TITLE TREATMENT OF GLYCOLYSIS-LOW AND GLYCOLYSIS-HIGH TUMORS WITH CTLA-4 INHIBITORS CROSS-REFERENCE TO RELATED APPLICATIONS [0001] This application claims the benefit of U.S. Provisional Application No. 63/310,089, filed on 14 February 2023, which is incorporated herein by reference in its entirety. STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT [0002] This invention was made with Government support under grant nos. CA215136 and CA221810 awarded by National Institutes of Health. The government has certain rights in the invention. SEQUENCE LISTING [0003] The instant application contains a Sequence Listing, which has been submitted electronically in XML format and is hereby incorporated by reference in its entirety. The XML copy, created on 10 February 2023, is named MSKCC_058_WO1-SL and is 3,801 bytes in size. INCORPORATION BY REFERENCE [0004] For countries that permit incorporation by reference, all of the references cited in this disclosure are hereby incorporated by reference in their entireties. In addition, any manufacturers’ instructions or catalogues for any products cited or mentioned herein are incorporated by reference. Documents incorporated by reference into this text, or any teachings therein, can be used in the practice of the present invention. Documents incorporated by reference into this text are not admitted to be prior art. BACKGROUND [0005] Cellular energy metabolism reprogramming is a critical hallmark of cancer2. High glucose consumption and lactate production by tumor cells restrict nutrient availability in the tumor microenvironment for effector T cells, which also rely on glycolysis to proliferate and function. 3-5. Limiting the metabolic competition in the tumor microenvironment may increase the effectiveness of immunotherapy. [0006] Cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) is an immune co- inhibitory receptor that has been successfully exploited as a therapeutic target to promote and bolster immune responses against cancer. It is induced on T cells upon T-cell receptor (TCR) signaling activation, and is typically up-regulated during the initial stage of naïve T-cell activation, and competes with CD28 for the same ligands (CD86 and CD80) expressed on antigen presenting cells (APCs), thus limiting excessive T-cell priming (Fife and Bluestone, 2008; Pentcheva-Hoang et al., 2004). CTLA-4 is also constitutively expressed at high levels on regulatory T cells (Tregs), and constitutes one of their immunosuppressive mechanisms (Wing et al., 2008). The CTLA-4 immune checkpoint is particularly deregulated in tumor- bearing hosts, where chronic ineffective immune responses usually predominate and result in T-cell exhaustion and Treg induction (Wing et al., 2008). [0007] These observations provided the rationale for developing strategies to inhibit CTLA-4 as new cancer immunotherapy modalities (Leach et al., 1996). In fact, blockade of CTLA-4 immune checkpoint with specific antibodies (anti-CTLA-4) has now become a standard of care for metastatic melanoma (Hodi et al., 2010; Robert et al., 2015). However, despite these successes, immune checkpoint blockade still does not benefit a significant proportion of patients with metastatic cancer, which underscores the need to better understand the biologic activity of anti-CTLA-4 for its more precise utilization of as a therapy. SUMMARY OF THE INVENTION [0008] We investigated the impact of CTLA-4 blockade on the metabolic fitness of intra- tumor T cells in relationship to the tumor glycolytic capacity. We found that CTLA-4 blockade promotes immune cell infiltration and metabolic fitness especially in glycolysis-low tumors. [0009] Accordingly, one aspect of the invention relates to a method of treating a subject having a tumor that is susceptible to treatment by CTLA-4 blockade, the method comprising administering one or more CTLA-4 inhibitors to the subject, in which the tumor is susceptible to treatment by CTLA-4 blockade when the tumor is a glycolysis-low tumor. In some embodiments, the treatment by CTLA-4 blockade comprises treatment by one or more CTLA-4 inhibitors. [0010] An aspect of the invention relates to a method of treating a subject having a tumor that is susceptible to treatment by CTLA-4 blockade, the method comprising determining that the tumor is a glycolysis-low tumor, and administering one or more CTLA-4 inhibitors to the subject. In some embodiments, the treatment by CTLA-4 blockade comprises treatment by one or more CTLA-4 inhibitors. [0011] Another aspect of the invention relates to a method for treating a tumor in a subject, the method comprising determining that the tumor is a glycolysis-low tumor, and administering one or more CTLA-4 inhibitors to the subject. [0012] Yet another aspect of the invention relates to a method of treating a tumor in a subject, comprising determining that the subject has a tumor that is susceptible to treatment by CTLA-4 blockade, and administering one or more CTLA-4 inhibitors to the subject; in which a tumor is susceptible to treatment by CTLA-4 blockade when the tumor is a glycolysis-low tumor. [0013] A further aspect of the invention relates to a method of treating a tumor in a subject, comprising administering one or more CTLA-4 inhibitors to the subject, in which, prior to the administration of the one or more CTLA-4 inhibitors, the tumor is determined to be a glycolysis-low tumor. [0014] An aspect of the invention relates to a method of treating a tumor in a subject, comprising administering to the subject (i) one or more CTLA-4 inhibitors, and (ii) one or more inhibitors of tumor glycolysis. [0015] An additional aspect of the invention relates to a method of treating a tumor in a subject, comprising administering to the subject (i) one or more CTLA-4 inhibitors, and (ii) one or more inhibitors of tumor glycolysis, in which the tumor is a glycolysis-high tumor. [0016] A further aspect of the invention relates to a method of improving susceptibility of a glycolysis-high tumor to treatment by CTLA-4 blockade, the method comprising administering one or more inhibitors of tumor glycolysis with the treatment by CTLA-4 blockade. In some embodiments, the treatment by CTLA-4 blockade comprises treatment by one or more CTLA-4 inhibitors. [0017] Yet, another aspect of the invention relates to a method for treating a tumor in a subject, the method comprising determining that the tumor is a glycolysis-high tumor, and administering to the subject (i) one or more CTLA-4 inhibitors, and (ii) one or more inhibitors of tumor glycolysis. [0018] Another aspect of the invention relates to a method of treating a tumor in a subject, the method comprising administering to the subject one or more CTLA-4 inhibitors wherein the subject is susceptible to respond to treatment by a CTLA-4 inhibitor, or administering to the subject a CTLA-4 inhibitor and an inhibitor of tumor glycolysis wherein the patient is not susceptible to respond to treatment by a CTLA-4 inhibitor; wherein the subject is susceptible to respond to treatment by a CTLA-4 inhibitor when the tumor is a glycolysis-low tumor, and the subject is not susceptible to CTLA-4 inhibitor when the tumor is a glycolysis-high tumor. In some embodiments, the method may further comprise determining whether the tumor is a glycolysis-low tumor or a glycolysis-high tumor. [0019] Yet another aspect of the invention relates to a method for predicting a response to a CTLA-4 inhibitor treatment in a subject having a tumor and treating the subject with one or more CTLA-4 inhibitors, the method comprising: (a) determining the glycolysis status of the tumor; (b) classifying the subject as susceptible to respond to CTLA-4 inhibitor treatment wherein the tumor is a glycolysis-low tumor, or classifying the subject as not susceptible to respond to CTLA-4 inhibitor treatment wherein the tumor is a glycolysis-high tumor; and (c) administering to the subject one or more CTLA-4 inhibitors wherein the subject is susceptible to respond to treatment by a CTLA-4 inhibitor. Alternatively, the method comprises (a) determining the glycolysis status of the tumor; (b) classifying the subject as susceptible to respond to CTLA-4 inhibitor treatment wherein the tumor is a glycolysis-low tumor, or classifying the subject as not susceptible to respond to CTLA-4 inhibitor wherein the tumor is a glycolysis-high tumor; and (c) administering to the subject one or more CTLA-4 inhibitors wherein the subject is susceptible to respond to CTLA-4 inhibitor treatment, or administering to the subject one or more CTLA-4 inhibitors and one or more inhibitors of tumor glycolysis wherein the patient is not susceptible to respond to CTLA-4 inhibitor treatment. [0020] Moreover, an aspect of the invention relates to a method of determining that a patient has a tumor susceptible to treatment by CTLA-4 blockade, the method comprising obtaining a biological sample from the tumor, and detecting whether the tumor is a glycolysis-low tumor or a glycolysis-high tumor; in which the patient is determined to have a tumor susceptible to treatment by CTLA-4 blockade when the tumor is a glycolysis-low tumor, and the patient is determined to not have a tumor susceptible to treatment by CTLA-4 blockade when the tumor is a glycolysis-high tumor. [0021] A further aspect of the invention relates to a method of determining that a patient has a tumor susceptible to treatment by CTLA-4 blockade, the method comprising obtaining a biological sample from the tumor; detecting whether the tumor is a glycolysis-low tumor or a glycolysis-high tumor; and administering to the subject either (i) one or more CTLA-4 inhibitors when the tumor is a glycolysis-low tumor, or (ii) one or more CTLA-4 inhibitors and one or more inhibitors of tumor glycolysis when the tumor is a glycolysis-high tumor. [0022] Further provided is an ex vivo method for determining whether a subject with a tumor is susceptible to ICB therapy comprising a CTLA-4 inhibitor, the method comprising determining whether the tumor is a glycolysis-low tumor, wherein a glycolysis-low tumor indicates that the subject is susceptible to ICB therapy comprising a CTLA-4 inhibitor and wherein a glycolysis-high tumor indicates that the subject is resistant to ICB therapy comprising a CTLA-4 inhibitor. [0023] In addition, a method is provided for in vitro prediction of the probability of a subject having a tumor responding to ICB therapy comprising a CTLA-4 inhibitor, the method comprising: (a) determining the glycolysis status of the tumor; and (b) comparing the glycolysis status of the tumor determined in step (a) with a reference tumor glycolysis status obtained from subjects who have responded to ICB therapy comprising a CTLA-4; wherein, if the glycolysis status of the tumor determined in step (a) is the same as or lower than the reference tumor glycolysis status, it is predicted that the subject will respond to ICB therapy. [0024] In some embodiments, the method further comprises determining that the tumor is a glycolysis-low tumor, determining that the tumor is a glycolysis-high tumor, or determining the glycolysis status of the tumor. In some embodiments, such a determination comprises evaluating gene expression signature of glycolysis-related genes in a biological sample from the subject. In some embodiments, such a determination comprises evaluating protein expression signature of glycolysis-related proteins in a biological sample from the subject. In some embodiments, the biological sample comprises a sample obtain from the tumor or the tumor microenvironment. [0025] In some embodiments, the one or more CTLA-4 inhibitor, the CTLA-4 inhibitor, or the CTLA-4 blockade, comprises ipilimumab, tremelimumab, or a combination thereof. [0026] In some embodiments, the one or more inhibitors of tumor glycolysis is selected from a lactate dehydrogenase A (LDHA) inhibitor, mammalian target of rapamycin (mTOR) inhibitor, phosphoinositide 3-Kinase (PI3K) inhibitor, mitogen-activated protein kinase (MEK) inhibitor, Raf inhibitor, and glutamine blocker, and any combination thereof. [0027] In one aspect, the invention provides the use of the measurement of the tumor glycolysis level in vitro in a blood sample from a patient as a biomarker for success of ICB therapy in a subject with a