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Title:
IDENTIFYING CANCER NEOANTIGENS FOR PERSONALIZED CANCER IMMUNOTHERAPY
Document Type and Number:
WIPO Patent Application WO/2021/091541
Kind Code:
A1
Abstract:
A method is described to discover, identify, analyze, quantitate, and otherwise detect expression of and determine the amino acid sequence of cancer neoantigenic peptides directly from histopathologically-processed cancer patient tumor tissue. Identification of cancer neoantigenic peptides that reside on the outside surface of specified cells derived from histologically-processed cancer patient tumor tissue can be used to create a personalized cancer immunotherapy strategy to treat the patient from whom the tissue was collected.

Inventors:
KRIZMAN DAVID (US)
Application Number:
PCT/US2019/059934
Publication Date:
May 14, 2021
Filing Date:
November 05, 2019
Export Citation:
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Assignee:
KRI TECH INCORPORATED (US)
International Classes:
A61K35/15; A61K35/17; A61K35/18; A61K35/76; A61K35/761; A61K38/19
Domestic Patent References:
WO2017205810A12017-11-30
WO2019168984A12019-09-06
WO2019050994A12019-03-14
WO2018005276A12018-01-04
Foreign References:
US20170052196A12017-02-23
Other References:
KRIZMAN ET AL.: "Application of tissue mesodissection to molecular cancer diagnostics", JOURNAL OF CLINICAL PATHOLOGY, vol. 68, 27 November 2014 (2014-11-27), pages 166 - 169, XP055441844, DOI: 10.1136/jclinpath-2014-202723
CHAURAND ET AL.: "Imaging Mass Spectrometry of Intact Proteins from Alcohol-Preserved Tissue Specimens: Bypassing Formalin Fixation", JOURNAL OF PROTEOME RESEARCH, vol. 7, no. 8, 10 July 2008 (2008-07-10), pages 3543 - 3555, XP055821117
MYLONAS ET AL.: "Estimating the Contribution of Proteasomal Spliced Peptides to the HLA-1 Ligandome", MOLECULAR & CELLULAR PROTEOMICS, vol. 17, no. 12, 31 August 2018 (2018-08-31), pages 2347 - 2357, XP055680510, DOI: 10.1074/mcp.RA118.000877
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Claims:
Claims

1. A method to detect expression of and identify the amino acid sequence of a cancer neoantigenic peptide comprising: a) collecting tumor cells from a section of cancer patient tumor tissue comprising histopathologically-processed tissue/cell material wherein said tissue is characterized by cellular heterogeneity and wherein said material is formalin fixed paraffin embedded tissue, ethanol fixed paraffin embedded tissue, or frozen tissue, b) preparing a peptide lysate representing a collection of candidate cancer neoantigens from said collected tumor cells, c) analyzing said peptide lysate using mass spectrometry to detect and identify all peptides and determine the amino acid sequence of all peptides thus providing for candidate cancer neoantigen peptides, and d) performing bioinformatic analysis of candidate cancer neoantigen peptides to determine and identify peptides that demonstrate a statistically significant probability of binding to one or more MHC complex molecules on the outer surface of said tumor cells in order to confirm, and optionally quantitate, at least one cancer neoantigenic peptide from the collection of candidate cancer neoantigen peptides.

2. The method of claim 1, wherein the peptide lysate representing a collection of candidate cancer neoantigens from said collected tumor cells is not the result of protein digestion using a protease.

3. The method of claim 1, wherein detecting expression of and determining the amino acid sequence of candidate cancer neoantigenic peptides from said tumor cells is performed on mass spectrometry data utilizing software tools including but not limited to MASCOT, MaxQuant, Sequest, Scaffold, and Skyline.

4. The method of claim 1, wherein identifying a peptide, or peptides, as a confirmed cancer neoantigen is based on statistically significant demonstration to bind to one or more MHC complex molecules on the outer surface of said tumor cells utilizing software tools including but not limited to NetMHCpan, MixMHC2pred, ImmuneEpitope, Immunogenicity, PEPVAC, RankPep, MARIA, and DeepLigand.

5. The method of claim 4, wherein said confirmed cancer neoantigenic peptide, or peptides, comprises a statistically- significant canonical MHC-anchoring motif.

6. The method of claim 1, wherein said confirmed cancer neoantigenic peptide, or peptides, originates in the genome and derives from an exon.

7. The method of claim 6, wherein the amino acid sequence of said exon-derived peptide results from one or more mutations in an exon region of the tumor cell genome and wherein one or more amino acids within said sequence is different from the normal peptide sequence.

8. The method of claim 1, wherein said confirmed cancer neoantigenic peptide does not originate in the genome and results from proteasome-generated splicing of previously unrelated amino acids and peptides.

9. The method of claim 1, wherein said cancer patient tumor tissue comprises histopathologically-processed tissue/cell material characterized by cellular heterogeneity.

10. The method of claim 9, wherein said cancer patient tumor tissue is formalin-fixed paraffin- embedded tissue.

11. The method of claim 9, wherein said cancer patient tumor tissue is ethanol fixed.

12. The method of claim 9, wherein said cancer patient tumor tissue is frozen.

13. The method of claim 9, wherein said cancer patient tumor tissue is stained to identify tumor cells using a histochemical stain.

