Checkpoint blockade cancer immunotherapy targets tumour-specific mutant antigens
Matthew M Gubin, Xiuli Zhang, Heiko Schuster, Etienne Caron, Jeffrey P Ward, Takuro Noguchi, Yulia Ivanova, Jasreet Hundal, Cora D Arthur, Willem-Jan Krebber, Gwenn E Mulder, Mireille Toebes, Matthew D Vesely, Samuel S K Lam, Alan J Korman, James P Allison, Gordon J Freeman, Arlene H Sharpe, Erika L Pearce, Ton N Schumacher, Ruedi Aebersold, Hans-Georg Rammensee, Cornelis J M Melief, Elaine R Mardis, William E Gillanders, Maxim N Artyomov, Robert D Schreiber, Matthew M Gubin, Xiuli Zhang, Heiko Schuster, Etienne Caron, Jeffrey P Ward, Takuro Noguchi, Yulia Ivanova, Jasreet Hundal, Cora D Arthur, Willem-Jan Krebber, Gwenn E Mulder, Mireille Toebes, Matthew D Vesely, Samuel S K Lam, Alan J Korman, James P Allison, Gordon J Freeman, Arlene H Sharpe, Erika L Pearce, Ton N Schumacher, Ruedi Aebersold, Hans-Georg Rammensee, Cornelis J M Melief, Elaine R Mardis, William E Gillanders, Maxim N Artyomov, Robert D Schreiber
Abstract
The immune system influences the fate of developing cancers by not only functioning as a tumour promoter that facilitates cellular transformation, promotes tumour growth and sculpts tumour cell immunogenicity, but also as an extrinsic tumour suppressor that either destroys developing tumours or restrains their expansion. Yet, clinically apparent cancers still arise in immunocompetent individuals in part as a consequence of cancer-induced immunosuppression. In many individuals, immunosuppression is mediated by cytotoxic T-lymphocyte associated antigen-4 (CTLA-4) and programmed death-1 (PD-1), two immunomodulatory receptors expressed on T cells. Monoclonal-antibody-based therapies targeting CTLA-4 and/or PD-1 (checkpoint blockade) have yielded significant clinical benefits-including durable responses--to patients with different malignancies. However, little is known about the identity of the tumour antigens that function as the targets of T cells activated by checkpoint blockade immunotherapy and whether these antigens can be used to generate vaccines that are highly tumour-specific. Here we use genomics and bioinformatics approaches to identify tumour-specific mutant proteins as a major class of T-cell rejection antigens following anti-PD-1 and/or anti-CTLA-4 therapy of mice bearing progressively growing sarcomas, and we show that therapeutic synthetic long-peptide vaccines incorporating these mutant epitopes induce tumour rejection comparably to checkpoint blockade immunotherapy. Although mutant tumour-antigen-specific T cells are present in progressively growing tumours, they are reactivated following treatment with anti-PD-1 and/or anti-CTLA-4 and display some overlapping but mostly treatment-specific transcriptional profiles, rendering them capable of mediating tumour rejection. These results reveal that tumour-specific mutant antigens are not only important targets of checkpoint blockade therapy, but they can also be used to develop personalized cancer-specific vaccines and to probe the mechanistic underpinnings of different checkpoint blockade treatments.
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References
- Shankaran V, et al. IFNgamma and lymphocytes prevent primary tumour development and shape tumour immunogenicity. Nature. 2001;410:1107–1111. doi: 10.1038/35074122.
- Dunn GP, Bruce AT, Ikeda H, Old LJ, Schreiber RD. Cancer immunoediting: from immunosurveillance to tumor escape. Nature immunology. 2002;3:991–998. doi: 10.1038/ni1102-991.
- Mantovani A, Allavena P, Sica A, Balkwill F. Cancer-related inflammation. Nature. 2008;454:436–444. doi: 10.1038/nature07205.
- Grivennikov SI, Greten FR, Karin M. Immunity, inflammation, and cancer. Cell. 2010;140:883–899. doi: 10.1016/j.cell.2010.01.025.