tumor. BRIEF DESCRIPTION OF THE DRAWINGS [0028] FIG.1 presents results of tumor glycolysis and immune cell function as described in Example 1. Panel A shows quantification of glucose and lactate by ¹ H NMR in supernatants from 72 h cultures of activated T cells (100K, 100,000 cells), 4T1 cells (3K, 3,000 cells) and the two cell types together. Plots show combined results from 2 independent experiments (n=2/experiment; mean ± SD; 2-sided unpaired t test). Panel B shows percent of proliferating (CFSE ^low , top) and dead (bottom) CD4 ⁺ or CD8 ⁺ T cells assessed by flow cytometry upon 48 h activation in the presence of the indicated concentrations of lactic acid to define the workable lactate dose range (n=3/condition, except for 0 µM lactic acid, n=2; mean ± SD). Panels C and D show flow cytometry analysis of the indicated parameters in CD8 ⁺ and CD4 ⁺ T cells activated for 48 h in the presence or absence of 4T1 cells (Panel C) or 10 mM lactate (Panel D). Data show mean ± SD of 1 out of 2 independent experiments (n=3; mean ± SD; 2-sided unpaired t test). Panels E and F show expression of immune cell signatures by CIBERSORT (top) and glycolysis-related genes (bottom) in RNAseq data sets from human melanoma samples at baseline (Panel E, n=7) and after ipilimumab (Panel F, n=15). Each column in the heatmaps represents an independent tumor sample. MFI, median fluorescence intensity. [0029] FIG.2 presents results showing correlation between tumor glycolysis and immune cell infiltration upon CTLA-4 blockade, as described in Example 1. Heatmaps with identical color mapping setting showing indexes of Pearson correlation analyses between the indicated glycolysis-related genes and immune cell signatures by CIBERSORT in RNAseq data sets from Panel A human melanoma samples at baseline (top) and after treatment with ipilimumab (bottom), and from 4T1-Sc (Panel B) and 4T1-KD (Panel C) tumors treated with anti-CTLA-4 (bottom) or the isotype control (IgG, top). In Panel A, pre-ipilimumab, n=7; post-ipilimumab, n=15. In Panel B, IgG, n=4; anti-CTLA-4, n=5. In Panel C, n=5/treatment. SLC16A1 (MCT1) and LDHA are highlighted in blue. [0030] FIG.3 presents results of lactate dehydrogenase A- (LDHA)-deficient tumor model for neoadjuvant CTLA-4 blockade treatment, as described in Examples 1 and 2. Panel A shows expression of LDHA and vinculin, as loading control, in 4T1-KD and 4T1-Sc whole cell protein extracts by western blot in 1 representative of 3 independent experiments. Panel B shows glycolytic Proton Efflux Rate (glycoPER) assessed by Seahorse XF Analyzer in 4T1-KD and 4T1-Sc cultures (n=20, mean ± SD; 2-way ANOVA with Bonferroni correction; Rot/AA, rotenone + antimycin A; 2-DG, 2-Deoxy-D-glucose). Panel C shows in vivo growth of 4T1-KD and 4T1-Sc tumors orthotopically implanted in the mammary fat pad (mfp) of immunocompetent wild type (WT) and immunodeficient RAG2 knock out (KO) BALB/c mice (n=10 mice/group; mean ± SEM; 2-way ANOVA with Bonferroni correction; 1 representative of 2 independent experiments). Panel D shows growth of primary 4T1-Sc and 4T1-KD tumors in mice treated as in FIG.4, Panel A (left and middle, respectively) and average tumor diameter on the day of tumor resection (right) (IgG, n=9; anti-CTLA-4, n=12; mean ± SEM). Panel E shows LDHA activity in 4T1-Sc (n=4) and 4T1-KD (n=5) tumor extracts on the day of tumor resection after treatment as in Panel D (mean ± SEM; 2-sided unpaired t test). Panel F shows tumor growth after a second injection with 4T1-Sc in 4T1- KD- and 4T1-Sc-bearing mice that survived neoadjuvant treatment with CTLA-4 blockade as in FIG.4, Panel A (n=4/group, except for naïve, n=5; mean ± SEM; 2-way ANOVA with Bonferroni correction). aC, anti-CTLA-4. [0031] FIG.4 presents results of long-lasting responses to neoadjuvant anti-CTLA-4 in LDHA-KD-tumor-bearing mice, as described in Example 2. Panel A shows metastasis-free and overall survival in BALB/c mice implanted in the mammary fat pad (mfp) with 10 ⁶ 4T1- Sc or 4T1-KD cells and treated with 3 cycles of anti-CTLA-4 (9D9 IgG2b; n=12) or IgG control (n=9) before primary tumor surgical resection (1 representative of 3 independent experiments; log-rank test). Panel B shows tumor growth upon re-injection of 10 ⁶ 4T1-Sc or 4T1-KD cells in survivor mice in the anti-CTLA-4-treated 4T1-KD group ~100 days after surgery (n=4/group) in comparison with treatment-naïve mice (n=5) (mean ± SEM; 2-way ANOVA with Bonferroni’s correction). Panel C shows frequency and representative flow cytometry plots of circulating anti-tumor AH1-specific CD8 ⁺ T cells before (pre) and one week after (post) 4T1-Sc (left) or 4T1-KD (right) re-implantation in survivor mice upon neoadjuvant anti-CTLA-4 as in Panel B. Panel D shows frequency (left) and (right) memory phenotype (CD44 vs. CD62L expression) in circulating AH1-specific CD8 ⁺ T cells in survivor mice as in Panel B (n=4/group) or treatment-naïve mice (n=5/group) one week after injection with 4T1-Sc or 4T1-KD (mean ± SEM; 2-sided unpaired t test; n=1 experiment with the IgG2b 9D9 anti-CTLA-4; similar results were obtained with the IgG2a 9D9 antibody). Panel E shows quantification of tumor-infiltrating T cells by flow cytometry in the indicated treatment groups (n=5 mice/groups; mean ± SEM; 2-sided unpaired t test; 1 representative of 2 independent experiments). * = P<0.05; ** = P<0.01. aC, anti-CTLA-4; TM, tumor. Teff, effector CD4 ⁺ Foxp3- T cells. [0032] FIG.5 shows results of neoadjuvant anti-CTLA-4 treatment schedule for same- day 4T1-Sc- and 4T1-KD-tumor resection, as described in Example 2. Additional treatment schedule modified to harvest 4T1-Sc and 4T1-KD tumors for flow cytometry analysis on the same day. Separate groups of BALB/c mice were injected with 10 ⁶ 4T1-KD and 4T1-Sc cells 3 days apart and then treated with 3 cycles of anti-CTLA-4 or the matched isotype control (IgG) every 3 days (arrows, T=treatment) before surgery and flow cytometry analysis of tumor and tumor draining lymph node (DLN) samples. Panel A shows primary tumor growth and tumor weight on the day of surgery, showing similar tumor size across groups during treatment and on the day of surgery (n=5 mice/group; mean ± SEM; 1 representative of 2 independent experiments). Panel B shows overall survival of mice treated as in Panel A (n=5 mice/group; log rank test). Panel C frequency of the indicated T cell subsets among total CD45 ⁺ leukocytes in tumors and DLNs from the indicated treatment groups (n=5 mice/group except for 4T1-Sc IgG, n=4; mean ± SEM; 2-sided unpaired t test). Panel D shows frequency of CD11b ⁺ myeloid cell subsets among total CD45 ⁺ leukocytes, M1 and M2 macrophages according to MHC-II and CD206 staining among total CD11b ⁺ F4/80 ⁺ macrophages, and Gr1 ⁺ granulocyte subsets among total CD11b ⁺ myeloid cells in 4T1-Sc and 4T1-KD tumors as well as DLNs from mice treated as indicated (n=5 mice/group except for 4T1-Sc IgG, n=4; mean ± SEM; 2-sided unpaired t test). Representative plots showing the flow cytometry gating strategy for M1 and M2 macrophages and granulocytes (granulo) are reported. Data show results from 1 representative of at least 2 independent experiments. * = P<0.05. [0033] FIG.6 presents results of loss of Treg stability and CD8 ⁺ TIL activation in anti- CTLA-4-treated LDHA-KD tumors, as described in Examples 2 and 3. Panels A and B show tumor weight, frequency of IFN-γ ⁺ and TNF-α ⁺ among CD45 ⁺ CD4 ⁺ Foxp3 ⁺ Tregs (mean ± SEM; 2-sided unpaired t test) and Pearson correlation analyses between IFN-γ expression in tumor-infiltrating Tregs and CD8 ⁺ T cells in 2 independent experiments where 4T1-Sc and 4T1-KD tumors were resected Panel A or injected Panel B 3 days apart to equalize tumor size (n=5 mice/group except for 4T1-Sc IgG in Panel B, n=4). Panels C and D show low cytometry of Foxp3 (Panel C),CD25 and intracellular (not cross-blocked by the therapeutic antibody) CTLA-4 (Panel D) in tumor-infiltrating Tregs in the indicated treatment groups (4T1-Sc IgG, n=3; 4T1-Sc anti-CTLA-4, n=4; 4T1-KD, n=5/group; mean ± SEM; 2-sided unpaired t test; 1 representative of 2 independent experiments). Panel E shows representative gating strategy for CTLA-4 ^lo and CTLA-4 ^hi 4T1-KD-infiltrating Tregs and quantification and representative plots of the indicated cytokines in these Treg subsets from IgG- and anti-CTLA-4-treated 4T1-KD tumors by flow cytometry (n=5 mice/group, mean ± SEM; 2-sided paired t test; 1 representative of 2 independent experiments). Panel F-L show BALB/c mice were implanted in mfp with 10 ⁶ 4T1-KD cells in Matrigel with or without 50 mM sodium lactate (Na-Lac) and treated with anti-CTLA-4 as indicated Panel F. Quantification of CTLA-4 and CD25 (Panel G), IFN-γ (Panel H), and Foxp3 (Panel I) by flow cytometry in tumor-infiltrating Tregs, and tumor weight at the end of the experiment (Panel J) (anti-CTLA-4, n=10; anti-CTLA-4+Na-Lac, n=9; mean ± SEM from 1 representative of 3 independent experiments; 2-sided unpaired t test). Panel K shows Pearson correlation analyses between IFN-γ ⁺ Tregs and IFN-γ ⁺ CD8 ⁺ TILs normalized per gr of tumor (TM), and Panel L shows quantification of IFN-γ by flow cytometry in CD8 ⁺ TILs from mice as in Panel F-I. MFI, median fluorescence intensity. [0034] FIG.7 shows results of selective loss of Treg functional stability in LDHA- deficient tumors treated with CTLA-4 blockade. Panel A shows representative gating strategy for tumor-infiltrating CD8 ⁺ , CD4 ⁺ Foxp3- Teff and CD4 ⁺ Foxp3 ⁺ Tregs, where expression of IFN-γ and TNF-α was assessed. Panel B shows representative flow cytometry plots showing IFN-γ and TNF-α expression in Tregs, Teff and CD8 ⁺ TILs gated as in Panel A from 4T1-Sc- and 4T1-KD-bearing BALB/c mice treated as in FIG.6, Panel A. Panel C and D shows quantification of TNF-α and IFN-γ expression in CD4 ⁺ Foxp3- Teff and CD8 ⁺ TILs from 4T1-Sc- and 4T1-KD-bearing BALB/c mice treated as in FIG.6, Panels A (c; n=5 mice/group) and B (d; n=5 mice/group except for 4T1-Sc IgG, n=4) (mean ± SEM; 2- sided unpaired t test). Panel E shows quantification of IFN-γ and TNF-α expression in CD8 ⁺ T cells, CD4 ⁺ Foxp3- Teff and Tregs from DLNs of 4T1-Sc- and 4T1-KD-bearing BALB/c mice treated as in FIG.6, Panel B (n=5 mice/group except for 4T1-Sc IgG, n=4; mean ± SEM; 2-sided unpaired t test). Panel F shows quantification and representative plots of CTLA-4 expression by flow cytometry in CD8 ⁺ T cells, CD4 ⁺ Foxp3- Teff and Tregs from tumor and DLN samples of 4T1-Sc and 4T1-KD tumor-bearing mice (n=5 mice/group, mean ± SEM; 2-sided paired t test). Data show results from 1 representative of at least 2 independent experiments. [0035] FIG.8 shows results of in vivo Treg response to tumor glucose metabolism and CTLA-4 blockade, as described in Example 3. LDHA protein expression by western blot in 1 representative of 3 independent experiments (Panel A) and LDH activity in 4T1-KD vs. 4T1-EtBr cells in comparison with control 4T1-Sc cells (Panel B) (n=3, mean ± SD), and complete cell energetic map with mitochondrial and glycolytic production rates in the indicated 4T1 cell variants using a real-time ATP rate assay by Seahorse (Panel C) (Sc and EtBr, n=22; KD and A3-8KD, n= 24; mean ± SD) in 1 representative of 2 independent experiments (2-sided unpaired t test). Panels D-G show results in BALB/c mice (n=5/group) that were orthotopically implanted with 10 ⁶ 4T1-KD or 4T1-EtBr cells and tumors were surgically resected 13 days later (Panel D). Overall survival and number of surviving mice out of total are shown in Panel D. Frequency of Foxp3 ⁺ Tregs among tumor-infiltrating CD4 ⁺ T cells (Panel E), CD25 and CTLA-4 (Panel F) and IFN- γ expression (Panel G) in intra-tumor Tregs by flow cytometry are shown. Mean ± SEM; 2-sided unpaired t test; 1 representative of 2 independent experiments. Panel H shows schematic representation of anti-CTLA-4 or control IgG treatment in BALB/c mice implanted with 4T1-Sc and 4T1-KD in opposite mfp, and tumor weight on day 13 for samples analyzed in Panels I and J. Panel I shows GlucoseCy3 staining by flow cytometry in CD45- tumor cells gated as indicated to enrich in live CD45- tumor cells by comparing CD45 and DAPI staining between tumor and spleen samples from mice treated as in Panel H. Panel J shows GlucoseCy3 staining by flow cytometry in Tregs gated based on