14. The method of claim 13, wherein said stain is selected from the group consisting of hematoxylin, eosin, Congo red, aldehyde fuchsin, anthraquinone derivatives, alkaline phosphatase, Bielschowsky, Cajal, cresyl violet, Fontana-Masson, Giemsa, Golgi stain, iron hematoxylin, luxol fast blue, luna, Mallory trichrome, Masson trichrome, Movat's pentachrome, mucicarmine, nuclear fast red, oil red 0, orcein, osmium tetroxide, Papanicolaou, periodic acidschiff, phosphotungstic acid-hematoxylin, picrosirius red, Prussian blue, reticular fiber, Romanowsky stains, safranin 0, silver, Sudan stains, tartrazine, toluidine blue, Van Gieson,Verhoeff, Von Kossa, and Wright’s stain.

15. The method of claim 13, wherein said tissue is stained to identify tumor cells using an antibody-based immunohistochemical method.

16. The method of claim 1, wherein said tumor cells are collected using tissue microdissection.

17. The method of claim 1, wherein the mode of mass spectrometry is selected from the group consisting of, but not limited to, collision-induced dissociation (CID), orbitrap, orbitrap/hybrid, ion trap, higher energy collision dissociation (HCD), electron-transfer dissociation (ETD), electron-transfer dissociation high definition (ETDHD), electron-capture dissociation (ECD), electron transfer higher energy collision dissociation (EThcD), or combinations thereof.

18. The method of claim 1, wherein the mode of mass spectrometry is selected from the group consisting of Selected Reaction Monitoring (SRM), Multiple Reaction Monitoring (MRM), intelligent Multiple Reaction Monitoring (iMRM), Parallel Reaction Monitoring (PRM), Consecutive Reaction Monitoring (CRM), and/or multiple Selected Reaction Monitoring (mSRM), and combinations thereof.

19. The method of claim 1, wherein said confirmed cancer neoantigenic peptide, or peptides, is used to select a treatment selected from the group including but not limited to small molecule agents, immunomodulatory agents, biological therapeutic agents, targeted antibodies, engineered natural killer cells, other engineered and/or non-engineered immune cells, standardized cancer vaccines, peptide vaccines, and personalized engineered cancer vaccines.

20. The method of claim 1, wherein information about said confirmed cancer neoantigenic peptide, or peptides, is combined with information resulting from mass spectrometry analysis of the same, or similar protein/peptide lysate, that is prepared from the same tumor tissue and tumor cells in order to detect and quantitate drug target proteins and chemotherapy target proteins that are not neoantigenic peptides for use in determining additional and combinatorial information about choice of cancer therapy.

21. The method of claim 1, wherein information about said confirmed cancer neoantigenic peptide, or peptides, is combined with information resulting from nucleic acid sequence obtained from nucleic acids prepared from the same tumor tissue and tumor cells in order to detect changes in nucleic acids for use in determining additional and combinatorial information about choice of therapy.

Description:
Identifying Cancer Neoantigens for Personalized Cancer Immunotherapy Field of Invention

Cancer neoantigen peptide identification and use thereof in the field of personalized cancer immunotherapy strategies is provided. Methods are provided to discover, identify, analyze, quantitate, and detect expression of cancer neoantigenic peptides in specified cells obtained directly from histopathologically -processed cancer patient tumor tissue. Such peptides can be useful as cancer therapeutic targets against which a cancer immunotherapy strategy can be developed to kill the tumor cells expressing the identified neoantigenic peptides.

Background

Small peptides, on the order of 8-12 amino acids in length, are continuously generated in tumor cells and can be presented on the tumor cell surface via or not via the Major Histocompatibility Complex (MHC) presentation process. The proteins of the Major Histocompatibility Complex (MHC) in vertebrates, (referred to in humans as the Histocompatibility antigen complex (HLA) and referred to herein as the MHC), provide the molecular process by which these peptides are presented to the host immunological system.

Tumor-derived peptides that are not presented on normal calls are referred to as tumor neoantigens and can function to identify tumor cells as self or non-self to the patient’s own immune system. Presentation on the outside of the tumor cell surface of such non-normal, tumor- specific peptides function to help the tumor cells escape immune surveillance. However, these same peptides can also be utilized by cancer immunotherapy strategies to tag tumor cells for attack by the patient’s own immune system.

Whether or not a peptide is identified as self or non-self to the patient’s own immune system depends on the peptide’s amino acid sequence. Neoantigens, often referred to as neoepitopes, can function to help tumor cells evade immune surveillance but can also make them molecular targets for cancer therapy strategies. Identifying the sequences of peptide neoantigens can lead to development of treatment strategies where the patient’s own immune system can be modulated to recognize the specific cancer neoantigenic peptides that are different from normal, and thus induce an immunological response to tumor cells expressing these neoantigenic peptides. One class of cancer neoantigenic peptides arises from nonsynonymous mutations in exons present within the genome whereby specific small peptides derived from the mutated form of proteins are presented on the tumor cell surface, usually via the MHC antigen presentation process. These neoantigenic peptides originate in the genome, are referred to as exon neoantigens, and can be identified by genomic analysis through technologies such as DNA and/or RNA sequencing. However, these genomics-based methods can only infer or predict the expression of these neoantigens. The methods described below provide the only definitive way presently known to determine the expression of these cancer neoantigens in specified cell types obtained directly from histopathologically-processed cancer patient tumor tissue.

