Thermo Fisher Scientific, A14697). COS-7 cells were transfected with plasmids at 70-80% confluency using Lipofectamine 3000 (Thermo Fisher Scientific, L3000015) and incubated at 37°C overnight in T75 flasks. A total of 30 μg plasmid (1:1 ratio of HLA plasmid/target protein plasmid in co- transfections) was used. Post transfection, COS-7 cells were plated with TCRαβ transfected JurkaT-cells containing NFAT reporter gene at a 1:1 ratio. After overnight incubation, activation of the NFAT reporter gene was measured by the Bio-Glo Luciferase Assay per manufacturer’s instructions (Promega). [000182] Single cell data preprocessing and quality control: Cell Ranger v3.1.0 was used to demultiplex the FASTQ reads, align them to the GRCh38 human transcriptome, and extract their “cell” and “UMI” barcodes. The output of this pipeline is a digital gene expression (DGE) matrix for each sample, which records the number of UMIs for each gene that are associated with each cell barcode. The quality of cells was then assessed based on (1) the number of genes detected per cell and (2) the proportion of mitochondrial gene/ribosomal gene counts. Low- quality cells were filtered if the number of detected genes was below 250 or above 3× the median absolute deviation away from the median gene number of all cells. Cells were filtered out if the proportion of mitochondrial gene counts was higher than 10% or the proportion of ribosomal genes was less than 10%. For single-cell VDJ sequencing, only cells with full-length sequences were retained. Dissociation/stress associated genes ^37,38 , mitochondrial genes (annotated with the prefix “MT-”), high abundance lincRNA genes, genes linked with poorly supported transcriptional models (annotated with the prefix “RP-”) ³⁹ and TCR (TR) genes (TRA/TRB/TRD/TRG, to avoid clonotype bias) were removed from further analysis. In addition, genes that were expressed in less than five cells were excluded. [000183] Single cell data integration and clustering: Seurat (3.1.5) ⁴⁰ was used to normalize the raw count data, identify highly variable features, scale features, and integrate samples. Principal component analysis (PCA) was performed based on the 3,000 most variable features identified using the vst method implemented in Seurat. Gene features associated with type I Interferon (IFN) response, immunoglobulin genes and specific mitochondrial related genes were excluded from clustering to avoid cell subsets driven by the above genes ³⁹ . Dimension reduction was done using the RunUMAP function. Cell markers were identified by using a two-sided Wilcoxon rank sum test. Genes with adjusted p.value < 0.05 were retained. Clusters were labeled based on the expression of the top differential gene in each cluster as well as canonical immune cell markers. Global clustering on all CD3 T-cells and refined clustering on CD8 T-cells were performed using same procedure. To select for CD8 ⁺ T-cells, SAVER ⁴¹ was used to impute dropouts by borrowing information across similar genes and cells. A density curve was fitted to the log2-transformed SAVER imputed CD8A expression values (using ‘density’ function in R) of all cells from all samples. A cutoff is determined as the trough of the bimodal density curve (i.e. the first location where the first derivative is zero and the second derivative is positive). All cells with log ₂ -transformed SAVER imputed CD8A expression larger than the cutoff are defined as CD8 ⁺ T-cells. TRB amino acid (aa) sequences were used as a biological barcode to match MANA/EBV/Influenza A specific T-cell clonotypes identified from the FEST assay with single- cell VDJ profile and were projected onto CD8 ⁺ T-cell refined UMAP. [000184] Single cell subset pseudobulk gene expression analysis: PCA was performed on a standardized pseudobulk gene expression profile, where each feature was standardized to have a mean of zero and unit variance. In global CD3 and CD8 TIL PCA, for each cell cluster we first aggregated read counts across cells within the cluster to produce a pseudobulk expression profile for each sample and normalized these pseudobulk expression profiles across samples by library size. Combat function in the “sva” R package ^42,43 was applied to address potential batch effects on the normalized pseudobulk profile. Highly variable genes (HVGs) were selected for each cell cluster by fitting a locally weighted scatterplot smoothing (LOESS) regression of standard deviation against the mean for each gene and identifying genes with