surface staining of CD4, CD25 and GITR in tumor samples as in Panel H. In Panels H-J, 4T1-Sc, n=4 (1 tumor sample in each treatment group was contaminated by DLN and was excluded); 4T1-KD, n=5; mean ± SEM; 2-sided unpaired t test; n=1 experiment. Panel K shows in vitro glucose consumption by B16-Sc vs. B16-KD cells, and Panel L and M show ex vivo glucose uptake potential by flow cytometry analysis of glucoseCy3 staining of CD45- tumor cells (Panel L) and intra-tumor Foxp3-GFP ⁺ Tregs (Panel M) from B16-Sc- and B16-KD-bearing Foxp3-GFP transgenic C57BL/6J mice treated with anti-CTLA-4 (n=3, mean ± SD; 2-sided unpaired t test; 1 representative of 2 independent experiments). [0036] FIG.9 shows results of Treg destabilization and CD8 ⁺ TIL activation in additional LDHA-deficient tumor models treated with CTLA-4 blockade, as described in Example 2. Panels A-E show primary tumor growth and overall survival, reporting the number of tumor-free mice at the end of the experiment, in BALB/c mice implanted in the mfp with the LDHA-KD 4T1 A3-8KD cell line (10 ⁶ cells/mouse) treated with neoadjuvant anti-CTLA-4 (n=9) or IgG control (n=10), as indicated. CTLA-4 and CD25 in tumor- infiltrating Tregs (Panel B), quantification of Tregs and CD8 ⁺ TILs as well as expression of the indicated markers by flow cytometry (Panel C), and flow cytometry analysis of IFN-γ expression (Panel D) in CTLA-4 ^lo and CTLA-4 ^hi tumor-infiltrating Tregs from mice treated as in Panel A (mean ± SEM; CTLA-4 ^lo vs. CTLA-4 ^hi Tregs, 2-sided paired t test; IgG vs. anti-CTLA-4 CTLA-4 ^lo Tregs, 2-sided unpaired t test). Panel E shows Pearson correlation analyses of indicated parameters in Tregs and CD8 ⁺ TILs from mice treated as in Panel A (open circle, IgG; open circle with X, anti-CTLA-4). n=1 experiment with n=9-10 mice/group. Panel F-J show 4T1-KD-bearing BALB/c mice were treated with the standard IgG2b 9D9 anti-CTLA-4 antibody (n=10) or its IgG2a variant (n=9) or IgG control (n=10) as indicated in Panel F and overall survival (log-rank test) (Panel G), quantification of CTLA-4 and GITR expression in Tregs (Panel H), and tumor-infiltrating Tregs and their expression of Foxp3 and IFN-γ by flow cytometry (Panel I) are shown (mean ± SEM; 2-sided unpaired t test). Panel J shows Pearson correlation analyses between indicated parameters in Tregs and CD8 ⁺ TILs from mice treated as in Panel F. n=1 experiment with 9D9 IgG2a. Panels K-M show LDHA protein expression by western blot (Panel K), LDH activity (Panel L), and glycolytic proton efflux rate (GlycoPER) by Seahorse analysis in B16-KD vs. B16-Sc cells (Panel M) (n=3, mean ± SD; 2-sided unpaired t test; 1 representative of 2-3 independent experiments). Panels N-P show C57BL/6J mice were implanted with B16-KD and B16-Sc tumors and treated with anti-CTLA-4 or IgG control as indicated in Panel N. Quantification of CTLA-4 and CD25 (Panel O; n=5/group except for B16-KD IgG, n=4) and IFN-γ expression in tumor-infiltrating Tregs by flow cytometry (Panel P;B16-Sc IgG, n=4; B16-Sc anti-CTLA-4, n=6; B16-KD IgG, n=4; B16-KD anti-CTLA-4, n=3; mean ± SEM; 2-sided unpaired t test; 1 representative of 2 experiments). TM, tumor; GzmB, granzyme B; i.d., intradermal. [0037] FIG.10 shows results of ex vivo and in vitro Treg response to tumor glucose metabolism and CTLA-4 blockade, as described in Examples 3 and 4. Panel A and B show Foxp3-GFP transgenic (Tg) mice were implanted with B16-Sc or B16-KD cells and treated with anti-CTLA-4 as indicated in Panel A and tumor-infiltrating Foxp3-GFP ⁺ Tregs were FACS-sorted and tested in ex vivo suppression assays with CellTrace Violet (CTV)-labeled CD8 ⁺ T cells activated with anti-CD3 in the presence of 0.5 or 10 mM glucose (Panel B). Panel B shows flow cytometry of CD44 and CD25 expression in CD8 ⁺ T cells cultured with B16-Sc- vs. B16-KD-derived Tregs (top) and quantification of proliferation (CTV dilution by CTV MFI) of dividing CTV ^lo CD8 ⁺ T cells and Treg suppression of CD8 ⁺ T-cell proliferation in the same culture conditions (bottom) (n=3, mean ± SD; 2-sided unpaired t test; 1 representative of 2 independent experiments). Panel C shows quantification by flow cytometry of IFN-γ and TNF-α expression in Tregs co-cultured with 4T1-Sc or 4T1-KD cells in 5 mM glucose RPMI1640 for 24 h in the presence of soluble anti-CD3, IL-2 and anti- CTLA-4 (n=3, mean ± SD; 2-sided unpaired t test; n=1 experiment). Panel D shows glucose consumption and lactate production by NMuMg benign mammary gland cell line vs.4T1 cells (n=6, mean ± SD; 2-sided unpaired t test; n=1 experiment with NMuMg). Panel E shows quantification by flow cytometry of IFN-γ and TNF-α expression in Tregs cultured for 48 h with 4T1-Sc, 4T1-KD- or NMuMg-conditioned media (11 mM glucose complete RPMI1640) in the presence of plate-bound anti-CD3, IL-2 and anti-CTLA-4 or an IgG control (n=3, mean ± SD; 2-sided unpaired t test; n=1 experiment). * = P<0.05; ** = P<0.01; *** = P<0.001. [0038] FIG.11 shows results of glucose-dependent loss of Treg functional stability induced by CTLA-4 blockade, as described in Example 4. Panel A shows flow cytometry representative plot (left) and (right) quantification of 2-NBDG staining on 4T1-KD and 4T1- Sc cells in 2 independent experiments (Rel MFI, relative MFI: 2-NBDG MFI of stained samples relative to matched unstained control; n=2). Panel B shows glucose consumption by 4T1-KD vs.4T1-Sc cells cultured in hypoxia (n=3; 1 representative of 2 independent experiments). Panel C shows flow cytometry representative plot (left) and (right) quantification of glucoseCy3 staining on Tregs treated with anti-CTLA-4 or IgG control in 11 mM glucose (n=2; 1 representative of 2 independent experiments). Panel D shows quantification of IFN-γ by Luminex-based bead immunoassay in supernatants from Treg cultures as in Panel C. Panels E-G show in vitro suppression assays with increasing glucose concentrations and anti-CTLA-4 or IgG control. Panel F shows percent Treg suppression of CD8 ⁺ T-cell proliferation relative to proliferation of CD8 ⁺ T cells cultured alone in the same treatment conditions (n=3; 1 representative of 3 independent experiments). Panel G shows the percentage of CD86-expressing B cells from cultures as in Panels F and G. Panels H-J show in vitro suppression assays with increasing glucose concentrations and anti-CD28 or IgG control. Panel I shows percent Treg suppression of CD8 ⁺ T-cell proliferation relative to proliferation of CD8 ⁺ T cells cultured alone in the same treatment conditions (n=3; 1 representative of 3 independent experiments). Panel J shows the percentage of CD86- expressing B cells from cultures as in Panels H and I. For Panels A-J, mean ± SD; 2-sided unpaired t test. Panel K shows model of loss of Treg functional stability according to glucose availability and CTLA-4 blockade. Under glucose restriction, such as in 4T1-Sc tumors, anti-CTLA-4 has limited activity against Treg-mediated immunosuppression of Teff (left). When competition for glucose is diminished, T cells better infiltrate the tumor and anti-CTLA-4 promotes Treg glucose metabolism via CD28 co-stimulation, leading to Treg functional destabilization and increased Teff activation (right). [0039] FIG.12 shows that results of loss of Treg functional stability induced by anti- CTLA-4 depends on Treg glycolysis and CD28 signaling, as described in Example 4. Panel A shows quantification and representative plots of GlucoseCy3 staining by flow cytometry of Tregs activated as in FIG.11, Panel C in the presence of 10 mM glucose ± rotenone/antimycin A (Rot/AA) or oligomycin (Oligo) and treated with anti-CTLA-4 or IgG control (average of 2 biological replicates/condition; 1 representative of 2 independent experiments). Panel B shows Foxp3 expression by flow cytometry and IL-10 production by Luminex-based bead immunoassay in Tregs activated in the presence of 10 mM glucose ± Rot/AA or Oligo (n=3, mean ± SD; 2-sided unpaired t test; 1 representative of 3 independent experiments). Panels C and D show representative plots of in vitro assays reported in FIG. 11, Panels F and G. Representative proliferation (CellTraceViolet dilution) by flow cytometry of activated CD8 ⁺ T cells cultured alone or in the presence of Tregs at the indicated glucose concentrations and treated with anti-CTLA-4 or an IgG control (Panel C). Panel D shows representative CD86 staining by flow cytometry on B cells from co-cultures with CD8 ⁺ T cells and Tregs treated as in Panel C. Panel E shows in vitro suppression assay with CD25 ^hi Tregs immunomagnetically purified from spleens of naïve WT or CD28 KO mice cultured for 48 h with CellTraceViolet-labeled CD8 ⁺ T cells and B cells and activated with anti-CD3 in the presence of anti-CTLA-4 or IgG control and the indicated glucose concentrations (n=3/conditions except for “+CD28 KO Tregs” at 1-10 mM glucose, n=2; mean ± SD; 2-sided unpaired t test; 1 representative of 2 independent experiments). [0040] FIG.13 shows results of CD28 agonism and CTLA-4 blockade, but not PD-1 blockade, drive loss of Treg functional stability. Panels A and B shows representative flow cytometry plots of in vitro assays reported in FIG.11, Panels I and J. Representative proliferation (CellTraceViolet dilution) by flow cytometry of activated CD8 ⁺ T cells cultured alone or in the presence of Tregs at the indicated glucose concentrations and treated with anti-CD28 (2 µg/ml) or IgG control (Panel A). Panel B shows representative CD86 staining by flow cytometry on B cells from co-cultures with CD8 ⁺ T cells and Tregs treated as in Panel A. Panel C shows proliferation of CD8 ⁺ T cells cultured alone or with Tregs in 0.5 mM (gray) or 10 mM glucose (black) and activated with increasing concentrations of anti- CD28 (0-0.2 µg/ml) from 1 of 2 independent experiments (n=3, mean ± SD; 2-sided unpaired t test). Panel D shows quantification and representative plots showing suppression of CD4 ⁺ T-cell proliferation (left) and CD86 expression on B cells (right) by flow cytometry in culture with Tregs treated with anti-CTLA-4, anti-PD-1 or an IgG control in complete RPMI1640 containing 11 mM glucose. Percent suppression was calculated relative to proliferation of CD4 ⁺ T cells cultured alone in the same treatment conditions (n=3; mean ± SD; 2-sided unpaired t test; n=1 experiment with anti-PD-1). Panel E shows suppression of proliferation of CD8 ⁺ T cells cultured at the indicated ratios with Foxp3-GFP ⁺ PD-1 ⁺ Tregs (top) or Foxp3- GFP ⁺ PD-1- Tregs (bottom) FACS-sorted from spleens of naïve Foxp3-GFP mice and incubated with anti-PD-1 or IgG control for 48 h (representative results from 1 experiment conducted with CD8 ⁺ and CD4 ⁺ as target T cells with similar results). Panel F shows quantification and representative plots of GlucoseCy3 staining by flow cytometry in Tregs activated as in FIG.11, Panel C and treated with anti-PD-1 or IgG control (n=3, mean ± SD; 1 representative of 2 independent experiments). Panel G shows flow cytometry quantification and phenotypic analysis of Tregs from 4T1-KD tumors treated with anti- CTLA-4, anti-PD-1 or IgG control as indicated (n=10 mice/group, mean ± SEM; 2-sided unpaired t test; 1 representative of 2 independent experiments). ** = P<0.01; *** = P<0.001. [0041] FIG.14 shows results of limiting Treg glucose metabolism prevents anti-CTLA- 4-mediated Treg destabilization in glycolysis-defective tumors, as described in Example 5. Panel A shows Foxp3 ^GFP-Cre-ERT2 ;Slc2a1(Glut1) ^fl/fl (cKO) and Foxp3 ^GFP-Cre-ERT2 control mice (ctrl) were implanted with B16-KD cells and treated with anti-CTLA-4 or IgG after induction of Glut1 deletion with tamoxifen as indicated. Tamoxifen treatment was continued throughout the treatment duration. Panel B shows Slc2a1(Glut1) mRNA quantification relative to beta actin in Foxp3-GFP- Teff and Foxp3-GFP ⁺ Tregs from the spleens of ctrl and Glut1 cKO mice at the end of treatment as in Panel A (n=3; mean ± SD, 2-sided unpaired t test). Panels C and D show flow cytometry analysis of CD25 and CTLA-4 (Panel C; n=3 except for ctrl IgG, n=1), and IFN- γ and TNF- α expression (Panel D; n=2) in tumor- infiltrating Tregs from mice treated as in Panel A (mean ± SEM; 2-sided unpaired t test; 1 representative of 2 independent experiments). Panel E shows ex vivo suppression assay with Tregs sorted from