A second, distinct class of cancer neoantigenic peptides have also been described. This class of neoantigenic peptides results from proteasome-generated splicing together of smaller, previously unrelated, peptides for presentation on the surface of tumor cells via, or not via, the MHC presentation process. This class of neoantigens, termed proteasome generated spliced epitopes (PGSEs), is not encoded in the genome and therefore can be detected only using proteomic technology, and particularly via mass spectrometry-based proteomics technologies. The methods described below also provide the only definitive way presently known to determine the expression of this second and distinct class of cancer neoantigens (PGSE-derived neoantigens) in specified cell types obtained directly from histopathologically-processed cancer patient tumor tissue.

The systems and methods described herein use standard histological processing of cancer patient tumor tissue, tissue microdissection, preparation of a peptide lysate, mass spectrometry, and bioinformatics to discover, identify, detect, and quantitate expression of genome-derived and PGSE-derived neoantigens directly in specified cells obtained from histologically -processed cancer patient tumor tissue. Cancer patient tumor tissue, for example formalin fixed paraffin embedded (FFPE) patient tissue, is cut into histology sections using standard histological methods. The sections can then be microdissected using tissue microdissection methods to collect only tumor cells from the tissue sections. This enriches for those peptides that are specifically expressed only by tumor cells, which is where cancer neoantigens are presented via, or not via, the MHC complex for presentation to the immune system. Once collected, the tumor cells can be processed to provide a lysate preparation of just peptides expressed by the tumor cells whereby the resulting lysate preparation is analyzed using mass spectrometry. Proteomics bioinformatic tools and software, such as MASCOT, MaxQuant, Sequest, Scaffold, and Skyline, may then be used to identify the amino acid sequence of all peptides expressed by the tumor cells (candidate cancer neoantigen peptides) identified via mass spectrometry. This will also determine whether a peptide sequence is genomically encoded or, in the case of PGSE neoantigens, is a peptide sequence that does not have its origins in a contiguous genomic sequence. Additional bioinformatic tools and software, such as NetMHCpan, MixMHC2pred, ImmuneEpitope, Immunogenicity, PEPVAC, RankPep, MARIA, and DeepLigand is then subsequently applied to the identified candidate cancer neoantigen peptides to determine which peptides from patient tumor cells have the critical properties of MHC presentation mediated by highly conserved MHC anchoring characteristics. These anchoring characteristics primarily comprise motifs mediated by specific amino acid residues at amino acid positions 1, 2, 7, and 9, and where the specified amino acids at these positions determine whether or not the neoantigenic peptides are bound via one or more of the various classes of the MHC complexes. It is precisely the determination of which cancer neoantigenic peptides have these specific MHC binding characteristics as determined by specific software tools that will identify which peptides are cancer neoantigens present on the tumor cell surface and which will be most useful for targeting tumor cells with immunotherapeutic strategies such as cancer vaccines.

The methodology described herein can be used to provide improved methods of treatment and, in particular, inform optimal choice of immunotherapy strategies on a personalized patient basis. A variety of immunotherapeutic approaches can be utilized to subsequently treat a patient. Targeted immunotherapeutic agents can be developed against cancer neoantigens whereby the agents comprise for example small molecules, antibodies, cancer vaccines, peptide vaccines, lymphocytes, modified lymphocytes, and multiple versions of natural killer (NK) cells, all of which are designed to recognize and bind to cancer neoantigens on the surface of patient tumor cells for the purposes of initiating, modulating and/or maintaining a patient-specific, immune- based, tumor cell killing response. The direct result of the described methodologies and systems is to inform the therapeutic strategy that will likely be most useful for treating a given cancer patient with a great degree of specificity and personalization. Summary

Methods are provided for discovering, identifying, analyzing, quantitating, and otherwise detecting expression of tumor- specific, cancer neoantigenic peptides. The method comprises collecting specified cells from cancer patient tumor tissue, for example via tissue microdissection, identifying neoantigenic peptides present in the collected specified cells by mass spectrometry, and bioinformatic tools/software to identify those peptides that have a high statistical probability to bind to MHC complexes on the surface of tumor cells. The cancer neoantigenic peptides can be used for personalized immunotherapeutic strategies. Cancer neoantigenic peptides directly encoded in the genome arise generally due to mutations in exons within tumor cell DNA, whereas neoantigenic peptides that are not directly encoded by a contiguous nucleic acid sequence in the genome can arise from peptide splicing properties within the tumor proteasome that give rise to proteasome generated spliced epitopes (PGSEs). The methods herein permit discovery, identification, analysis, quantitation, and detection of expression of either or both types of cancer neoantigens on the outer surface of specified cells obtained directly from histologically-processed cancer patient tumor tissue using mass spectrometry and sophisticated bioinformatic tools/software. Because these cancer neoantigenic peptides reside on the outside of the tumor cell membrane, and most probably bind MHC molecules on the tumor cell surface, they can serve as patient- specific immunotherapeutic targets whereby the cancer neoantigenic peptides can be targeted by a number of therapeutic strategies including cancer vaccines, peptide vaccines, and targeted therapeutic agents, all of which are designed to initiate, enhance, target, and otherwise manipulate the patient’s own immune system to kill the patient’s own tumor cells.