positive residuals. For each sample, all cell clusters were then concatenated by retaining each cluster’s HVGs to construct a concatenated gene expression vector consisting of all highly variable features identified from different cell clusters. Each element in this vector represents the pseudobulk expression of a HVG in a cell cluster. Samples were embedded into the PCA space based on these concatenated gene expression vectors. Canonical correlation ^44,45 between the first two PCs (i.e., PC1 and PC2) and a covariate of interest (i.e., tissue type or response status) was calculated. Permutation test was used to assess the significance by randomly permuting the sample labels 10,000 times. In the MANA-specific PCA (FIGS.15A-15D), MANA-enriched cell clusters, defined by clusters with MANA-specific T-cell frequency at least two fold higher than randomly expected, were aggregated as one combined cell cluster. Then, a similar procedure by first identifying HVGs, computing the first 2 PCs and then calculating the canonical correlation was repeated for the combined MANA-enriched cell cluster and each of the other CD8 clusters. [000185] Differential analysis comparing MPR vs non-MPR by total CD8/CD4 TIL and by cell cluster: The gene expression read counts were adjusted by library size. SAVER ⁴¹ was used to impute the dropouts, and further log ₂ -transformed the imputed values after adding a pseudocount of 1. A linear mixed-effect model ⁴⁶ was constructed to identify genes that are significantly differential between MPR and non-MPR among total CD8/CD4 TIL and by each cell cluster, respectively. The B-H procedure ⁴⁷ was used to adjust the p-values for multiple testing, and the statistical significance is determined using a cutoff of FDR < 0.05. [000186] Differential expression tests and antigen-specific T-cell marker genes: Differential expression (DE) tests for antigen specific T-cells were performed using FindAllMarkers functions in Seurat with Wilcoxon Rank Sum test on SAVER imputed expression values. Genes with > 0.25 log2-fold changes, at least 25% expressed in tested groups, and Bonferroni-corrected p values < 0.05 were regarded as significantly differentially expressed genes (DEGs). Antigen-specific (MANA vs flu vs EBV) T-cell marker genes were identified by applying the DE tests for upregulated genes between cells of one antigen specificity to all other antigen specific-T-cells in the dataset. MANA-specific T-cell genes associated with response to ICB were identified by applying the DE tests comparing MANA-specific T-cells from MPR vs those from non-MPR. Top ranked DEGs (by log-fold changes) with a log2-fold changes > 0.8 and DEGs relating to T-cell function were extracted for further visualization in heatmap using pheatmap package ⁴⁸ . SAVER imputed expression values of selective marker genes (transcriptional regulators/memory markers/tissue resident markers/T-cell checkpoints/effector/activation markers) were plotted using the RidgePlot function in Seurat. [000187] In vitro short-term TIL stimulation with IL7: Cryopreserved TIL from patient MD01-004 were thawed, counted, and stained with the LIVE/DEAD™ Fixable Aqua (ThermoFisher) viability marker and antibodies specific for CD3 (PE, clone SK1) and CD8 (BV786, clone RPA-T8). Thirty thousand CD8 ⁺ T-cells per condition were sorted on a BD FACSAria II Cell Sorter into a 96-well plate. Autologous T-cell-depleted PBMC were added as antigen presenting cells (APC) at 1:1 ratio. The cells were stimulated with either influenza A or MD01-004-MANA 12 peptide and titrating concentrations of recombinant human IL7 (Miltenyi) for 12 hours in a round-bottomed 96-well plate. [000188] Gene expression analysis of IL7-stimulated MANA/flu-specific TIL: Following 12 hours of antigen and IL7 stimulation, cells were spun down, counted and re-suspended in 1% BSA at desired concentration. Single-cell RNA seq and VDJ libraries were prepared using 10x Chromium single cell platform using 5’ DGE library preparation reagents and kits according to manufacturer’s protocols (10x Genomics, Pleasonton, CA) and as described above. MANA/flu- specific T-cell clonotypes from the single-cell dataset were identified by using the TRB amino acid sequences as a biological barcode. SAVER imputed gene expression was scaled and centered using the “ScaleData” function in Seurat. A composite score for the IL7-upregulated gene set ⁴⁹ expression was computed using the AddModuleScore function and subsequently visualized using ridgeplot. Mean ± standard error was used to show the dose response curve of the IL7-upregulated gene set score by antigen-specific T-cells+peptide stimulation groups. [000189] Immune checkpoint/exhaustion score generation and highly correlated genes: To characterize dysfunctional CD8 MANA TIL, 6 best characterized (and clinically targeted) checkpoints: CTLA4, PDCD1, LAG3, HAVCR2, TIGIT and ENTPD1, were used to compute the T-cell checkpoint score, and a published gene list from exhausted T-cells was used to compute the T-cell exhaustion score, using AddModuleScore function in Seurat. Applying T-cell checkpoint score as an anchor, genes that were maximally correlated to the score were identified using linear correlation in MANA-specific TIL from MPR and non-MPR, respectively. Top 30 genes (from HVG selected using FindVariableGenes function in Seurat and excluded the 6 genes included in immune checkpoint score generation) with the highest correlation coefficients were plotted using barplot. The difference of correlation coefficients of the above genes was additionally computed between MPR and non-MPR and visualized using waterfall plot. [000190] Evaluation of peripheral MANA-specific T-cell transcriptome changes during treatment: Peripheral blood T cells from patient MD01-005 were sorted based on expression of CD8 and TCR V ^2, followed by single cell TCRseq/RNAseq and clustering on conventional CD8 ⁺ T cells (MAIT cells excluded). To evaluate whether there was a statistically significant change in the cell types of MANA cells between week 2 (W2) and week 4 (W4) samples in FIGS.4D-4D, a Fisher’s exact test was conducted which yields a p-value=0.021, indicating a statistically significant phenotype change in MANA-specific cells (FIG.4E). A more sophisticated test was also conducted to adjust for potential background differences in cell type abundance between W2 and W4 samples. In this test, mc,t denotes the probability that a MANA- specific T-cell collected at time point t (=W2 or W4) comes from cell type c, and let p _c,t denote the proportion of all cells in time point t that come from cell type c. We evaluated the ratio R _c,t = mc,t/pc,t, which characterizes the relative abundance of MANA-specific T-cells in each cell type. The null model was compared where this ratio does not change over time (H0: Rc,W2 = Rc,W4 for all cell type c) versus the alternative model where W2 and W4 have different ratios (H ₁ : R _c,W2 ≠ Rc,W4). To do this, the test statistic were computed using the observed data and compared it to its null distribution obtained using Monte Carlo simulations. To construct the null distribution for ^^, cells were pooled from W2 and W4 together and treated them as one sample to estimate the common ratio Rc,W2 = Rc,W4 = Rc shared by W2 and W4, and then derived the probability that a MANA-specific T-cell collected at time point t comes from cell type c under the null model H ₀ , which is proportional to p _c,t R _c (i.e. the product of the sample-specific background cell type proportion pc,t and the common MANA-abundance ratio Rc shared between samples). The MANA-specific T-cells at timepoint t were then redistributed to different cell types randomly based on a multinomial distribution with this expected MANA- specific T-cell type proportion (i.e., the expected probability that a MANA-specific T-cell at time point t comes from cell type c under H0 is while keeping the total number of MANA-specific T-cells at each time point the same as the observed MANA-specific T-cell number at that time point. The test statistic S was then computed using this simulated sample. This simulation was repeated 10,000 times to derive the null distribution of S. Comparing the observed S to its null distribution yields a p-value < 1e-4. [000191] RNA velocity-based differentiation trajectory tracing: The RNA velocity analysis was performed by first recounting the spliced reads and unspliced reads based on aligned bam files of scRNA-seq data using the velocyto python package. The calculation of RNA velocity values for each gene in each cell and embedding RNA velocity vector to low-dimension space were done using the SeuratWapper workflow for estimating RNA velocity using Seurat (github.com/satijalab/seurat-wrappers/blob/master/docs/veloc ity.md). The first two diffusion components from Diffusion map were used to construct the coordinates along with velocity. TSCAN (v.1.7.0) was used to reconstruct the cellular pseudotime on diffusion maps space for the PBMC T-cells from three