the spleens of ctrl and Glut1 cKO mice treated with anti-CTLA-4 as in Panel A. Treg suppression of CD8 ⁺ T-cell expansion after 48 h co-culture in 10 mM glucose and representative flow cytometry plot showing CTV proliferation and generation (G) overlay of CD8 ⁺ T cells cultured alone (gray) or in the presence of ctrl (black) or Glut1 cKO (dashed) Tregs (n=3; mean ± SD; 2-sided unpaired t test; 1 representative of 2 independent experiments). Panels F-L show Foxp3 ^YFP-Cre ;Slc2a1(Glu1) ^fl/+ (Glut1 HET) or Foxp3 ^{YFP- Cre} ;Ldha ^fl/fl (Ldha cKO) and Foxp3 ^YFP-Cre mice (ctrl) were implanted with B16-KD cells and treated with anti-CTLA-4 (Panel F). Panel G shows Slc2a1(Glut1) mRNA quantification relative to beta actin in Foxp3-GFP ⁺ Tregs from spleens of ctrl and Glut1 HET mice (n=2; mean ± SD). Panels H and I show quantification by flow cytometry of intra-tumor Tregs (Panel H) and their expression of Ki67 (Panel I) in ctrl and Glut1 HET mice treated as in (f) (ctrl, n=4; HET, n=2; mean ± SEM; 2-sided unpaired t test; 1 representative of 2 independent experiments with mice carrying Glut1 HET or cKO Tregs). Panel J shows Ldha mRNA quantification relative to beta actin in Foxp3-GFP ⁺ Tregs from spleens of ctrl and Ldha cKO mice (n=3; mean ± SD; 2-sided unpaired t test). Panel K and L show quantification by flow cytometry of intra-tumor Tregs (Panel K) and their expression of Ki67 (Panel L) in ctrl or Ldha cKO mice treated as in Panel F (ctrl, n=3; Ldha cKO, n=2; mean ± SEM, 2-sided unpaired t test; 1 representative of 2 independent experiments). Panel M shows schematic representation of the culture conditions used in Panels N and O. CD5 ⁺ T cells from Ldha cKO or ctrl mice were co-cultured for 48 h with CD45.1 ⁺ congenic APCs (either B cells or T- cell depleted splenocytes) as scaffold for soluble anti-CD3 crosslinking in low (0.5 mM) or higher (10 mM) glucose concentrations as indicated. Panel N shows quantification by flow cytometry of Ldha cKO or ctrl Foxp3 ⁺ CD4 ⁺ Tregs and their expression of Ki67 after activation as in Panel M. Panel O shows Foxp3 and CTLA-4 expression by flow cytometry (MFI) in Ki67-negative Ldha cKO or ctrl Tregs from cultures as in Panel M. Ctrl 0.5 mM glucose, n=3 except for anti-CD28, n=2; ctrl 10 mM glucose, n=3; cKO, n=4; mean ± SD, 2- sided unpaired t test; 1 representative of 2 independent experiments. ** = P<0.01; *** = P<0.001. aCTLA-4, anti-CTLA-4; aCD28, anti-CD28. DETAILED DESCRIPTION OF THE INVENTION [0042] Unless defined otherwise, all 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 is related. For example, The Dictionary of Cell and Molecular Biology (5th ed. J.M. Lackie ed., 2013), the Oxford Dictionary of Biochemistry and Molecular Biology (2d ed. R. Cammack et al. eds., 2008), and The Concise Dictionary of Biomedicine and Molecular Biology (2d ed. P-S. Juo, 2002) can provide one of skill with general definitions of some terms used herein. Definitions [0043] As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents, unless the context clearly dictates otherwise. The terms “a” (or “an”) as well as the terms “one or more” and “at least one” can be used interchangeably. [0044] Furthermore, “and/or” is to be taken as specific disclosure of each of the two specified features or components with or without the other. Thus, the term “and/or” as used in a phrase such as “A and/or B” is intended to include A and B, A or B, A (alone), and B (alone). Likewise, the term “and/or” as used in a phrase such as “A, B, and/or C” is intended to include A, B, and C; A, B, or C; A or B; A or C; B or C; A and B; A and C; B and C; A (alone); B (alone); and C (alone). [0045] Units, prefixes, and symbols are denoted in their Système International de Unites (SI) accepted form. Numeric ranges are inclusive of the numbers defining the range, and any individual value provided herein can serve as an endpoint for a range that includes other individual values provided herein. For example, a set of values such as 1, 2, 3, 8, 9, and 10 is also a disclosure of a range of numbers from 1-10. Where a numeric term is preceded by “about,” the term includes the stated number and values ±10% of the stated number. The headings provided herein are not limitations of the various aspects or embodiments of the invention, which can be had by reference to the specification as a whole. Accordingly, the terms defined immediately below are more fully defined by reference to the specification in its entirety. [0046] Amino acids are referred to herein by their commonly known three-letter symbols or by the one-letter symbols recommended by the IUPAC-IUB Biochemical Nomenclature Commission. Nucleotides, likewise, are referred to by their commonly accepted single-letter codes. Unless otherwise indicated, amino acid sequences are written left to right in amino to carboxy orientation, and nucleic acid sequences are written left to right in 5’ to 3’ orientation. [0047] Wherever embodiments are described with the language “comprising,” otherwise analogous embodiments described in terms of “consisting of” and/or “consisting essentially of” are included. [0048] The term “immune checkpoint blockade” or “ICB,” as used herein, refers to the administration of one or more inhibitors of one or more immune checkpoint proteins or their ligand(s). Immune checkpoint proteins include, but are not limited to, cytotoxic T lymphocyte-associated antigen 4 (CTLA-4), also known as CD152, programmed cell death protein 1 (PD-1), also known as CD279, lymphocyte-activation gene 3 (LAG-3), also known as CD223, and T cell immunoglobulin mucin (TIM-3), also known as HAVcr2. [0049] An “active agent” is an agent which itself has biological activity, or which is a precursor or prodrug that is converted in the body to an agent having biological activity. Active agents useful in the methods of the invention include inhibitors of immune checkpoint proteins or their ligand(s), for example, CTLA-4 inhibitors (including antibodies to CTLA-4 that inhibit its function). [0050] The terms “inhibit,” “block,” and “suppress” are used interchangeably and refer to any statistically significant decrease in biological activity, including full blocking of the activity. An “inhibitor” is an active agent that inhibits, blocks, or suppresses biological activity in vitro or in vivo. Inhibitors include but are not limited to small molecule compounds; nucleic acids, such as siRNA and shRNA; polypeptides, such as antibodies or antigen-binding fragments thereof, dominant-negative polypeptides, and inhibitory peptides; and oligonucleotide or peptide aptamers. [0051] Terms such as “treating” or “treatment” or “to treat” or “alleviating” or “to alleviate” refer to therapeutic measures that cure, slow down, lessen symptoms of, and/or halt progression of a diagnosed pathologic condition or disorder. Thus, those in need of treatment include those already with the disorder. In certain embodiments, a subject is successfully “treated” for a disease or disorder according to the methods provided herein if the patient shows, e.g., total, partial, or transient alleviation or elimination of symptoms associated with the disease or disorder. [0052] “Prevent” or “prevention” refers to prophylactic or preventative measures that prevent and/or slow the development of a targeted pathologic condition or disorder. Thus, those in need of prevention include those at risk of or susceptible to developing the disorder. In certain embodiments, a disease or disorder is successfully prevented according to the methods provided herein if the patient develops, transiently or permanently, e.g., fewer or less severe symptoms associated with the disease or disorder, or a later onset of symptoms associated with the disease or disorder, than a patient who has not been subject to the methods of the invention. [0053] By “subject” or “individual” or “patient” is meant to be any subject, preferably a mammalian subject, for whom diagnosis, prognosis, or therapy is desired. Mammalian subjects include humans, domestic animals, farm animals, sports animals, and zoo animals including, e.g., humans, non-human primates, dogs, cats, guinea pigs, rabbits, rats, mice, horses, cattle, and so on. [0054] A “CTLA-4 inhibitor”, “inhibitor of CTLA-4”, or the like, refers to an active agent that antagonizes the activity of cytotoxic T lymphocyte-associated antigen 4 or reduces its production in a cell. [0055] An “inhibitor of tumor glycolysis”, “tumor glycolysis inhibitor”, or the like, refers to an active agent that antagonizes the activity of glycolysis. [0056] The “glycolysis status”, for example, of a tumor or tumor microenvironment, refers to whether the tumor or tumor microenvironment is glycolysis-low or glycolysis-high. [0057] An “effective amount” of a composition as disclosed herein is an amount sufficient to carry out a specifically stated purpose. An “effective amount” can be determined empirically and in a routine manner, in relation to the stated purpose, route of administration, and dosage form. [0058] A “biological sample” may be any fluid or tissue sample obtained from the subject. A biological sample may be a blood product, such as plasma, serum and the like; or a urine sample, saliva sample, cerebrospinal fluid (CSF) sample, sweat sample, or tear sample. In some embodiments, the biological sample may be a sample from the tumor microenvironment, for example, blood, cells, and/or extracellular matrix. In some embodiments, the biological sample may be a cell or tissue sample of the tumor. [0059] As used herein, the term “molecular signature” is used consistently with its conventional meaning in the art, and refers to an expression profile of a group of genes or proteins that is characteristic of a certain cell type, a certain cell population, a certain biological phenotype, or a certain medical condition. [0060] As used herein, the term “gene expression signature” is used consistently with its conventional meaning in the art, and refers to an expression profile of a group of genes that is characteristic of a certain cell type, a certain cell population, a certain biological phenotype, or a certain medical condition. By way of example, when the term “gene expression signature” is used in relation to glycolysis, it refers to an expression profile of a group of genes that is characteristic of glycolysis. Gene expression signatures can be determined using any suitable method known in the art for determining the expression of a gene, including, but not limited to, those that detect and/or measure gene expression at the mRNA level or the protein level, such as RT-PCR-based methods. [0061] As used herein, the term “protein expression signature” is used consistently with its conventional meaning in the art, and refers to an expression profile of a group of proteins that is characteristic of a certain cell type, a certain cell population, a certain biological phenotype, or a certain medical condition. By way of example, when the term “protein expression signature” is used in relation to glycolysis, it refers to an expression profile of a group of proteins that is characteristic of glycolysis. Protein expression signatures can be determined using any suitable method known in the art for determining the expression of a protein. [0062] As used herein, “tumor microenvironment” refers to the environment around a tumor, including one or more or all of the surrounding blood vessels, immune cells, fibroblasts, signaling molecules and the extracellular matrix. Methods of the Invention [0063] We investigated the impact of CTLA-4 blockade on the metabolic fitness of intra- tumor T cells in relationship to the tumor glycolytic capacity. We found that CTLA-4 blockade promotes immune cell infiltration and metabolic fitness especially in glycolysis-low tumors. [0064] Thus, in some aspects, the invention relates to a method of treating a subject having a tumor that is susceptible to treatment by CTLA-4 blockade. The method may comprise administering one or more CTLA-4 inhibitors to the subject, in which the tumor is susceptible to treatment by CTLA-4 blockade when the tumor is a glycolysis-low tumor. Alternatively, the method may comprise determining that the tumor is a glycolysis-low tumor, and administering one or more CTLA-4 inhibitors to the