Brief Description of the Drawings

Figure 1 shows a graphical description of the methods described herein. Specified cells, such as patient tumor cells, are collected directly from histologically-processed cancer patient tumor tissue, potentially using tissue microdissection methodology, and a peptide lysate is prepared and subsequently analyzed using a mass spectrometer. Mass spectrometry is used to identify and provide the amino acid sequence for potential cancer neoantigenic peptides expressed by tumor cells, and the data are further analyzed by sophisticated bioinformatic tools/software to identify which of these potential cancer neoantigens show a high statistical probability to be bound to the MHC molecules on the outer surface of the tumor cells and thus making them targets for cancer immunotherapy. Such identified peptides are considered cancer neoantigens that can be the target of a personalized immunotherapy strategy encompassing such therapeutic agents as cancer vaccines, small molecules, biologies, lymphocytes, modified lymphocytes, and preconfigured and non-preconfigured natural killer cells.

Detailed Description

Methods are provided for discovery, identification, detection, and quantitation of expression of cancer neoantigenic peptides in tumor cells obtained directly from histopathologically-processed cancer patient tumor tissue for use in personalized cancer immunotherapy strategies. These techniques generate direct empirical evidence of tumor originating neoantigens based on proteomic analysis and do not rely solely on inferred or indirect evidence such as that reliant on genomic analysis. Moreover, the proteomic techniques detect and identify the actual neoantigen peptides that can be converted into patient specific therapies and therefore provide advantages over techniques previously used in the art.

Cancer neoantigens are newly formed antigens that are present on the outside of tumor cells that have not been previously recognized by the immune system. Neoantigens are small peptides, approximately 8-16 amino acids in length, are usually presented on the tumor cell surface by the MHC process/complex and are sometimes formed when a protein undergoes further modification within a biochemical pathway such as glycosylation, phosphorylation, or proteolysis. The most common cancer neoantigens arise via nonsynonymous mutations within exons present in the tumor cell genome, where expression of the mutated form of a protein is processed by the cellular presentation machinery, such as the tumor proteasome, and presented on the tumor cell surface via the MHC complex/process. However, there is a unique, distinct class of cancer neoantigens that is generated by the tumor proteasome whereby previously unrelated small peptides are spliced together, generating hybrid peptides that do not have origins in the tumor cell genome. These unique cancer neoantigens are known as proteasome generated spliced epitopes (PGSEs) and are also present on the outside surface of the tumor cell.

Cancer neoantigens are, by definition, bound to the MHC complex on the surface of tumor cells for presentation to the host immune system. MHC molecules have a very specialized role in presenting peptides for cell recognition by T lymphocytes and natural killer cells (NK cells). In general, MHC molecules bind peptides within a peptide binding groove on the MHC molecule allowing for presentation of the peptide sequences on the tumor cell surface. T lymphocytes and NK cells recognize these MHC complexes which have been shown to both inhibit the cytotoxic effects of these lymphocytic cells as well as trigger expansion of lymphocyte cell subsets for antitumor responses. There are MHC-binding motifs found within peptides that bind within the peptide binding groove of the MHC complex where these motifs, in general, involve highly conserved MHC anchoring characteristics mediated by specific amino acid residues at amino acid positions 1, 2, 7, and 9, and where the specified amino acids at these positions determine if the neoantigenic peptides bind to one or more of the various classes of the MHC complex molecules. For example, the most highly conserved amino acids that mediate binding to the MHC class I (HLA-C) complex comprise the amino acids F and Y at amino acid position PI; the amino acids R, A, S, F, W, and Y at amino acid position P2; amino acids K, Q, R, F, W, and Y at amino acid position P7; and amino acids F, I, L, M, V, and Y at amino acid position P9.

Proteasomes are protein complexes inside all eukaryotic cells that are located in both the nucleus and the cytoplasm. The main function of the proteasome is to degrade unneeded or damaged proteins by proteolysis mediated by protease enzymes. Proteasomes are part of a major mechanism by which cells regulate the concentration of proteins, degrade misfolded proteins, and recycle amino acids for use in synthesizing new proteins. The degradation process yields peptides that are usually 6-9 amino acid in length, and which can then be further degraded into shorter amino acid sequences. In general, proteins are identified for degradation with a small protein called ubiquitin where the identification reaction is catalyzed by ubiquitin ligase enzymes. Once a protein is identified with a single ubiquitin molecule, this is a signal to other ligases to attach additional ubiquitin molecules resulting in a polyubiquitin chain that is bound by the proteasome allowing it to degrade the protein.

The proteasomal degradation pathway is essential for many cellular processes including the cell cycle, regulation of gene expression, and responses to oxidative stress. The proteasome also plays a critical role in the function of the adaptive immune system whereby peptide antigens from invading pathogens are displayed by the MHC class I proteins on the surface of antigen- presenting cells. These peptides are products of proteasomal degradation of proteins originated by the invading pathogen. Although constitutively expressed proteasomes can participate in this process, a specialized proteasomal complex composed of additional proteins and whose expression is induced by interferon gamma, are the primary producers of peptides that are optimal in size and composition for MHC binding. Utilizing this same natural and useful cellular process, peptides that result from proteasome processing and presentation on the tumor cell outer surface via the MHC complex/process can function as cancer neoantigens which can be exploited as cancer immunotherapeutic targets.