- Trinchieri G. Cancer and inflammation: an old intuition with rapidly evolving new concepts. Annual review of immunology. 2012;30:677–706. doi: 10.1146/annurev-immunol-020711-075008.
- Coussens LM, Zitvogel L, Palucka AK. Neutralizing tumor-promoting chronic inflammation: a magic bullet? Science. 2013;339:286–291. doi: 10.1126/science.1232227.
- Koebel CM, et al. Adaptive immunity maintains occult cancer in an equilibrium state. Nature. 2007;450:903–907. doi: 10.1038/nature06309.
- Quezada SA, Peggs KS, Simpson TR, Allison JP. Shifting the equilibrium in cancer immunoediting: from tumor tolerance to eradication. Immunological reviews. 2011;241:104–118. doi: 10.1111/j.1600-065X.2011.01007.x.
- Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer. 2012;12:252–264. doi: 10.1038/nrc3239.
- Wolchok JD, et al. Nivolumab plus ipilimumab in advanced melanoma. N Engl J Med. 2013;369:122–133. doi: 10.1056/NEJMoa1302369.
- Hamid O, et al. Safety and tumor responses with lambrolizumab (anti-PD-1) in melanoma. N Engl J Med. 2013;369:134–144. doi: 10.1056/NEJMoa1305133.
- Topalian SL, et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. The New England journal of medicine. 2012;366:2443–2454. doi: 10.1056/NEJMoa1200690.
- Hodi FS, et al. Improved survival with ipilimumab in patients with metastatic melanoma. The New England journal of medicine. 363:711–723.
- Matsushita H, et al. Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature. 482:400–404.
- Paul S, et al. HLA class I alleles are associated with peptide-binding repertoires of different size, affinity, and immunogenicity. Journal of immunology. 2013;191:5831–5839. doi: 10.4049/jimmunol.1302101.
- West EE, et al. Tight regulation of memory CD8(+) T cells limits their effectiveness during sustained high viral load. Immunity. 2011;35:285–298. doi: 10.1016/j.immuni.2011.05.017.
- Wherry EJ. T cell exhaustion. Nat Immunol. 2011;12:492–499.
- Castle JC, et al. Exploiting the mutanome for tumor vaccination. Cancer research. 72:1081–1091.
- Robbins PF, et al. Mining exomic sequencing data to identify mutated antigens recognized by adoptively transferred tumor-reactive T cells. Nature medicine. 2013;19:747–752. doi: 10.1038/nm.3161.
- Fritsch EF, et al. HLA-binding properties of tumor neoepitopes in humans. Cancer immunology research. 2014;2:522–529. doi: 10.1158/2326-6066.CIR-13-0227.
- van Rooij N, et al. Tumor exome analysis reveals neoantigen-specific T-cell reactivity in an ipilimumab-responsive melanoma. Journal of clinical oncology: official journal of the American Society of Clinical Oncology. 2013;31:e439–442. doi: 10.1200/JCO.2012.47.7521.
- Curran MA, Montalvo W, Yagita H, Allison JP. PD-1 and CTLA-4 combination blockade expands infiltrating T cells and reduces regulatory T and myeloid cells within B16 melanoma tumors. Proceedings of the National Academy of Sciences of the United States of America. 2010;107:4275–4280. doi: 10.1073/pnas.0915174107.
- Brunner MC, et al. CTLA-4-Mediated inhibition of early events of T cell proliferation. Journal of immunology. 1999;162:5813–5820.
- Keir ME, Butte MJ, Freeman GJ, Sharpe AH. PD-1 and its ligands in tolerance and immunity. Annual review of immunology. 2008;26:677–704. doi: 10.1146/annurev.immunol.26.021607.090331.
- Okazaki T, Chikuma S, Iwai Y, Fagarasan S, Honjo T. A rheostat for immune responses: the unique properties of PD-1 and their advantages for clinical application. Nature immunology. 14:1212–1218.