subject. In some embodiments, the treatment by CTLA-4 blockade comprises treatment by one or more CTLA-4 inhibitors. [0065] In other aspects, the invention relates to a method for treating a tumor in a subject. The method may comprise determining that the tumor is a glycolysis-low tumor, and administering one or more CTLA-4 inhibitors to the subject. Or, the method may comprise determining that the subject has a tumor that is susceptible to treatment by CTLA-4 blockade, and administering one or more CTLA-4 inhibitors to the subject, in which a tumor is susceptible to treatment by CTLA-4 blockade when the tumor is a glycolysis-low tumor. Alternatively, the method may comprise administering one or more CTLA-4 inhibitors to the subject, in which, prior to the administration of the one or more CTLA-4 inhibitors, the tumor is determined to be a glycolysis-low tumor. [0066] In yet other aspects, the invention relates to a method of treating a tumor in a subject comprising administering to the subject (i) one or more CTLA-4 inhibitors, and (ii) one or more inhibitors of tumor glycolysis. In some embodiments, the tumor is a glycolysis- high tumor. [0067] In other aspects, the invention relates to a method of improving susceptibility of a glycolysis-high tumor to treatment by CTLA-4 blockade. The method may comprise administering one or more inhibitors of tumor glycolysis with the treatment by CTLA-4 blockade. In some embodiments, the treatment by CTLA-4 blockade comprises treatment by one or more CTLA-4 inhibitors. [0068] In other aspects, the invention relates to a method for treating a tumor in a subject, in which the method comprises determining that the tumor is a glycolysis-high tumor, and administering to the subject (i) one or more CTLA-4 inhibitors, and (ii) one or more inhibitors of tumor glycolysis. [0069] In further aspects, the invention relates to a method of treating a tumor in a subject, in which the method comprises either administering to the subject one or more CTLA-4 inhibitors wherein the subject is susceptible to respond to treatment by a CTLA-4 inhibitor, or administering to the subject one or more CTLA-4 inhibitors and one or more inhibitors of tumor glycolysis wherein the patient is not susceptible to respond to treatment by a CTLA-4 inhibitor. The subject is susceptible to respond to treatment by a CTLA-4 inhibitor when the tumor is a glycolysis-low tumor, and the subject is not susceptible to CTLA-4 inhibitor when the tumor is a glycolysis-high tumor. [0070] In yet other aspects, the invention relates to a method for predicting a response to a CTLA-4 inhibitor treatment in a subject having a tumor and treating the subject with one or more CTLA-4 inhibitors. The method may comprise (a) determining the glycolysis status of the tumor; (b) classifying the subject as susceptible to respond to CTLA-4 inhibitor treatment wherein the tumor is a glycolysis-low tumor, or classifying the subject as not susceptible to respond to CTLA-4 inhibitor treatment wherein the tumor is a glycolysis-high tumor; and (c) administering to the subject one or more CTLA-4 inhibitors wherein the subject is susceptible to respond to treatment by a CTLA-4 inhibitor. Alternatively, the method may comprise (a) determining the glycolysis status of the tumor; (b) classifying the subject as susceptible to respond to CTLA-4 inhibitor treatment wherein the tumor is a glycolysis-low tumor, or classifying the subject as not susceptible to respond to CTLA-4 inhibitor wherein the tumor is a glycolysis-high tumor; and (c) administering to the subject one or more CTLA-4 inhibitors wherein the subject is susceptible to respond to CTLA-4 inhibitor treatment, or administering to the subject one or more CTLA-4 inhibitors and one or more inhibitors of tumor glycolysis wherein the patient is not susceptible to respond to CTLA-4 inhibitor treatment. [0071] Moreover, in other aspects, the invention relates to a method of determining that a patient has a tumor susceptible to treatment by CTLA-4 blockade. The method may comprise obtaining a biological sample from the tumor, and detecting whether the tumor is a glycolysis-low tumor or a glycolysis-high tumor; in which the patient is determined to have a tumor susceptible to treatment by CTLA-4 blockade when the tumor is a glycolysis-low tumor, and the patient is determined to not have a tumor susceptible to treatment by CTLA-4 blockade when the tumor is a glycolysis-high tumor. Alternatively, the method may comprise obtaining a biological sample from the tumor; detecting whether the tumor is a glycolysis-low tumor or a glycolysis-high tumor; and administering to the subject either (i) one or more CTLA-4 inhibitors when the tumor is a glycolysis-low tumor, or (ii) one or more CTLA-4 inhibitors and one or more inhibitors of tumor glycolysis when the tumor is a glycolysis-high tumor. [0072] Further provided is an ex vivo method for determining whether a subject with a tumor is susceptible to ICB therapy comprising a CTLA-4 inhibitor. The method comprises determining whether the tumor is a glycolysis-low tumor, wherein a glycolysis-low tumor indicates that the subject is susceptible to ICB therapy comprising a CTLA-4 inhibitor and wherein a glycolysis-high tumor indicates that the subject is resistant to ICB therapy comprising a CTLA-4 inhibitor. [0073] In addition, a method is provided for in vitro prediction of the probability of a subject having a tumor responding to ICB therapy comprising a CTLA-4 inhibitor. The method comprises (a) determining the glycolysis status of the tumor; and (b) comparing the glycolysis status of the tumor determined in step (a) with a reference tumor glycolysis status obtained from subjects who have responded to ICB therapy comprising a CTLA-4. If the glycolysis status of the tumor determined in step (a) is the same as or lower than the reference tumor glycolysis status, it is predicted that the subject will respond to ICB therapy comprising CTLA-4. [0074] In yet other aspects, the invention relates to the use of the measurement of the tumor glycolysis content in vitro in a biological sample from a patient as a biomarker for success of ICB therapy in a subject with a tumor. [0075] In embodiments of the invention, the one or more CTLA-4 inhibitors may be selected from, for example, ipilimumab, tremelimumab, BMS-986249, BMS-986288, AGEN1884, BCD-145, ADU-1604, IBI310, CS1002, BA3071, ADG116, ADG126, and any combination thereof. Derivatives of these compounds that act as CTLA-4 inhibitors are also suitable for use in the invention. In certain embodiments, the CTLA-4 inhibitor according to the methods of the invention is ipilimumab or tremelimumab. [0076] In embodiments of the invention, the one or more tumor glycolysis inhibitors may be selected from, for example, a lactate dehydrogenase A (LDHA) inhibitor, a monocarboxylate transporter (MCT) inhibitor, a mammalian target of rapamycin (mTOR) inhibitor, a phosphoinositide 3-Kinase (PI3K) inhibitor, a mitogen-activated protein kinase (MEK) inhibitor, a Raf inhibitor, a glutamine blocker, and any combination thereof. Examples of LDHA inhibitors include, but are not limited to, GSK2837808A, GNE-140, and NCI-006. Examples of MCT inhibitors include, but are not limited to, AZD3965. Examples of mTOR inhibitors include, but are not limited to, sirolimus and everolimus. Examples of PI3K inhibitors include, but are not limited to, Alpelisib, Idelalisib, Umbralisib, Duvelisib, and Copanlisib. Examples of MEK inhibitors include, but are not limited to, trametinib, copimetinib, and binimetinib. Examples of Raf inhibitors include, but are not limited to vemurafenib, dabrafenib, and encorafenib. Finally, examples of glutamine blockers include, but are not limited to, JHU-083 and CB-839). [0077] In embodiments in which one or more CTLA-4 inhibitors and one or more inhibitors of tumor glycolysis are administered to the subject, (a) the one or more CTLA-4 inhibitors may be administered before the one or more inhibitors of tumor glycolysis; (b) the one or more inhibitors of tumor glycolysis may be administered before the one or more CTLA-4 inhibitors; or (c) the one or more CTLA-4 inhibitors and the one or more inhibitors of tumor glycolysis may be administered simultaneously. [0078] In some embodiments, the methods may further comprise determining the glycolysis status of the tumor, i.e., whether the tumor is a glycolysis-low tumor or a glycolysis-high tumor. [0079] In some embodiments, the glycolysis status of a tumor (i.e., whether the tumor is glycolysis-low or glycolysis-high) may be determined using molecular signatures (at gene or protein levels) that capture the glycolytic pathway. For instance, the determination may be based on the glycolysis-related gene expression signature of genes identified in the Molecular Signatures Database (MSigDB, http://software.broadinstitute.org/gsea/ msigdb) KEGG (see Kaneshia et al., 2017), or as demonstrated in the Examples herein. In some embodiments, the glycolysis-related gene expression signature may be based on expression of one or more or all of the following genes: SLC2A1, HK1, HK2, HK3, GPI, PFKL, PFKM, PFKP, ALDOA, ALDOB, ALDOC, TPI1, GAPDH, PGK1, PGAM1, PGAM4, ENO1, ENO2, ENO3, PKLR, PKM and LDHA. Alternatively, or in combination, the determination of whether a tumor is glycolysis-low or glycolysis-high may be by genetic mutations sustaining the glycolytic pathway (for example, phosphatase and tensin homolog (PTEN) loss, RAF/RAS activating mutations, MYC activating mutations, or amplification). [0080] In other embodiments, the determination of the glycolysis status of a tumor may be by determining protein expression signature of glycolysis-related proteins known in the art. [0081] In some embodiments, designation or classification of a tumor or tumor microenvironment as glycolysis-low or glycolysis-high tumor may be based on the art. For example, Wei et al. (2020) identified kidney renal clear cell carcinoma, head and neck squamous cell carcinoma, lung squamous cell carcinoma, colon adenocarcinoma, rectum adenocarcinoma, and skin cutaneous melanoma as cancers having high glycolysis; and prostate adenocarcinoma, thyroid carcinoma, stomach adenocarcinoma, thymoma, and liver hepatocellular carcinoma as cancer having low glycolysis. Accordingly, in some embodiments, tumors associated with kidney renal clear cell carcinoma, head and neck squamous cell carcinoma, lung squamous cell carcinoma, colon adenocarcinoma, rectum adenocarcinoma, and skin cutaneous melanoma may be considered as glycolysis-high tumors, and tumors associated with prostate adenocarcinoma, thyroid carcinoma, stomach adenocarcinoma, thymoma, and liver hepatocellular carcinoma may be considered as glycolysis-low tumors. [0082] In some embodiments, designation or classification of a tumor or tumor microenvironment as glycolysis-low or glycolysis-high tumor may be based on employing methods as described in the present Examples, or as described in the art, for example, in Wei et al. (2020), which is incorporated herein by reference. [0083] In some embodiments, designation or classification of a tumor or tumor microenvironment as glycolysis-low or glycolysis-high tumor may be based on the molecular signature of the tumor relative to a reference molecular signature. In some embodiments, the reference molecular signature may be the molecular signature of a tumor in one or more subjects who have responded to ICB therapy, for example, CTLA-4 inhibitor treatment. In some embodiments, the reference molecular signature may be the average (mean, median, or mode) molecular signature of tumors from one or more different types of cancer, for example, two or more, or three or more, or five or more, or ten or more, or 15 or more, or 20 or more or 25 or more, or 30 or more different types of cancer. In embodiments in which the molecular signature comprises expression of one or more glycolysis-related genes, for example, if the expression of the one or more genes in the tumor is indicative of a reduced level of glycolysis relative to the expression levels of the reference molecular signature, the tumor may be considered as glycolysis-low; if the expression of the one or more genes in the tumor is indicative of an elevated level of glycolysis relative