Proteomics technologies permit detection and quantitation of proteins and peptides in a biological sample, such as a protein lysate from cancer patient tumor tissue. Proteomics, and more specifically, proteomics using mass spectrometry as the analytical tool, can identify known and unknown peptides within a protein/peptide lysate prepared from cancer patient tumor tissue. Mass spectrometry (MS) is an analytical technique that ionizes chemical species and sorts the ions based on their mass-to-charge ratio. Mass spectrometry is used in many different fields of science and is applied to pure samples as well as complex mixtures of molecules. Mass spectra are used to determine the elemental or isotopic signature of a sample, the masses of particles and of molecules, and to elucidate the chemical structures of molecules, such as peptides and other chemical compounds. In the case of the presently described method mass spectrometry is applied to complex peptide lysates prepared from specified cells obtained directly from histopathologically-processed cancer patient tumor tissue to precisely identify and provide the amino acid sequence of such peptides.

Mass spectrometry proteomics can detect, identify, and provide the amino acid sequence of peptides in a complex protein lysate either in a “global profiling” mode, which aims to detect and identify the presence of as many peptides, known and unknown, as is possible, or in a “targeted” mode which aims to detect and identify only specified, previously known peptides suspected of being present in the complex protein lysate while ignoring all other peptides in the lysate. The presently described method utilizes both “global profiling” and “targeted” analysis of peptides in a complex protein lysate prepared from specified cells obtained directly from histopathologically-processed cancer patient tumor tissue. “Global profiling” is used to detect and identify expression of both known and previously unknown cancer neoantigenic peptides, while the “targeted” approach is used to detect and identify expression of previously discovered and known peptides that are suspected of being present in specified cells obtained directly from histologically-processed cancer patient tumor tissue. The “global profiling” approach is most advantageously performed using an ion trap mass spectrometer (e.g. the Orbitrap (Thermo-Fisher Scientific)). Different versions of the mass spectrometer suitable for performing a global profile include but are not limited to ion trap, orbitrap, and hybrid ion trap instruments. Such instruments may be interfaced with liquid chromatography and provide an outer barrel-like electrode and a coaxial inner spindle-like electrode that traps ions in an orbital motion around the spindle. The image current from the trapped ions is detected and converted to a mass spectrum using the Fourier transform of the frequency signal. This instrument is particularly useful for detecting and identifying as many peptides as possible in a complex protein lysate without requiring any prior knowledge of the peptide content of the complex protein lysate.

The “targeted” approach is most advantageously performed using a triple quadrupole mass spectrometer. The triple quadrupole instrument also is most often interfaced with liquid chromatography and is a tandem mass spectrometer consisting of two quadrupole mass analyzers in series with a (non-mass-resolving) radio frequency (RF)-only quadrupole between them to act as a cell for collision-induced dissociation. Unlike traditional MS techniques, MS/MS techniques allow for mass analysis to occur in a sequential manner in different regions of the instruments. The triple quadrupole mass spectrometer follows the tandem-in- space arrangement, due to ionization, primary mass selection, collision induced dissociation (CID), mass analysis of fragments produced during CID, and detection occurring in separate segments of the instrument. Ion trap instruments surpass the triple quadrupole mass spectrometer in mass resolution and mass range; however, the triple quadrupole has the advantage of being less expensive to operate, easier to operate, and highly efficient. Also, when operated in the Selected Reaction Monitoring/ Multiple Reaction Monitoring (SRM/MRM) mode, the triple quadrupole mass spectrometer has superior detection sensitivity as well as quantification. The triple quadrupole allows the study of low-energy low-molecule reactions, which is useful when peptides are being analyzed. This instrument is effective for detecting, identifying, and quantitating known peptides from a complex protein lysate without any prior knowledge of the peptide content of the complex protein lysate.

Performing SRM/MRM analysis of proteins in cancer patient tumor tissue can inform the therapeutic strategy for treating the cancer patient by detecting and quantitating specific drug target proteins directly in the tumor cells from patient tissue. Therapeutic agents that inhibit function of specific target oncoproteins can be administered to the cancer patient based on this information. In addition, therapeutic agents that mark the tumor cells for killing via the patient’s own immune system can also be administered to the patient from which the tissue was obtained to kill any tumor cells that remain within the cancer patient. Thus, detecting expression of cancer neoantigenic peptides that identify tumor cells as different from normal cells is critical to administering optimal therapies to the cancer patient.

Cancer neoantigens that are deposited by normal cellular mechanisms on the outside surface of the tumor cell membrane, as for example in MHC molecular complexes, can only be inferred (not confirmed as expressed peptides) using genomics technologies but can be unequivocally confirmed using proteomics technologies. Proteomics technologies have distinct advantages over genomics for evaluation of cancer neoantigenic peptides which include confirming empirically the expression of cancer neoantigens in tumor cells and determining empirically the actual amino acid structure of the neoantigens. As described herein, mass spectrometry advantageously is used to identify whether a peptide neoantigen is actually expressed by tumor cells, and potentially other cells within cancer patient tumor tissue.

Genomics technologies can only infer (through RNA expression analysis) that such cancer neoantigens peptides are expressed in tumor cells. Because the particularly unique class of peptide neoantigens known as PGSEs does not originate in the genome this particular class can only be analyzed at the peptide level i.e. using proteomics technologies. Identifying the cellular expression of these candidate cancer neoantigens in tumor cells, and other cell types, is only possible by a proteomic approach, advantageously using mass spectrometry.