time points (samples) of one patient (MD01-005). Based on velocity analysis, the T _memory (3) cluster was specified as the starting cluster for the pseudotemporal trajectory which has branches. For each branch, log2-transformed and library size-normalized SAVER-imputed gene expression values were used for analyzing gene expression dynamics along the pseudotime.10,325 genes with normalized expression ≥ 0.01 in at least 1% of cells were retained. For each gene g, the gene expression along pseudotime t in each sample s was described as a function which was obtained by fitting B-spline regression to the gene’s normalized expression values in single cells. The red curves in FIG.4H are the mean of the function of the three samples. In order to test whether the gene expression shows a significant change along pseudotime, the above model was compared with a null model in which is assumed to be a constant over time. The likelihood ratio statistic between the two models was computed. To determine the p-value, the null distribution of the likelihood ratio statistic was constructed by permuting the pseudotime of cells in each sample, refitting the models and recomputing the likelihood ratio statistic. The p-value was calculated as the number of permutations out of a total of 1,000 permutations that produce a likelihood ratio statistic larger than the observed one. The p-values from all genes were converted to FDR by Benjamini- Hochberg procedure to adjust for multiple testing. Genes with FDR < 0.05 were considered as dynamic genes with statistical significance. K-means clustering was applied to group genes with similar dynamic expression patterns into clusters. topGO (v.2.42.0) was used to identify the enriched Gene Ontology terms by comparing the genes in each cluster to all 10325 genes as background. [000192] Data Availability: Bulk TCR V ^ sequencing data generated by Adaptive Biotechnologies is available in the Adaptive Biotechnologies ImmuneACCESS repository under DOI 10.21417/JC2021N, at clients.adaptivebiotech.com/pub/caushi-2021-n. Bulk TCR V ^ raw and processed sequencing data generated by the SKCCC FTIC are available in GEO with accession number GSE173351. Raw scRNAseq/TCRseq data reported in this paper are available in the European Genome-phenome archive under controlled access with accession number EGAS00001005343. Due to the personal, sensitive and inherently identifying nature of raw genomic data, access to rawRNAseq/TCRseq data are controlled and full instructions to apply for data access can be found at ega-archive.org/access/data-access. Approvals will be granted immediately upon confirmation that all requirements are met. Processed and de-identified single cell data are available in GEO with accession number GSE176022. [000193] Results [000194] Global Gene Expression of NSCLC TIL [000195] For the present study, peripheral blood and tissue biospecimens were utilized, which were obtained from the first-in-human clinical trial of neoadjuvant anti-PD-1 (nivolumab) in resectable non-small cell lung cancer (NSCLC; NCT02259621; FIG.1A, top) ⁸ to study the transcriptional programs of MANA-specific TIL. Nine out of twenty patients (45%) treated in this trial had a major pathologic response (MPR) at the time of resection, defined as ≤10% viable tumor at the time of surgery; prior studies have established an association between MPR and improved overall survival ^9-12 . A schematic of the study design and experimental approach is shown in FIG.1A, bottom. In total, single-cell (sc) RNA-seq/TCR-seq was performed on TIL (n=15), paired adjacent normal lung (NL, n=12), tumor draining lymph nodes (TDLN, n=3), and a distant metastasis (FIG.5A, Tables 1-3). In total, 560,916 T-cells passed quality control (FIG. 1B and Table 3) and were carried forward for analyses. [000196] A uniform manifold approximation and projection (UMAP) of cells from all samples based on filtered and normalized transcript counts defined 15 T-cell clusters (FIGS.1B, 1C, 5B-5E). Expression of subset-defining markers and T-cell checkpoints were visualized in red-scale on the UMAP (FIG.1D). Both TRM-designated clusters had the highest expression of the canonical TRM genes, ZNF683 (HOBIT) and ITGAE (CD103), and the highest expression of a TRM gene-set ¹³ (FIG.5F). Principal component analysis (PCA) of samples based on concatenated cell cluster-level pseudo-bulk profiles distinguished adjacent NL T-cells from TIL (FIG.1E), but did not distinguish MPR from non-MPR (FIG.5F). Notable