to the expression levels of the reference molecular signature, the tumor may be considered as glycolysis-high. [0084] In some embodiments, the reduction or elevation the molecular signature (e.g., gene expression, protein expression, etc.) relative to the reference molecular signature may be a difference of about 1% or more, or about 5% or more, or about 10% or more, or about 15% or more, or about 20% or more, or about 25% or more, or about 30% or more, or about 35% or more, or about 40% or more, or about 45% or more, or about 50% or more, or about 55% or more, or about 60% or more, or about 65% or more, or about 70% or more, or about 75% or more, or about 80% or more, or about 85% or more, or about 90% or more, or about 95% or more, or about 100% or more, or about 150% or more, or about 200% or more, or about 250% or more, or about 300% or more, or about 350% or more, or about 400% or more, or about 450% or more, or about 500% or more, or about 550% or more, or about 600% or more, or about 650% or more, or about 700% or more, or about 750% or more, or about 800% or more, or about 850% or more, or about 900% or more, or about 950% or more, or about 10-fold or more, or about 15-fold or more, or about 20-fold or more, or about 25-fold or more, or about 30-fold or more, or about 35-fold or more, or about 40-fold or more, or about 45-fold or more, or about 50-fold or more, or about 55-fold or more, or about 60-fold or more, or about 65-fold or more, or about 70-fold or more, or about 75-fold or more, or about 80-fold or more, or about 85-fold or more, or about 90-fold or more, or about 95-fold or more, or about 100-fold or more, or about 200-fold or more, or about 300-fold or more, or about 400-fold or more, or about 500-fold or more, or about 600-fold or more, or about 700- fold or more, or about 800-fold or more, or about 900-fold or more, or about 1000-fold or more. [0085] Patients to whom the methods and uses of the invention can be applied may be undergoing ICB therapy for any type of cancer. Examples include melanoma, skin carcinoma, non-small cell lung cancer (NSCLC), kidney cancer, bladder cancer, head and neck cancers, lymphoma, breast cancer, ovarian cancer, prostate cancer, pancreatic cancer, colorectal cancer, gastric cancer, and esophageal cancer. [0086] In embodiments of the invention, the treatment comprises administration of an effective dose of the one or more CTLA-4 inhibitors, and/or an effective dose of the one or more inhibitors of tumor glycolysis. The effective dose is known by a person of skill in the art for each medication, and may be the dose that is indicated in the prescribing information and/or the dose that is most frequently administered under particular clinical circumstances (for example for the particular CTLA-4 inhibitor and/or inhibitor of tumor glycolysis being used, the particular route of administration being used, the particular cancer being treated, the age, weight, and/or sex of the particular patient, etc.). . [0087] In some embodiments, administration of the one or more CTLA-4 inhibitors and/or the one or more inhibitors of tumor glycolysis can comprise systemic administration, at any suitable dose and/or according to any suitable dosing regimen, as determined by one of skill in the art. The one or more CTLA-4 inhibitors and/or the one or more inhibitors of tumor glycolysis can be administered according to any suitable dosing regimen, for example, where the daily dose is divided into two or more separate doses. It is within the skill of the ordinary artisan to determine a dosing schedule and duration for administration. EXAMPLES [0088] Embodiments of the present disclosure can be further defined by reference to the following non-limiting examples. It will be apparent to those skilled in the art that many modifications, both to materials and methods, can be practiced without departing from the scope of the present disclosure. Example 1. Tumors Glycolysis Limited Immune Fitness [0089] The negative impact of tumor glucose metabolism on T-cell function was corroborated using the highly glycolytic murine mammary carcinoma 4T1 (Martinez et al. 2018; Simoes et al.2015; Serganova et al.2011). It was found that 4T1 cells, cultured either alone or with activated T cells, consume more glucose and produce more lactate than activated T-cell monocultures (FIG.1, Panel A). In the presence of 4T1 cells, or similar non-toxic concentrations of exogenous lactate (FIG.1, Panel B), T cells were significantly less activated and viable (FIG.1, Panels C and D), indicating the negative impact of tumor glycolysis on T-cell function and potentially response to immunotherapy. [0090] To explore the role of tumor glycolysis in the response to immunotherapy, tumor immune infiltration and glycolysis before and after CTLA-4 blockade was correlated using RNA sequencing data from advanced melanoma patients treated with ipilimumab (Chiappinelli et al.2015; Nathanson et al.2017). At baseline, expression of glucose catabolism genes was frequently negatively correlated with infiltration of major immune cell subsets (FIG.2, Panel A, left; FIG.1, Panel E), suggesting that tumor glycolysis may contribute to a non-inflamed tumor phenotype. After treatment with ipilimumab, these negative correlations were alleviated, with some glycolysis-related genes becoming positively correlated with most immune cell subsets (FIG.2, Panel A, right; FIG.1, Panel F). However, key glycolytic genes, such as the critical enzyme subunit for lactate production, LDHA, and the lactate transporter MCT1 (SLC16A1), remained inversely correlated with immune infiltrates after ipilimumab treatment (FIG.2, Panel A, right), suggesting that anti- CTLA-4 alone may not be sufficient to potentiate immune cell fitness in highly glycolytic tumors overexpressing these genes. [0091] These effects were investigated by comparing a glycolysis-defective 4T1 variant, where LDHA was knocked down (4T1-KD), with the scramble-shRNA-transfected 4T1 control (4T1-Sc) (FIG.3, Panel A). 4T1-KD displayed decreased glycolytic capacity and grew slightly but significantly slower than 4T1-Sc in immunocompetent mice (FIG.3, Panels B and C), pointing to increased immune sensitivity. CTLA-4 blockade did not alter the growth of these tumors and by resecting 4T1-Sc and 4T1-KD lesions 3 days apart, their size for downstream analyses could be equalized (FIG.3, Panel D). In this setting, positive correlations between glycolysis-related genes and immune cell subsets became particularly apparent in glycolysis-defective 4T1-KD tumors upon CTLA-4 blockade (FIG.2, Panels B and C). In these tumors, where LDHA is selectively down-regulated in tumor cells (FIG.3, Panels A and E), positive correlations between LDHA expression and the immune infiltrate were observed, which were eventually amplified by CTLA-4 blockade, pointing to activation of glycolysis in immune cells (FIG.2, Panel C, right). This suggested that glycolysis-low tumors may be more responsive to CTLA-4 blockade, while treatment of glycolysis-high tumors may require dampening tumor glycolysis together with anti-CTLA-4. Example 2. LDHA-KD Tumors Responded Better to Anti-CTLA-4 [0092] The impact of slowing tumor glycolysis on the efficacy of CTLA-4 blockade and the underlying mechanisms was investigated. To simulate the clinical management of breast cancer, mice orthotopically implanted with 4T1-KD or 4T1-Sc cells were treated with anti- CTLA-4 before surgical tumor resection. In these experiments, 4T1-KD and 4T1-Sc tumors were resected 3 days apart to equalize tumor size on the day of surgery (FIG.4, Panel A; FIG.3, Panel D). Importantly, LDH activity remained potently down-regulated in 4T1-KD vs.4T1-Sc tumors up to the day of surgery (FIG.3, Panel E). Neoadjuvant CTLA-4 blockade significantly prolonged survival in 4T1-KD- but not 4T1-Sc-bearing mice (FIG. 4, Panel A). To clarify the immunologic nature of this effect, disease-free mice were re- implanted ~100 days after anti-CTLA-4 and surgical resection of 4T1-KD tumors with either 4T1-KD or the more aggressive 4T1-Sc model. The growth of both 4T1-Sc and 4T1-KD was significantly delayed in the re-implanted compared to naïve control mice (FIG.4, Panel B). Despite the high number of tumor cells re-injected (n=106), ~20-25% of these mice completely eradicated a second tumor implantation, especially with 4T1-KD (n=2/4 tumor- free upon 4T1-KD, n=0/4 tumor-free upon 4T1-Sc; FIG.4, Panel B). This response was associated with greater expansion and maturation in 4T1-KD-re-implanted mice of anti-tumor CD8+ T cells recognizing the 4T1-associated antigen AH1 (FIG.4, Panels C and D). In contrast, mice surviving after neoadjuvant anti-CTLA-4 and surgical resection of 4T1-Sc tumors were not able to control the growth of re-implanted 4T1-Sc tumors (FIG.3, Panel F). This underscored the importance of limiting tumor glycolysis for the development of long- lasting memory anti-tumor responses upon anti-CTLA-4. [0093] Immune changes unique to 4T1-KD-bearing mice responding to neoadjuvant anti- CTLA-4 were examined. For this, 4T1-Sc and 4T1-KD tumors were either resected or injected 3 days apart, which produced similar-size tumors and similar survival outcomes (FIG.4, Panel A; FIG.5, Panels A and B), and with the latter schedule allowing for simultaneous flow cytometry analyses. Tumor LDHA down-regulation resulted in increased T-cell infiltration. Interestingly, this effect extended to Tregs and occurred irrespective of treatment (FIG.4, Panel E; FIG.5, Panel C), pointing to functional modulation or changes in other immune cells in tumor or periphery as potential mechanisms underlying the enhanced activity of anti-CTLA-4 in LDHA-KD tumors. Peripheral Tregs increased after anti-CTLA-4 irrespective of tumor LDHA expression (FIG.5, Panel C). No specific changes in myeloid cells occurred in 4T1-KD-bearing animals treated with anti-CTLA-4 that could explain the different therapeutic outcomes (FIG.5, Panel D). By contrast, tumor- infiltrating CD4 ⁺ T cells—especially Tregs, consistently up-regulated IFN- γ and TNF- α production in 4T1-KD-bearing mice upon anti-CTLA-4 in either schedule (FIG.6, Panels A and B; FIG.7, Panel A-E). CTLA-4 overexpression in intratumoral Tregs may explain their preferential targeting by anti-CTLA-4 (FIG.7, Panel F). Of note, IFN-γ production in Tregs positively correlated with IFN-γ expression in CD8 ⁺ T cells (FIG.6, Panel A and B), suggesting that Treg functional destabilization (i.e., IFN-γ production) could in turn favor activation of CD8 ⁺ tumor-infiltrating lymphocytes (TILs) in vivo. IFN-γ production by 4T1- KD-infiltrating Tregs upon anti-CTLA-4 was not associated with substantial loss of Foxp3 expression (FIG.6, Panel C) but was coupled with CD25 and/or CTLA-4 down-regulation (FIG.6, Panel D). Accordingly, CTLA-4 ^lo Tregs, which proportionally increased after CTLA-4 blockade in 4T1-KD tumors (FIG.6, Panel D), preferentially expressed IFN- γ (FIG.6, Panel E). [0094] These results were confirmed in 3 additional experimental settings. First, the LDHA-KD 4T1 A3-8KD model generated with a different LDHA-targeting shRNA was used, which was previously reported as having LDHA less down-regulated compared to the 4T1 A2-10KD cell variant used here as 4T1-KD corresponding to less severe impairments in glycolysis (FIG.8, Panel C). In this setting, CTLA-4 blockade was slightly less effective and prevented metastasis formation in about 50% of the animals (FIG.9, Panel A). In 4T1 A3-8KD similar to 4T1-KD tumors, CTLA-4 blockade led to Treg phenotypic instability (CD25/CTLA-4 down-regulation), increased IFN- γ production by Tregs and granzyme B by CD8 ⁺ TILs (FIG.9, Panel B and C). Even in this setting, CTLA-4 ^lo Tregs preferentially expressed IFN-γ and further up-regulated IFN-γ after anti-CTLA-4 (FIG.9, Panel D). Accordingly, CTLA-4 expression and IFN-γ production in Tregs were inversely correlated, and IFN-γ production by CTLA-4 ^lo Tregs positively correlated with granzyme B expression in CD8 ⁺ TILs (FIG.9, Panel E). As a second approach, Tregs were perturbed more robustly by employing an IgG2a version of the anti-CTLA-4 clone 9D9, which binds to the mouse FcγRI more efficiently than the standard 9D9 IgG2b antibody (Bruhns 2012), better crosslinks CTLA-4 and has been reported