Tumor cells present within cancer patient tumor tissue can be identified for collection using a multitude of standard tissue staining methods. Standard tissue staining methods are normally used by a trained histologist/pathologist to visualize specific cells, cell populations, and physical tissue characteristics in tissue sections to guide cancer diagnostics. There are many standard histology stains that result in a wide range of visual colors that are well established and well known in the field of histology/pathology and which can possibly be used to identify tumor cells for collection and include, but are not limited to, hematoxylin, eosin, congo red, aldehyde fuchsin, anthraquinone derivatives, alkaline phosphatase, Bielschowsky, Cajal, cresyl violet, Fontana Masson, Giemsa, Golgi stain, iron hematoxylin, luxol fast blue, luna, Mallory trichrome, Masson trichrome, Movat's pentachrome, mucicarmine, nuclear fast red, oil red 0, orcien, osmium tetroxide, Papanicolaou, periodic acid-schiff, phospho tungstic acid-hematoxylin, picrosirius red, Prussian blue, reticular fiber, Romanowsky stains, safranin 0, silver, Sudan stains, tartrazine, toluidine blue, Van Gieson, Verhoeff, Von Kossa, and Wright’s stain. Each type of stain generates different colors to the human eye and/or spectrum channels in a digital image. The methods described herein use stains that specifically identify and make evident tumor cells.

An additional method of staining is immunohistochemistry. Immunohistochemistry (IHC) can identify the region of the tissue, the cells of the tissue, and the subcellular region(s) of the cell that contain a specific protein and/or peptide. IHC uses a primary antibody that specifically binds to a particular target protein and/or peptide, whereby a tissue section on a surface, such as a slide, is incubated with the primary antibody so that the primary antibody binds to its target protein and/or peptide as it resides within the regions and cells of the tissue.

The tissue section is then incubated in the presence of a secondary antibody that specifically binds the primary antibody. The secondary antibody is labeled so that it is possible to see where binding has occurred. For example, the secondary antibody can be engineered with a specific molecule, such as an enzyme, that has the ability to elicit a chemical reaction when contacted treatment with other chemicals to render a specific color. The tissue is then incubated under various biochemical conditions with specific other chemical reagents designed to impart the specific color to the secondary antibody. Thus, where the secondary antibody binds its primary antibody target that is where the colorimetric stain will present. Using a primary antibody specific for tumor cells can be highly desirable for the presently described invention.

Chemical reagents that induce colorimetric stains in an immunohistochemical and/or in situ RNA hybridization assay include but are not limited to 3,3'-Diaminoben/idine, 5-Bromo-4- chloro-3-indolyl phosphate, methyl green, PTAH, toluidine blue, PAS, luxol fast blue, and Wright's stain. There are also many ways in which to develop a fluorescent stain using fluorescent signal emission molecules to impart a specific color to an immunohistochemical and/or in situ RNA hybridization assay including, but not limited to, fluorescein, carboxyfluorescein, rhodamine, coumarin, and cyanine. The skilled artisan will recognize that the methods described herein can use essentially any method to identify and highlight tumor cells within cancer patient tumor tissue, including standard histology and/or immunohistochemical methodology. An effective and typical way of identifying tumor cells is carried out by visualization of where stains are imparted to the tissue and cells by the methods previously described including but not limited to standard histological stains and/or IHC. Various colors can be imparted to the tissue and cells using these methods whereby tumor cells can show a different staining color than other tissue features such as benign cells, non-cellular material, stromal cells, and lymphocytes.

In addition, tumor cells can show physical and morphological features that differ from benign, non-tumor cells such as stroma and lymphocytes. A trained histologist/pathologist is able to use a combination of knowledge comprising unique staining colors and unique morphological features of tumor cells, benign non-tumor cells, and non-cellular tissue regions to identify the tumor cells for collection from cancer patient tumor tissue.

Once tumor cells have been identified, via histological staining, they can be collected for mass spectrometry proteomic analysis using for example the technology of tissue microdissection. Many commercial tissue microdissection instmments, protocols, and methods are known in the art and can be used to collect tumor cells, and other cell types, from stained tissue sections. Tumor tissue contains many types of cells including tumor epithelial cells, normal epithelial cells, fibroblastic connective cells, and immune cells. In order to understand the molecular status of the tumor cells they must be separated and collected from the heterogeneous mixture of tumor tissue cells. Laser Capture Microdissection (LCM) technology can be used to achieve this separation (see, for example, US Patent No. 6,867,038). LCM as well as other tissue microdissection technologies have improved the analysis of tissue samples by allowing molecular profiling of cells derived from tissue samples that can be placed in a pathologically relevant context.

Other tissue microdissection technologies also are commercially available, including the PixCell systems (Arcturus), the PALM system (PALM Microlaser Technologies), the uCuT (Molecular Machines and Industries), the Leica AS LMD (Leica Microsystems), the LaserScissors (Cell Robotics), the MicroDis sector (Eppendorf), xMD (xMDx), and the Clonis system (Bio-Rad). Any one of these tissue microdissection methods can be employed to collect tumor cells, and other cell types, in the presently described methods for mass spectrometric analysis of cancer neoantigens expressed in tumor cells obtained from cancer patient tumor tissue. Other tissue microdissection methods not involving one of the above-mentioned methods and instruments designed to perform those methods can also be employed to collect tumor cells, and other cell types, in the presently described methods for mass spectrometric analysis of cancer neoantigens expressed in tumor cells obtained from cancer patient tumor tissue.

Surgically-collected, preserved, and stored cancer patient tumor tissue is analyzed in the presently described method, and the most common methods of preserving and storing surgically removed patient tumor tissue are: 1) snap freezing in liquid nitrogen and subsequent storage at - 80C to -140C, 2) fixing in ethanol and embedding in paraffin followed by subsequent room temperature storage, and 3) fixing in formalin and embedding in paraffin followed by subsequent storage at room temperature. All three forms of preserved tissue can be used for analysis of cancer neoantigenic peptides in cancer patient tumor tissue using the presently described method.