differentially- expressed gene programs were not observed between MPR and non-MPR TIL, indicating that gene expression profiling of total TIL has limited sensitivity in distinguishing pathologic response to PD-1 blockade. [000197] Expression Programs of MANA-specific TIL [000198] MANAFEST (Mutation Associated NeoAntigen Functional Expansion of Specific T-cells) ³ was performed on nine of the 16 patients on whom scRNA-seq/TCR-seq was conducted. This assay detects in vivo antigen-experienced T-cell responses and identifies the clonal identity of the T-cell receptor (TCR) corresponding to these cells. Of these nine, four were MPR and five were non-MPR (results from one patient were previously described ⁸ ). Putative MANA (Tables 4-6), peptide pools representing flu matrix and nucleoproteins, and a pool of MHC class I-restricted CMV, EBV, and flu epitopes (CEF) were queried for CD8 ⁺ T-cell reactivity in parallel (Tables 6 and 7). Among seven (three MPR and four non-MPR) of the nine patients, 72 total unique MANA-specific TCRs, 33 unique CEF-specific TCRs, and 52 unique flu-specific TCRs were identified (FIG.6, Tables 8, 9). Of the 33 CEF-specific TCRs, six of these matched known public EBV-specific TCRs and three matched known public flu-specific TCRs ¹⁴ . No CMV-reactive TCRs were mapped from our CEF-specific TCRs. Interestingly, 4 of the 41 MANA-specific TCRVβ CDR3 clonotypes identified in non-MPR patient MD01-004 (FIG.6) were specific for a MANA (MD01-004-MANA12) derived from a p53 R248L hotspot mutation, and were found at appreciable frequency in the pre- and post-treatment tumor (FIG. 7), despite the tumor not attaining MPR. Most MANA-specific clones were detected at very low frequency (median: 0.001%) in the peripheral blood across all available timepoints (FIGS.2A, 7). Overall, pathologic response was not associated with the prevalence, frequency, or intratumoral representation of MANA-specific T-cells (Table 9, FIGS.6, 7). In fact, more MANA-specific TIL were observed in non-MPR TIL than MPR TIL. No consistent pattern was observed for the frequency of viral T-cells in the tissue or peripheral blood (FIGS.6, 7). [000199] Ten MANA-specific clonotypes, for which the TCRα could be confidently identified from the single cell analysis, were selected for validation of MANA recognition via TCR cloning and introduction into a Jurkat/NFAT luciferase reporter system ¹⁵ .70% of tested clonotypes (representing 95.2% of total cells bearing MANAFEST-identified TCRs) were validated as MANA-specific (FIGS.8A-8C). Peptide-HLA binding assays demonstrated that two MANA peptides – MD01-005-MANA7 and MD01-004-MANA12 – displayed comparable high MHC class I affinity (measured KD=5.1nM and 17.5nM, respectively) and stability (FIGS. 8D, 8E). [000200] The transcriptional programming of MANA- and viral-specific CD8+ T-cells were next evaluated. Refined clustering of all CD8 ⁺ T-cells (n=235,851) identified 15 unique clusters (FIGS.2B, 9A). Clusters were named based on previously-defined T-cell states from single cell transcriptomic studies ¹⁶ . Six clusters had gene expression programs consistent with TRM T-cells, characterized by high expression of HOBIT, LINC02246, CD103, and a published TRM gene-set score (FIG.9B). Selective genes and linkage to the global CD3 T-cell clusters shown in FIGS.1A-1F were visualized (FIGS.9C, 9D). The six TRM subsets were heterogeneous in their expression of an exhaustion gene-set described previously in NSCLC ¹⁷ (FIG.9E). None of the most frequent tumor-infiltrating clonotypes were restricted to a single cluster (FIG.9F). Among all patients tested, a total of 28 MANA-specific CD8 clonotypes (1,350 total cells from 3 MPR and 3 non-MPR), as identified by MANAFEST, were detected in the single cell data, of which 20 clonotypes (890 cells) were in the tumor (FIG.2C, Table 8). Of the viral-specific T-cell clonotypes, 23 flu-specific (866 cells) and 2 EBV-specific (281 cells) clones were found in the CD8 single cell analysis. [000201] Overlay of these clonotypes onto the CD8 ⁺ T-cell UMAP demonstrated a striking distinction between the clonotypes with different antigen specificities (FIGS.2C and 10A-10C). EBV-reactive T-cells primarily resided in Teff clusters, whereas flu- and MANA-specific T-cells largely occupied distinct TRM clusters. Notably, since influenza is a respiratory virus, flu- specific T-cells may be considered the quintessential lung-resident memory T-cells ¹⁸ . None of the patients in this study were symptomatic for influenza in