to deplete tumor-infiltrating Tregs more efficiently in other tumor models (Selby et al.2013). In this experimental setting, neoadjuvant 9D9 IgG2a maximized metastasis protection and overall survival in mice bearing 4T1-KD, more extensively down-regulated CTLA-4 ⁺ GITR ⁺ intratumoral Tregs and more strongly up- regulated IFN-γ in the remaining tumor-infiltrating Tregs without affecting their Foxp3 expression (FIG.9, Panel F-I). Again, IFN- γ production by Tregs was found inversely correlated with Treg stability (CTLA-4 and GITR expression) and positively correlated with IFN-γ production in CD8 ⁺ TILs (FIG.9, Panel J). Lastly, these effects were investigated in a different tumor model and mouse genetic background (C57BL/6J), by knocking down LDHA in the mouse melanoma B16F10 (B16-KD; FIG.9, Panel K). B16-KD cells displayed lower LDH activity and glycolytic capacity than the scramble B16-Sc control (FIG.9, Panels L and M). Similar to the effects in the 4T1 model, CTLA-4 blockade significantly down-regulated CTLA-4 and CD25 and increased IFN-γ expression in B16-KD- but not B16-Sc-infiltrating Tregs (FIG.9, Panels N-P). Together, these findings suggested that inhibition of tumor glycolysis may promote the ability of CTLA-4 blockade to induce loss of Treg stability associated with the development of anti-tumor immunity. Example 3. Tumor Glycolysis Supported Treg Stability [0095] To clarify the link between tumor glycolysis and Treg stability in vivo, 4T1-KD in Matrigel plugs containing sodium lactate—a strategy that was shown to partially reverse the anti-tumor effect of LDHA-KD (Serganova et al.2018; Sonveaux et al.2012)—were implanted. Treg phenotypic and functional changes associated with CD8+ TIL activation after anti-CTLA-4 treatment were assessed. In this condition, intratumoral Treg stability was better retained (increased CTLA-4 and decreased IFN- γ), while Foxp3 expression and tumor burden were not substantially affected (FIG.6, Panels F-J). Furthermore, the positive correlation between IFN-γ-producing Tregs and CD8 ⁺ TILs was lost upon addition of lactate (FIG.6, Panel K). This effect appeared to be driven by IFN-γ changes in Tregs, as lactate did not directly affect IFN-γ-expressing CD8 ⁺ T cells (FIG. 6, Panel L). We corroborated these results by maximizing tumor glycolysis (as opposed to exogenously supplying lactate into the TME). For this, hyper-glycolytic 4T1 Rho-0 cells (4T1-EtBr) were generated by ethidium bromide treatment in vitro to reduce mitochondrial function. Tregs infiltrating these hyper-glycolytic tumors vs. glycolysis-defective 4T1-KD tumors were compared and contrasted. 4T1-EtBr cells tended to further up-regulate LDHA, displayed stronger LDH activity than 4T1-Sc or 4T1-KD cells and produced ATP mostly out of glycolysis, in sharp contrast with 4T1-KD cells which produced ATP mainly through mitochondria respiration (FIG.8, Panels A-C). 4T1-EtBr also appeared slightly more aggressive than 4T1-KD in vivo (FIG.8, Panel D). CD4+ T cells infiltrating 4T1-EtBr vs.4T1-KD tumors were found to be enriched in Foxp3 ⁺ Tregs that are phenotypically and functionally more stable, expressing CTLA-4 and CD25 more broadly and producing less IFN-γ (FIG.8, Panels E-G). These results illustrated a direct relationship between tumor glycolysis and intratumoral Treg stability and suggested that the local glucose:lactate ratio may alter Treg susceptibility to anti-CTLA-4-mediated re-programming. In glycolysis-defective tumors, glucose may be more largely available, and CTLA-4 blockade can more efficiently induce Tregs to metabolize glucose. Using a bilateral 4T1-Sc and 4T1-KD tumor system to control for nutrient input, it was found that 4T1-KD cells take up glucose less efficiently and Tregs infiltrating these tumors increase glucose uptake upon anti-CTLA-4 (FIG.8, Panels H-J). These effects were confirmed using a more precise system to detect intra-tumor Tregs for surface glucose staining with Foxp3-GFP transgenic C57BL/6J mice implanted with syngeneic B16-KD and B16-Sc tumors (FIG.8, Panels K-M). Interestingly, increased glucose uptake in Tregs infiltrating glycolysis-defective B16-KD tumors was associated with the tendency of these Tregs to be less suppressive ex vivo (FIG.8, Panel M; FIG.10, Panel A). Example 4. Glucose and CD28 Axis Limited Treg Stability [0096] The conditions leading to loss of Treg stability in glycolysis-defective tumors upon anti-CTLA-4 in vivo were studied. 4T1-KD utilizes less glucose than 4T1-Sc in vitro as well (FIG.11, Panels A and B) and Tregs co-cultured with 4T1-KD vs.4T1-Sc cells modestly, but significantly, up-regulated IFN-γ±TNF-α expression after anti-CTLA-4 treatment (FIG.10, Panel C). Similarly, Tregs cultured in media conditioned by either 4T1- KD or the poorly glycolytic benign mammary gland cell line NMuMg produced more IFN- γ±TNF-α than Tregs exposed to 4T1-Sc-conditioned media, and anti-CTLA-4 enhanced this effect (FIG.10, Panels D and E). It was investigated whether higher glucose availability in cultures with glycolysis-low tumors contributed to anti-CTLA-4-mediated Treg destabilization and whether this effect was linked to CD28 co-stimulation, which has been extensively shown to modulate T-cell glucose metabolism (Frauwirth et al.2002; Klein Geltink et al.2017). It was found that CTLA-4 blockade directly enhances Treg glucose uptake and IFN-γ production in the presence of glucose (11 mM) and physiologic CD28 co- stimulation by irradiated B cells (FIG.11, Panels C and D) independent of mitochondrial metabolism (FIG.12, Panel A). Conversely, blocking oxidative phosphorylation with oligomycin reduced Foxp3 expression and IL-10 production in Tregs (FIG.12, Panel B), indicating that mitochondrial respiration is important for Treg integrity, and that forcing glycolysis in Tregs makes them more susceptible to losing their stability, in support of our new findings here. The impact of anti-CTLA-4-induced Treg glucose consumption on Treg suppression capacity in relationship to glucose loads and CD28 co-stimulation was then evaluated (FIG.11, Panel E). Anti-CTLA-4 was found to inhibit Treg suppression and increase CD86 expression as a function of glucose concentration (FIG.11, Panels F and G; FIG.12, Panels C and D). Importantly, this effect was lost with CD28-deficient Tregs (FIG. 12, Panel E), suggesting that anti-CTLA-4-mediated inhibition of Tregs suppression in the presence of glucose is dependent on CD28 signaling in Tregs. Direct CD28 co-stimulation using an agonist antibody fully overcame the need for glucose to counteract Treg suppression (FIG.11, Panels H-J; FIG. 13, Panels A and B). However, despite complete Treg inhibition, CD28 agonism delayed CD8 ⁺ T-cell proliferation especially at low glucose concentrations (FIG.13, Panel A). By titrating CD28 stimulation, it was found that above a certain concentration (~0.05 µg/ml), anti-CD28 slows T-cell proliferation especially in low glucose (FIG.13, Panel C), CD28 co-stimulation triggers mitochondrial respiration in activated T cells, which less efficiently sustains proliferation (Klein Geltink et al.2017). In contrast to CTLA-4 blockade, inhibition of the other major immune checkpoint PD-1 did not affect Treg suppression, either when high glucose concentrations (11 mM) or PD-1 ⁺ Tregs were tested (FIG.13, Panels D and E), and did not promote Treg glucose uptake in vitro or loss of Treg stability in vivo (FIG.13, Panels F and G). Because anti-PD-1 acts downstream and requires CD28 signaling (Kamphorst et al.2017; Hui et al.2017), these results may be explained by high CTLA-4 expression in Tregs that prevents CD28 co-stimulation. Example 5. Fitness Opposed Stability in Glycolytic Tregs [0097] To formally prove that anti-CTLA-4-mediated Treg destabilization in glycolysis- defective tumors depends on Treg glucose catabolism, it was tested whether this effect is lost in mice with conditional Treg deletion of LDHA or the glucose transporter Glut1. B16-KD was used as a glycolysis-defective tumor model compatible with the genetic background of these mutant mice (C57BL/6). Upon CTLA-4 blockade, Glut1-deficient vs. control Tregs infiltrating glycolysis-defective tumors restored CTLA-4 and CD25 expression, less extensively up-regulated IFN-γ and TNF-α and were less suppressive ex vivo (FIG.14, Panels A-E). Intriguingly, Glut1- or LDHA-deficient tumor-infiltrating Tregs displayed poor expansion and proliferation potential after treatment (FIG.14, Panels F-L). Similarly, LDHA-deficient Tregs remained less fit in culture despite high glucose concentrations (10 mM), and increasing CD28 co-stimulation further reduced their fitness to levels comparable to control Tregs activated in acute glucose restriction (0.5 mM) (FIG.14, Panels M and N). Importantly, the prevalent Ki67-negative fraction in LDHA-deficient Tregs better retained suppressive markers upon activation (FIG.14, Panels M and O). These observations reveal a dual implication for glycolysis in Tregs: it is needed to sustain Treg expansion, but it makes Tregs more susceptible to re-programmability, especially when CD28 can be engaged, such as upon CTLA-4 blockade. This also suggests that glucose is dispensable for active Treg suppression and that alternative sources of fuel can support this function. Material and Methods for the Examples Tumor Cell Lines [0098] Murine breast tissue cell lines were cultured in DMEM supplemented with 10% heat inactivated FBS, 25 mM glucose, 6 mM L-glutamine, 1 x penicillin/streptomycin, and 4 mg/L puromycin. The B16F10 mouse melanoma cell line was cultured in RPMI1640 supplemented with 10% inactivated FBS, 1× nonessential amino acids and 2 mM l- glutamine. Cell lines were authenticated by STR profiling or morphology and expression of specific antigens and were routinely tested for mycoplasma contamination. Tumor cells were transfected with SureSilencing ^TM LDHA-targeting shRNA plasmids (KD; A2= (SEQ ID NO:1); A3= (SEQ ID NO:2)) or scramble control plasmids (Sc= ggaatctcattcgatgcatac (SEQ ID NO:3)). Stable LDHA-KD (4T1 A2-10KD = 4T1-KD, 4T1 A3-8KD and B16-KD) and scramble control (4T1-Sc and B16-Sc) cell lines were generated as previously described (Serganova et al.2018; Rizwan et al.2013). Hyper-glycolytic/poorly oxidative Rho-0 cells were generated by in vitro treatment of 4T1 cells with ethidium bromide treatment (4T1-EtBr) as described (King and Attardi, 1989). LDHA modulation in these cell variants was confirmed at protein level by western blot, using a rabbit anti-LDHA antibody (1:1,000) coupled with an HRP- conjugated anti-rabbit IgG (1:5,000) as secondary antibody, with vinculin (1:1,000; revealed by an HRP-conjugated anti-mouse IgG, 1:5,000) or beta actin (1:5,000) as protein loading control, and at enzymatic activity level by using the Cytotoxicity Detection Kit PLUS (LDH), as previously reported (Serganova et al.2018). Altered glycolytic and mitochondrial metabolism capacity of these tumor cells was also confirmed by Glycolytic Proton Efflux Rate and ATP rate assays using a Seahorse XF 96 Analyzer according to the manufacturer’s instructions. Mice [0099] Same sex, same age mice were used in each experiment. All mice were bred and maintained under specific pathogen-free conditions (with a 12 h light-dark cycle at temperature of 21–23°C and humidity of 35–55%) and used at the ages of 5–10 weeks. The maximal tumor size of 20 mm in any direction was not exceeded in any experiment. In vivo experiments [0100] Five-to-six-week old female BALB/c mice were injected orthotopically with 10 ⁶ 4T1 cells in the mfp. Two days later, the tumor burden was quantified by BLI and mice were randomized in the different treatment groups to receive 3 intraperitoneal injections with 100 µg anti-CTLA-4 (clone 9D9 IgG2b; clone 9D9 IgG2a) or isotype control (clone MPC-11) 3 days apart. 