The most widely available form of tissue, including tumor tissue, from cancer patients for use in the presently described method is formalin fixed, paraffin embedded tissue (FFPE). Formaldehyde/formalin fixation of surgically removed tissue is by far the most common method of preserving cancer tissue samples worldwide and is the accepted convention in standard pathology practice. Aqueous solutions of formaldehyde are referred to as formalin. “100%” formalin is a saturated solution of formaldehyde (about 40% by volume or 37% by mass) in water, with a small amount of stabilizer (usually methanol), to limit oxidation and degree of polymerization. The most common way to preserve tissue is to soak whole tissue for extended periods of time (8 hours to 48 hours) in aqueous formaldehyde, commonly termed 10% neutral buffered formalin, followed by embedding the fixed whole tissue in paraffin wax for long term storage at room temperature. The presently described methods allow analysis and identification of cancer neoantigenic peptides directly in cells procured from FFPE tissue.

Preparing a peptide lysate from histopathologically-processed frozen tissue, ethanol-fixed tissue, or formalin fixed paraffin embedded tissue can be performed using steps that are well known in the art. In general, tissue is placed in a buffer, with or without a detergent (surfactant), and maintained at elevated temperature for some period of time. The temperature and/or time can be varied as necessary. The tissue/buffer mixture optionally may be agitated or shaken during the elevated temperature step, at which point the peptides can be separated out for mass spectrometry analysis from partial-length or full-length proteins and bits of insoluble tissue. Fractionation methods that can be used for this separation include, but are not limited to, spin- column separation, centrifugation, gel electrophoresis, isoelectric focusing, and any other chromatography. The peptide mixture can then be injected directly into a mass spectrometer for analysis or dried down and reconstituted in buffers suitable for mass spectrometry analysis.

Expression of specific proteins and peptides on the surface of tumor cells that function to mask the tumor cells from the patient’s own immune surveillance system have been the focus of targeted cancer therapy approaches in recent years. A number of biological molecules and small molecules have been developed by the pharmaceutical industry to interact with these types of masking proteins whereby new cancer therapy molecules function to unmask the tumor cells and allow the patient’s own immune system to identify the tumor cells as foreign to the body thus mounting a tumor-killing immune response to the tumor cells. Expression of these immune system-masking proteins is effectively analyzed by the presently described methods using mass spectrometry for either “global profiling” or “targeted” analysis to detect and identify cancer neoantigenic peptides expressed by tumor cells which are most likely presented on the cell surface of the tumor cells collected by tissue microdissection of patient tumor tissue.

In addition to the cancer therapeutic agents that specifically kill tumor cells by inhibiting the function of oncoproteins that are driving tumor cell growth, the presence of cancer neoantigenic peptides bound, or not bound, to the MHC complex on the cell surface of tumor cells can also be exploited to act as patient-specific immunotherapy targets for such therapies as vaccine targets. These cancer neoantigens can be considered patient-specific cancer antigens (neoantigens) for use in arming the patient’s own immune system to attack and kill the tumor cells expressing such cancer neoantigens. Discovery, identification, analysis, and determining the amino acid sequence of cancer neoantigenic peptides is the focus of the presently described method through precise analysis of cancer neoantigenic peptides expressed in tumor cells and determining which are most likely to be presented by the MHC complex on the outer surface of said tumor cells obtained directly from cancer patient tumor tissue.

The described method is used to inform a cancer therapeutic strategy, or combination of strategies, for inhibiting tumor cell growth in a cancer patient and for determining appropriate therapy for the patient. This is done by matching cancer therapeutic agents with those cancer proteins or cancer neoantigenic peptides found aberrantly expressed in the tumor cells and which are determined, using bioinformatic software/tools, to demonstrate a high statistical probability of residing directly on the surface of the tumor cells procured from cancer patient tumor tissue. Any given cancer treatment strategy targets specific proteins and/or specific peptides present in the tumor cells, or on the outer surface of said tumor cells, whereby the most optimal biological, small molecule, chemotherapeutic, cancer vaccine, and/or immunomodulatory treatment strategy is directly matched to the molecular characteristics of the patient’s own tumor cells. Small molecules and standard chemotherapeutic agents function by binding to specific, targeted proteins to inhibit their function and thus kill the tumor cell.

Immunomodulatory agents and cancer vaccines function to elicit an immune response from the patient to that patient’s own tumor cells. Treating a patient with more than one of these treatment strategies can be more effective in general than treating with only one of these strategies because tumor cells frequently express one or more such target proteins and/or peptides simultaneously, imparting dmg resistance to the tumor cell. It is much more difficult for a tumor cell to simultaneously evade and develop resistance to multiple agents. Accordingly, it is particularly advantageous to design treatment strategies using a combination of a biological agent such as cetuximab, a small molecule biochemical agent such as lapatinib, a standard chemotherapeutic agent such as gemcitabine, an immunomodulatory agent such as nivolumab, and/or a cancer vaccine agent that targets a cancer neoantigenic peptide(s) identified from patient tumor cells.