the 6 weeks preceding surgery. It is thus not surprising that flu-specific CD8 cells were TRM rather than T _eff . In contrast, EBV- specific T-cells exclusively occupied T _eff clusters, consistent with periodic acute stimulation upon latent EBV reactivation. While flu-specific cells were most numerous in normal lung, MANA-specific CD8 cells were more numerous in the tumor (FIG.10D, 10E). [000202] There was significant shared expression of selective cytotoxic T lymphocyte (CTL) activation genes between MANA- and EBV-specific T-cells, in particular genes encoding T-cell activation and CTL activity, such as HLA-DR, GZMH, IFNG, and NKG7 (FIG.2D). However, genes encoding certain canonical cytolytic molecules, such as GZMK, were lowly expressed in MANA-specific TIL. Most notably, EOMES, a transcription factor that is critical to CTL activity ¹⁹ , was present in EBV-specific CD8 cells but had minimal expression in most MANA-specific cells. Multiple checkpoints were significantly upregulated in MANA-specific TIL compared to EBV-specific TIL. Interestingly, MANA-specific cells expressed higher levels of PRDM1, which encodes Blimp-1 and has been reported to participate in coordinated transcriptional activation of multiple of these checkpoint genes, including PD-1, LAG3, TIGIT and HAVCR2 ²⁰ . TOX, a chromatin modifier important for exhaustion programs of chronic virus- specific and tumor-specific T-cells in murine models ^21,22 , was only marginally increased in MANA-specific cells, whereas its homolog, TOX2, which has also been reported to drive T-cell exhaustion ²³ , showed much greater upregulation in MANA-specific vs EBV-specific CD8 TIL. HOBIT, which is selectively upregulated in tissue resident memory T-cells ²⁴ , was also upregulated in MANA-specific TIL, even relative to flu-specific TRM (FIG.2E). Indeed, MANA-specific T-cells demonstrated the highest immune checkpoint and exhaustion signatures (FIG.10F) ¹⁷ . These findings demonstrate that MANA-specific CD8 T-cells in the tumor have an unconventional “hybrid” transcriptional program characterized by incomplete activation of effector programs and significant upregulation of checkpoint molecules such as PD-1, CTLA-4, TIM3, TIGIT, and CD39. In fact, each of these checkpoints was more highly expressed among MANA-specific CD8 cells than either flu- or EBV-specific CD8 cells, with CD39 being the most highly differentially expressed (FIGS.2D, 2E), congruent with flow cytometry findings of Simoni et. al. on MANA-specific lung cancer TIL ² . [000203] Flu-specific TRM were distinguished from MANA-specific TRM by low levels of both activation and effector CTL programs and had lower expression of multiple checkpoint molecules, but had the highest levels of genes encoding stem/memory molecules, such as TCF7 and IL7R (FIG.2F). Indeed, IL7R expression was 4.6-fold higher on flu-specific TIL relative to MANA-specific TIL. In TIL obtained from non-MPR MD01-004, culture with titrating concentrations of IL7 in vitro induced much higher levels of IL7R-regulated genes in flu-specific vs. MANA-specific TIL (FIGS.2G, 11A and 11B). Nonetheless, supraphysiologic levels of IL7 induced appreciable upregulation of IL7R-induced genes in MANA-specific TIL. Given the distinct transcriptional programs of the identified MANA-specific CD8 cells, it was hypothesized that other CD8 T-cells in the same TRM cluster showing differential expression relative to flu- specific T-cells (FIG.2G) may also recognize MANA that were not detected by the MANAFEST assay. Seven TCRs were cloned,, corresponding to CD8 ⁺ T-cells with highly differential gene expression relative to flu-specific T-cells. Each TCR was screened with a library of candidate MANA (Table 6) and confirmed MANA recognition in three of these TCRs, one TCR each from patients MD01-004, MD01-005, and MD043-011 (FIG.12A-12D). [000204] To next investigate the ligand-dependent TCR signaling capacity of antigen- specific T-cells, we performed a dose-response curve with cognate peptides matched to the ten total Jurkat-validated MANA-specific TCRα/β pairs (Table 10). Peptide dose-response curves of MPR-derived TCRs were comparable to EBV- and flu-specific TCRs, providing evidence that these TCRs were capable of strong ligand-dependent signaling (sometimes referred to as “functional avidity”). However, the peptide dose-response curves of TCRs derived from non- MPRs were markedly lower (~2 log10 leftward shift in peptide dose response curve) (FIGS.2H, 12E). Together, these data show