4T1-Sc and 4T1-KD tumors were injected or resected 3 days apart to equalize tumor size before surgery. Disease free mice approximately 100 days after surgery were re- inoculated with 10 ⁶ 4T1-Sc or 4T1-KD cells in the opposite mfp and monitored for tumor growth to test development of anti-tumor immunologic memory. In some experiments, 4T1- KD cells (0.2-1x10 ⁶ /mouse) were implanted in the mammary fat pad in Matrigel with or without 30-50 mM sodium lactate as previously reported (Serganova et al.2018). Metastasis development was monitored every week by BLI upon intraperitoneal injection of 50 μl of D- Luciferin (30 mg/ml). At the time of sacrifice, lungs were collected to quantify lung metastases either by ex vivo bioluminescence imaging or by hematoxylin and eosin staining of formalin fixed and paraffin embedded tissue sections. B16-Sc and B16-KD cells (250,000 cells/injection) were implanted intradermally in 5-8 weeks old wild type or Foxp3-GFP, Foxp3 ^GFP-Cre-ERT2 , Foxp3 ^GFP-Cre-ERT2 ; Slc2a1(Glut1) ^fl/fl , Foxp3 ^YFP-Cre and Foxp3 ^YFP-Cre ; Slc2a1(Glut1) ^fl/+ or Foxp3 ^YFP-Cre ; Ldha ^fl/fl C57BL/6J mice, which were then treated with 100 µg anti-CTLA-4 or the isotype control for 4 administrations 3 days apart. Primary tumor growth was measured twice a week by caliper. Survival was defined as time to death or time to sacrifice for those animals that had to be euthanized because sick and/or their tumors reached the size limits. RNA sequencing analyses [0101] RNA sequencing data for 22 human melanoma samples (n=7, before ipilimumab; n=15, after ipilimumab) was interrogated from a previous analyses (Chiappinelli et al.2015; Nathanson et al.2017) and from 4T1-Sc and 4T1-KD tumors treated with anti-CTLA-4 (n=5/tumor type) or an IgG control (n=4, 4T1-Sc and n=5, 4T1-KD). For mouse samples, frozen tissue was homogenized in TRIzol Reagent using the QIAGEN TissueLyser at 15Hz for 2-3 minutes with a Stainless Steel Bead. Phase separation was induced with chloroform. RNA was precipitated with isopropanol and linear acrylamide and washed with 75% ethanol. RNA samples were resuspended in RNase-free water. After RiboGreen quantification and quality control by Agilent BioAnalyzer, 500ng of total RNA underwent polyA selection and TruSeq library preparation according to instructions provided by Illumina, with 8 cycles of PCR. Samples were barcoded and run on a HiSeq 4000 in a PE50 run, using the HiSeq 3000/4000 SBS Kit (Illumina). An average of 51 million paired reads was generated per sample and the percentage of mRNA bases averaged 69%. Heatmaps of expressed genes were generated using log2-transformed and standardized counts. Immune cell composition was estimated from bulk RNA sequencing data using the mean z-score approach with CIBERSORT LM22 signatures (Newman et al.2015). In this approach, values for each gene are first z-transformed across all samples. Resulting z-scores are then averaged across genes to arrive at a single signature score for each sample. Pearson correlation test was used to analyze dependency between variables. All analyses after gene count generation were conducted in the R statistical environment. In vitro T cell assays [0102] Mouse T cells were cultured in RPMI1640 supplemented with 10% heat inactivated FBS, 1× nonessential amino acids, 2 mM l-glutamine, 1 mM sodium pyruvate and 50 μM β-mercaptoethanol (complete RPMI1640). [0103] Total T cells were immunomagnetically sorted from spleens of naïve BALB/c mice using CD5 microbeads. T cells were labeled with carboxyfluorescein succinimidyl ester (CFSE, Invitrogen) and activated using phytohemagglutinin (PHA, 5 µg/ml) or anti- CD3/anti-CD28 microbeads (1:1 ratio, Dynabeads™ Mouse T-Activator CD3/CD28) in the presence of 4T1 (at 30-50:1, T-cell:4T1 ratio) or the indicated concentrations of lactic acid for 2-3 days in a humidified chamber with 5% CO ₂ at 37°C. After incubation, culture supernatants were collected for lactate and glucose quantification and T cells were processed for flow cytometry analyses. [0104] Suppression assays were performed by incubating Tregs at 1:1 ratio with immunomagnetically purified CD45.1 ⁺ CD8 ⁺ T cells (CD8 microbeads) or CD45.1 ⁺ CD4 ⁺ T cells (CD4 microbeads), which were labeled with CellTrace Violet, and immunomagnetically purified CD45.1 ⁺ CD19 ⁺ B cells (CD19 microbeads) as previously reported (Zappasodi et al. 2018). Cultures were stimulated with 0.5 µg/ml soluble anti-CD3 (clone 145-2C11) in the presence of 50 µg/ml anti-CTLA-4 (clone 9D9), 10-50 µg/ml anti-PD-1 (clone RMP1-14), or 0.0125-2 µg/ml anti-CD28 (clone 37.51) or the matched isotype controls in complete RPMI1640 containing the indicated concentrations of glucose for 48 h in a humidified chamber with 5% CO2 at 37°C. After incubation, cultures were processed for flow cytometry analyses of CellTrace Violet dilution (CD8 ⁺ T cell proliferation) and CD86 expression (B cell co-stimulation). Treg suppression was calculated with the following formula: Treg suppression = [1 - % CTV ^low (CD8 ⁺ T cells + Tregs)/ % CTV ^low (CD8 ⁺ T cells alone)]*100. [0105] For Treg:4T1/4T1-conditioned media assays, CD25 ^hi Tregs were immunomagnetically purified from naïve BALB/c splenocytes. Tregs were incubated with established 4T1-Sc or 4T1-KD cultures in 5 mM glucose complete RPMI1640 for 24 h in the presence of 1 µg/ml soluble anti-CD3, 2,000 U/ml IL-2 and 50 µg/ml anti-CTLA-4. Alternatively, Tregs were cultured for 48 h in 4 h tumor-conditioned media (complete RPMI1640, 11 mM glucose) with 1µg/ml plate-bound anti-CD3, 2,000 U/ml IL-2 and 50 µg/ml anti-CTLA-4 or an isotype control. Monensin and brefeldin A were added for the last 4 h of culture before performing intracellular cytokine staining. [0106] Activation of Treg monocultures was performed by incubating FACS-sorted Foxp3-GFP ⁺ Tregs with 30-Gy irradiated immunomagnetically purified CD45.1 ⁺ CD19 ⁺ B cells (1:1 ratio) in the presence of 0.5 µg/ml soluble anti-CD3 and 50 µg/ml anti-CTLA-4, anti-PD-1 or an IgG control for 48 h in a humidified chamber with 5% CO2 at 37°C. To block mitochondrial metabolism in this assay, 2-5 nM rotenone + antimycin A or 4 nM oligomycin were added. 2,000 U/ml IL-2 were added for the last 24 h incubation. Glucose and lactate measurements [0107] Glucose and lactate were quantified in culture supernatants by either ¹ H NMR, luminescent assays, or by YSI meter. [0108] Quantification of glucose consumption and lactate production by ¹ H NMR was conducted by integration of spectral line-shapes, as previously reported (Simoes et al.2015). Glucose and lactate concentrations were calculated with the following formula: Cu=Ck*(Iu/Ik)*(Nk/Nu) in which Cu=concentration of the unknown (lactate or glucose); Ck=concentration of glucose in base medium ; Iu=integral area of unknown peak (lactate or glucose); Ik=integral area of glucose in base medium; Nk=number of protons associated with glucose peak (C6-glucose=1 proton); and Nu=number of protons associated with unknown (C6-glucose = 1 proton, C3- lactate=3 protons). [0109] The Glucose-Glo ^TM Assay was used to quantify glucose consumption in supernatants from 4T1-Sc, 4T1-KD, B16-Sc and B16-KD cells. Glucose consumption was calculated with the following formula: Glucose consumption = (glucose in base media – glucose in conditioned media)/n. of cells. YSI-based measurements of glucose consumption and lactate production were calculated as follows: Glucose consumption = (glucose in conditioned media - glucose in base media)/(n. of cells/10 ⁶ x hours) Lactate production = (lactate in conditioned media - lactate in base media)/(n. of cells/10 ⁶ x hours) Multiplex cytokine analysis [0110] Cytokine concentrations in culture supernatants were quantified by using Luminex-based bead multiplex immunoassays and the DropArray system according to the manufacturers’ instructions. Quantitative real time PCR [0111] Total RNA was extracted by using TRIZOL reagent and reverse-transcribed into complementary DNA (cDNA) using the High Capacity cDNA Transcription kit. Expression of the indicated transcripts was quantified with the Fluidigm Biomark system by using the appropriate 6-fluorescein amidite (6-FAM)-minor groove binder (MGB)-conjugated TaqMan primer probes on target gene pre-amplification according to the manufacturer’s protocol. Gene expression was normalized relative to beta actin. Data were analyzed by applying the 2−ΔCT calculation method. Flow cytometry analyses [0112] Tumors were dissociated after 30 min incubation with Liberase TL and DNAse I to obtain single-cell suspensions. When tumor mass exceeded 0.1 gr, immune-cell infiltrates were enriched by Percoll gradient centrifugation. Surface staining was performed after 10 min incubation on ice with an anti-mouse CD16/CD32 antibody (clone 2.4G2) to block Fcγ receptors, by using panels of appropriately diluted fluorochrome-conjugated antibodies against the following mouse proteins in different combinations: CD45 (clone 30-F11; 1:250), CD45.1 (clone A20; 1:200), CD3 (clone 145-2C11; 1:200), CD4 (clone RM4-5; 1:200), CD8a (clone 5H10; 1:200), CD25 (clone PC61.5; 1:200), CD44 (clone IM7; 1:200), CD62L (clone MEL-14; 1:200), GITR (clone DTA-1; 1:200), PD-1 (clone RMP1-30; 1:200), CD86 (clone GL1; 1:200), CD11b (clone M1/70.15; 1:200), F4/80 (clone BM8; 1:200), MHC-II (clone M5/114.15.2; 1:200), Gr1 (clone RB6-8C5; 1:200) and an eFluor506 fixable viability dye. For intracellular staining, mouse cells were fixed and permeabilized (Foxp3 fixation/permeabilization buffer) and incubated with appropriately diluted FITC- or AF488- labeled anti-mouse Foxp3 (clone FJK-16s; 1:200), PE-labeled anti-CTLA-4 (clone UC10- 4F10-11; 1:200) and PECy7 or PE-labeled anti-Ki67 (clone B56, 1:50; clone 16A8, 1:250) antibodies for 30 min on ice. CD206 was revealed following cellular permeabilization and fixation in the Cytofix and Cytoperm buffer, according to the manufacturer’s instructions, using an AlexaFluor647-conjugated anti-mouse CD206 antibody (clone C068C2, 1:200). [0113] 2-NBDG staining of 4T1 cells was performed by incubation with 100 µM 2- NBDG in complete DMEM in a humidified incubator at 37°C for 15 min. Cells were then extensively washed before acquisition. GlucoseCy3 staining was performed by 25 min incubation in serum-free, glucose-free RPMI1640 containing 0.4 µM glucoseCy3 in a humidified incubator at 37°C. [0114] AH1 Dextramer staining was performed on peripheral blood after red blood cell lysis (PharmLyse) by 10 min incubation at RT° according to the manufacturer’s instructions, followed by 20 min surface staining with anti-CD8, anti-CD44, and anti-CD62L antibodies. DAPI was added right before acquisition to exclude dead cells. [0115] For intracellular cytokine staining, mouse tumor immune infiltrates were re- stimulated with 0.1 µg/ml PMA and 0.5-1 μg/ml ionomycin in complete RPMI1640 in a humidified chamber with 5% CO2 at 37°C. After 1 hour, 1x GolgiStop and 1x GolgiPlug were added to the cultures and incubated for an additional 4-5 hours at 37°C. Surface staining was performed after blocking Fcγ receptors by incubating cells with PerCPCy5.5- labeled anti-CD4, BV650-labeled anti-CD8, and APCCy-labeled anti-CD45 antibodies and an eFluor506-labeled fixable viability dye for 30 min on ice. Cells were then washed, fixed and permeabilized with the Foxp3 fixation/permeabilization buffer and stained for 45 min with FITC- or AF488-labeled anti-Foxp3, BV450- or BV510-labeled anti-IFN-γ (clone XMG1.2, 1:200-250) and APC-labeled or PECy7-labeled anti-TNF-α (clone MP6-XT22, 1:200-250) antibodies. Samples were acquired on an LSRII or Symphony X50 flow cytometer using BD FACSDiva software (and data analyzed with FlowJo 10.6.1 software. [0116] Mouse Tregs were sorted from Foxp3-GFP, Foxp3 ^GFP-Cre-ERT2 and Foxp3 ^{GFP-Cre- ERT2} ;Slc2a1(Glut1) ^fl/fl transgenic mice by using CD4-pre-enriched splenocytes (CD4 Microbeads). Briefly, following Fc γ receptor blockade with anti-mouse CD16/CD32, samples were stained with a PECy7- or APC-labeled anti-CD4 antibody for 30 min on ice. Cells were then washed and DAPI was added immediately before acquisition. FACS sorting was conducted on a FACSAria II cell sorter. Statistical Analyses [0117] Two-sided Student’s t test and 2-way ANOVA (with Bonferroni’s multiple comparisons test) were used to detect statistically significant differences between groups. P values for survival analyses were calculated with log-rank (Mantel-Cox) test. Detailed information of the statistical test and number of observations/replicates used in each experiment, and the definition of center and dispersion is appropriately reported in the legend of each figure. Significance was defined as follows: * = p<0.05, ** = p<0.01, *** = p<0.001, **** = p<0.0001.

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