- Duraiswamy J, Kaluza KM, Freeman GJ, Coukos G. Dual blockade of PD-1 and CTLA-4 combined with tumor vaccine effectively restores T-cell rejection function in tumors. Cancer research. 2013;73:3591–3603.
- Spiotto MT, Rowley DA, Schreiber H. Bystander elimination of antigen loss variants in established tumors. Nature medicine. 2004;10:294–298. doi: 10.1038/nm999.
- Wolkers MC, Brouwenstijn N, Bakker AH, Toebes M, Schumacher TN. Antigen bias in T cell cross-priming. Science. 2004;304:1314–1317. doi: 10.1126/science.1096268.
- Corbiere V, et al. Antigen spreading contributes to MAGE vaccination-induced regression of melanoma metastases. Cancer research. 2011;71:1253–1262. doi: 10.1158/0008-5472.CAN-10-2693.
- Tran E, et al. Cancer immunotherapy based on mutation-specific CD4+ T cells in a patient with epithelial cancer. Science. 2014;344:641–645. doi: 10.1126/science.1251102.
- Hildner K, et al. Batf3 deficiency reveals a critical role for CD8alpha+ dendritic cells in cytotoxic T cell immunity. Science. 2008;322:1097–1100. doi: 10.1126/science.1164206.
- Peters B, Sette A. Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method. BMC Bioinformatics. 2005;6:132. doi: 10.1186/1471-2105-6-132.
- Lundegaard C, et al. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11. Nucleic Acids Res. 2008;36:W509–512. doi: 10.1093/nar/gkn202.
- Hoof I, et al. NetMHCpan, a method for MHC class I binding prediction beyond humans. Immunogenetics. 2009;61:1–13. doi: 10.1007/s00251-008-0341-z.
- Nielsen M, Lundegaard C, Lund O, Kesmir C. The role of the proteasome in generating cytotoxic T-cell epitopes: insights obtained from improved predictions of proteasomal cleavage. Immunogenetics. 2005;57:33–41. doi: 10.1007/s00251-005-0781-7.
- Esquivel F, Yewdell J, Bennink J. RMA/S cells present endogenously synthesized cytosolic proteins to class I-restricted cytotoxic T lymphocytes. The Journal of experimental medicine. 1992;175:163–168.
- Toebes M, et al. Design and use of conditional MHC class I ligands. Nature medicine. 2006;12:246–251. doi: 10.1038/nm1360.
- Andersen RS, et al. Parallel detection of antigen-specific T cell responses by combinatorial encoding of MHC multimers. Nature protocols. 2012;7:891–902. doi: 10.1038/nprot.2012.037.
- Kvistborg P, et al. TIL therapy broadens the tumor-reactive CD8(+) T cell compartment in melanoma patients. Oncoimmunology. 2012;1:409–418.
- Kowalewski DJ, Stevanovic S. Biochemical large-scale identification of MHC class I ligands. Methods in molecular biology. 2013;960:145–157. doi: 10.1007/978-1-62703-218-6_12.
- Thommen DS, et al. Two preferentially expressed proteins protect vascular endothelial cells from an attack by peptide-specific CTL. Journal of immunology. 2012;188:5283–5292. doi: 10.4049/jimmunol.1101506.
- Domon B, Aebersold R. Options and considerations when selecting a quantitative proteomics strategy. Nature biotechnology. 2010;28:710–721. doi: 10.1038/nbt.1661.
- MacLean B, et al. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics. 26:966–968.
- Lange V, Picotti P, Domon B, Aebersold R. Selected reaction monitoring for quantitative proteomics: a tutorial. Mol Syst Biol. 2008;4:222.
- Escher C, et al. Using iRT, a normalized retention time for more targeted measurement of peptides. Proteomics. 2012;12:1111–1121. doi: 10.1002/pmic.201100463.
- Subramanian A, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America. 2005;102:15545–15550. doi: 10.1073/pnas.0506580102.
Source: PubMed