that despite similar measured MANA-HLA binding affinities (FIGS.8C, 8D), TCR from expandable MANA-specific clones from the MPR patients had significantly higher functional avidity than MANA-specific clones from non-MPR patients. [000205] MANA-Specific TIL Programs Correlate with MPR [000206] To explore determinants of ICB sensitivity vs resistance, differences were examined in gene expression patterns between MPR vs non-MPR MANA-specific TIL. The neoadjuvant clinical trial format allowed for this distinction through pathological analysis of surgically resected tissue. In total, 45 MPR TIL transcriptomes were compared (39 from MD01- 005, 2 from MD043-003, and 4 from NY016-025) with 885 non-MPR TIL transcriptomes (782 from MD043-011, 62 from MD01-004, and 22 from NY016-014; Table 8 and FIGS.13A-13C). Highly significant differences between pathologic MPR vs. non-MPR tumors (FIG.3A). Significantly higher levels of genes associated with T-cell dysfunction such as TOX2, CTLA4, HAVCR2 and ENTPD1 were observed for non-MPR MANA-specific T-cells, whereas MPR MANA-specific T-cells had higher expression of genes associated with memory (IL7R/TCF7) and effector function (GZMK) (FIGS.3A-3C). Both the checkpoint score and exhaustion score were higher in MANA-specific TIL from non-MPR patients (FIGS.3D, 14A, 14B). Interestingly, CXCL13 is one of the genes most highly correlated with checkpoint-associated genes in non-MPR MANA-specific TIL, and was also found to be highly expressed in MANA- specific cells relative to virus-specific cells among CD8 TIL (FIGS.2D-2F). [000207] A number of genes encoding T-cell inhibitory molecules were more highly correlated with a composite immune checkpoint score of MANA-specific TIL from non-MPR vs MPR (FIGS.3E, 14C). In two non-MPRs (MD01-004 and MD043-011) and one MPR (MD01- 005), MANA-specific cells were also detected upon single cell profiling of CD8 T-cells from TDLN (FIGS.14D, 14E). Tracking the MANA-specific CD8 clonotypes from the primary tumor, those clones were detected among TIL from a brain metastasis resected from patient MD043-01124 months after primary tumor resection (FIG.14F). Relative to the primary tumor, even higher levels of three checkpoints – LAG3, TIGIT and HAVCR2 – were expressed on MANA-specific TIL in the metastasis (FIG.14G). [000208] Going back to overall TIL transcriptomic patterns, it was hypothesized that MANA-specific T-cells and/or a MANA-specific T-cell-like signature might correlate with response to ICB, even though total TIL single cell transcriptomic patterns did not (FIG.1E). Among CD8 TIL from 6 MPRs and 9 non-MPRs, the greatest correlation with pathologic response status was observed by combining four TIL clusters most highly enriched in MANA- specific cells, whereas the expression profile of total CD8 TIL did not distinguish MPR from non-MPR (FIGS.15A-15D). These data provide evidence that additional T-cells with this profile may contribute to the anti-tumor response. [000209] Systemic Reprogramming of MANA-Specific T-Cells [000210] scRNA-Seq/TCR-seq of serial peripheral blood T-cells from MPR patient MD01- 005 was performed after FACS-enriching for expression of the TCR-Vβ genes corresponding to this patient’s MANA-specific TCRs (FIGS.4A-4C, 16A). Nine of ten MANA-specific clones mapped to a TRM-like cluster (T _mem (3)), with some transcriptional features of TRM, such as expression of HOBIT) two weeks after initiation of anti-PD-1 treatment (FIG.4D). By four weeks (time of tumor resection), a significant diversification of phenotype was observed (p≤0.021, see Methods). Half of the MANA-specific cells were in T _eff clusters (FIG.4E). By 11 weeks (7 weeks after tumor resection), they were below limits of detection in the blood, consistent with known TRM patterns in the peripheral blood ²⁵ . Using RNA velocity, a clear bidirectional flow was observed among total peripheral blood CD8 cells of TRM-like memory MANA-specific T-cells in the Tmem(3) cluster toward either an activated effector (Teff(3)) or memory T-cell (Tmem(2)) transcriptional profile (FIG.4F). Genes associated with effector T-cell function and activation, T-cell homing and migration, and tissue retention were upregulated along the pseudotime from T _mem (3) to T _eff (3), whereas there was a decrease in genes associated with resting memory T-cells (FIGS.4G, 4H). Gene Ontology (GO) analysis revealed significant enrichment of an interferon-gamma-mediated signaling pathway along the differentiation trajectory (FIGS.16B-16F). While