The presently described methods precisely collect tumor cells from cancer patient tumor tissue and analyze the expressed peptide content of the tumor cells to discover, identify, analyze, quantitate, and detect expression of tumor cell-specific, cancer neoantigenic peptides that demonstrate a high statistical probability to reside on the tumor cell surface and that can act as diagnostic targets to provide for individualized cancer patient immunotherapy strategies. This information can be combined with information about other proteins derived from SRM/MRM data for a combined treatment approach.

One embodiment of the methods described herein is diagrammed in Figure 1. A section of cancer patient tumor tissue is used to collect only the tumor cells from the tissue section. The methodology of tissue microdissection may or may not be used to collect the tumor cells. A peptide lysate is prepared from the collect tumor cells and the lysate is subsequently analyzed by mass spectrometry. The mass spectrometer advantageously can use EThcD (energy transfer higher energy collision dissociation) for identifying peptides and where bioinformatics software such as MASCOT (Matrix Science), MaxQuant (Max Planck Institute for Biochemistry),

Sequest, Scaffold (Proteome Software), and Skyline (Sciex) can be used to determine the complete amino acid sequence of small peptides expressed in the tumor cells. Once the sequence of each candidate cancer neoantigen has been determined, bioinformatics software such as NetMHCpan, MixMHC2pred, ImmuneEpitope, Immunogenicity, PEPVAC, RankPep, MARIA, and DeepLigand can be used to identify and confirm which peptides demonstrate a high statistical probability to be bound by the MHC presentation complex, and thus which peptides are present on the tumor cell surface. These cancer neoantigen peptides can be targeted by cancer immunotherapy agents and strategies that include, but are not limited to, small molecules, metabolites, antibodies, cancer vaccines, lymphocytes, and various forms of activated immunological cells such as natural killer cells and other modified/activated T lymphocytes.

Description of Method

Patient tumor tissue is used for the presently described method whereby tumor cells are procured directly from histologically-processed cancer patient tumor tissue and analyzed by mass spectrometry in order to detect, identify, and quantitate candidate cancer neoantigenic peptides that are expressed explicitly in by the tumor cells. The amino acid sequence of each candidate cancer neoantigen peptide is then bioinformatically analyzed using one or more available software tools in order to identify which of the candidates demonstrates statistically significant probability to bind to MHC complex molecules and reside on the outside of the tumor cell surface, this identifying and confirming one or more cancer neoantigens that reside on the tumor cell surface and that can be targeted by cancer immunotherapy strategies. Patient tumor tissue can take the form of either frozen tissue, ethanol fixed tissue, or formalin fixed paraffin embedded tissue. All forms of tissue are equally useful for this presently described method. Prior to collecting tumor cells, the tissue section is stained using standard staining methods such as hematoxylin/eosin and IHC to uniquely identify tumor cells from other tissue microenvironment features such as normal epithelial cells, normal endothelial cells, immunological cells, and intercellular spaces.

Once tumor cells have been collected a protein/peptide lysate suitable for analysis by mass spectrometry is prepared. Mass spectrometry is used to detect, identify, discover, and quantitate candidate cancer neoantigenic peptides expressed within tumor cells following one or more of the modes previously described to achieve either a “global profile” and/or a “targeted” analysis of peptides. Bioinformatics software such as MASCOT, MaxQuant, Sequest, Scaffold, and Skyline is used on mass spectrometry -generated data to determine the amino acid sequence of each peptide. Amino acid sequences for each of the candidate cancer neoantigen peptides are analyzed using bioinformatic software tools such as but not limited to NetMHCpan, MixMHC2pred, ImmuneEpitope, Immunogenicity, PEPVAC, RankPep, MARIA, and DeepLigand to identify which of the candidate peptides demonstrate a high statistical probability to bind to MHC complexes on the surface of the tumor cells thus identifying and confirming those peptides as cancer neoantigens and targets against which cancer immunotherapeutic strategies can be developed. Peptides considered to be confirmed cancer neoantigens are: 1) peptides that originate in exon regions of the tumor cell genome that contain (exon neoantigen) an amino acid change different from the normal genome coding sequence which is a direct result of a non- synonymous mutation present in the tumor cell genome, and 2) those that do not originate in the tumor cell genome wherein these peptides result from proteasome-generated splicing of smaller, previously unrelated peptides which are termed proteasome generated spliced epitopes (PGSEs), and 3) whereby suspected exon or PGSE neoantigens comprise one or more of the canonical MHC binding motifs at peptide positions PI, P2, P7, P9, and/or the last amino acid in the peptide and show a high statistical probability of residing on the surface of tumor cells as determined by one or more of the following software tools NetMHCpan, MixMHC2pred, ImmuneEpitope, Immunogenicity, PEPVAC, RankPep, MARIA, and DeepLigand.

The presence of these neoantigens on the surface of patient tumor cells can be exploited as targets for immunotherapeutic agents such as cancer vaccines, peptide vaccines, targeted antibodies, T lymphocytes, modified T lymphocytes, and natural killer cells. Once statistically- significant target cancer neoantigens have been identified these immunotherapies can be engineered to attack tumor cells that present these newly-identified peptides on their cell surface for efficient tumor cell killing.

Identification, discovery, analysis, detected expression, and determined presence of cancer neoantigenic peptides on the outside surface of the tumor cells directly obtained from cancer patient tumor tissue holds great potential and promise to dramatically advance personalized cancer immunotherapy. When used in combination with targeted therapeutic agents that target other proteins and peptides that reside on, or do not reside on, the tumor cell surface provides a combined therapeutic approach that will further that potential and promise.