all these tissue compartments were only available for one MPR, these findings are consistent with our hypothesis that, upon activation, functional effector MANA-specific T-cells enter the blood and traffic into tissues, including normal lung, in search of micro-metastatic tumor ²⁶ and are compatible with a study by Behr et. al. showing that TRM cell plasticity can influence systemic memory T-cell responses ²⁷ . [000211] Discussion [000212] This is the first study to describe the transcriptional programming of MANA- specific TIL after ICB in lung cancer, and further, differential gene programs between patients whose tumors show major pathologic responses vs. those that do not. Via the MANAFEST platform, MANA-specific CD8 T-cells in peripheral blood were detected in the majority of patients treated with anti-PD-1; these were also found among TIL in roughly a third of patients. Detection of these T-cells was irrespective of tumor response, providing evidence that factors in the tumor microenvironment affecting T-cell function likely contribute to anti-tumor responsiveness. Indeed, the most frequent MANA-specific clonotype, representing 782 TIL, was observed in a non-MPR patient. Interestingly, this patient’s tumor had dual Kras and STK11 oncogenic mutations, which are known to be highly associated with non-response to PD-1 blockade ²⁸ . Consistent with a prior study ² , CD39 expression was a key gene that distinguished MANA-specific from viral-specific T-cells. Among MANA-specific CD8 TIL, roughly 90% were TRM with high expression of HOBIT, but also displayed a partial but incompletely activated Teff program, along with upregulation of several targetable checkpoints in non-MPR tumors. MANA-specific T-cells also express far less IL7R relative to flu TRM, translating functionally into poor IL7 responsiveness. These features may all contribute to their limited tumor-specific responsiveness in contrast to anti-viral responses. Future studies are warranted to assess the diminished functional capacity of MANA-specific T-cells that was suggested by the transcriptomic profiles observed in this study. [000213] One hypothesis for the lack of ICB response in some patients is that tumor- specific T-cells are poorly active due to poor avidity/affinity of their TCR for its cognate peptide:MHC. The finding herein, comparing ligand-induced TCR signaling of 3 MANA- specific TCRs from MPR TIL vs 7 from non-MPR patients support this notion. An overall limitation of these studies is the modest number of MANA-specific cells among TIL that were detected, representing 3 responders and 3 non-responders. Indeed, identification of MANA- specific cells is experimentally challenging, and only a few studies have successfully identified these cells in NSCLC ^2,3,8,29,30 , yet none of these profiled the transcriptome of MANA-specific T- cells at single cell resolution. Among the 930 MANA-specific transcriptomes we identified in TIL, there was high consistency among cells from each response group in highly differential expression of key genes known to regulate T-cell function. These findings inform on potential ICB combination therapies to overcome anti-PD-1 resistance that occurs even in the presence of potent MANA-specific T-cells. For example, the data herein, demonstrated reduced activation of transcriptional programs downstream of IL7 receptor ligation in MANA-specific TIL relative to flu-specific TIL, but that they still retain their ability to respond to supraphysiologic levels of IL7. Because IL7 signaling is requisite for maintenance of T-cell homeostasis and long-lived memory, it is conceivable that targeting the IL7 pathway could enhance ICB response. These findings thus provide a platform for follow-up studies to more rigorously test the generalizability of our conclusions in the setting of resectable and metastatic NSCLC. 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Nat Commun 9, 4483, doi:10.1038/s41467-018- 06804-y (2018).   OTHER EMBODIMENTS [0001] From the foregoing description, it will be apparent that variations and modifications may be made to the disclosure described herein to adopt it to various usages and conditions. Such embodiments are also within the scope of the following claims. [0002] All citations to sequences, patents and publications in this specification are herein incorporated by reference to the same extent as if each independent patent and publication was specifically and individually indicated to be incorporated by reference.