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  • Perspective
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OPINION

Alternative tumour-specific antigens

Abstract

The study of tumour-specific antigens (TSAs) as targets for antitumour therapies has accelerated within the past decade. The most commonly studied class of TSAs are those derived from non-synonymous single-nucleotide variants (SNVs), or SNV neoantigens. However, to increase the repertoire of available therapeutic TSA targets, ‘alternative TSAs’, defined here as high-specificity tumour antigens arising from non-SNV genomic sources, have recently been evaluated. Among these alternative TSAs are antigens derived from mutational frameshifts, splice variants, gene fusions, endogenous retroelements and other processes. Unlike the patient-specific nature of SNV neoantigens, some alternative TSAs may have the advantage of being widely shared by multiple tumours, allowing for universal, off-the-shelf therapies. In this Opinion article, we will outline the biology, available computational tools, preclinical and/or clinical studies and relevant cancers for each alternative TSA class, as well as discuss both current challenges preventing the therapeutic application of alternative TSAs and potential solutions to aid in their clinical translation.

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Fig. 1: Summary of tumour-specific antigen production in the tumour cell.
Fig. 2: Average tumour-specific antigen counts by cancer type.
Fig. 3: Computational workflow for tumour-specific antigen calling.

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References

  1. Yarchoan, M. et al. Targeting neoantigens to augment antitumour immunity. Nat. Rev. Cancer 17, 209–222 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Sahin, U. et al. Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature 547, 222–226 (2017).

    CAS  PubMed  Google Scholar 

  3. Ott, P. A. et al. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature 547, 217–221 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Gubin, M. M. et al. Tumor neoantigens: building a framework for personalized cancer immunotherapy. J. Clin. Invest. 125, 3413–3421 (2015).

    PubMed  PubMed Central  Google Scholar 

  5. Hacohen, N. et al. Getting personal with neoantigen-based therapeutic cancer vaccines. Cancer Immunol. Res. 1, 11–15 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Schumacher, T. N. & Schreiber, R. D. Neoantigens in cancer immunotherapy. Science 348, 69–74 (2015).

    CAS  PubMed  Google Scholar 

  7. Cristescu, R. et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science 362, eaar3593 (2018).

    PubMed  PubMed Central  Google Scholar 

  8. Keskin, D. B. et al. Neoantigen vaccine generates intratumoral T cell responses in phase Ib glioblastoma trial. Nature 565, 234–239 (2019).

    CAS  PubMed  Google Scholar 

  9. Hilf, N. et al. Actively personalized vaccination trial for newly diagnosed glioblastoma. Nature 565, 240–245 (2019).

    CAS  PubMed  Google Scholar 

  10. Turajlic, S. et al. Insertion-and-deletion-derived tumour-specific neoantigens and the immunogenic phenotype: a pan-cancer analysis. Lancet Oncol. 18, 1009–1021 (2017).

    CAS  PubMed  Google Scholar 

  11. Smith, C. C. et al. Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma. J. Clin. Invest. 128, 4804–4820 (2018).

    PubMed  PubMed Central  Google Scholar 

  12. Thorsson, V. et al. The immune landscape of cancer. Immunity 48, 812–830 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Mertens, F., Antonescu, C. R. & Mitelman, F. Gene fusions in soft tissue tumors: recurrent and overlapping pathogenetic themes. Genes Chromosomes Cancer 55, 291–310 (2016).

    CAS  PubMed  Google Scholar 

  14. Wang, Y. et al. Recurrent fusion genes in leukemia: an attractive target for diagnosis and treatment. Curr. Genomics 18, 378–384 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Pellagatti, A. et al. Impact of spliceosome mutations on RNA splicing in myelodysplasia: dysregulated genes/pathways and clinical associations. Blood 132, 1225–1240 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Bartel, F., Taubert, H. & Harris, L. C. Alternative and aberrant splicing of MDM2 mRNA in human cancer. Cancer Cell 2, 9–15 (2002).

    CAS  PubMed  Google Scholar 

  17. Perz, J. F. et al. The contributions of hepatitis B virus and hepatitis C virus infections to cirrhosis and primary liver cancer worldwide. J. Hepatol. 45, 529–538 (2006).

    PubMed  Google Scholar 

  18. Ambrosio, M. R. & Leoncini, L. in Tropical Hemato-Oncology (eds Droz, J.-P. et al.) 127–141 (Springer International Publishing, 2015).

  19. Mahieux, R. & Gessain, A. HTLV-1 and associated adult T cell leukemia/lymphoma. Rev. Clin. Exp. Hematol. 7, 336–361 (2003).

    PubMed  Google Scholar 

  20. Mesri, E. A., Cesarman, E. & Boshoff, C. Kaposi’s sarcoma herpesvirus/ Human herpesvirus-8 (KSHV/HHV8), and the oncogenesis of Kaposi’s sarcoma. Nat. Rev. Cancer 10, 707–719 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Harrington, W. J., Wood, C. & Wood, C. in DNA Tumor Viruses (eds Pipas, J. & Damania, B.) 683–702 (Springer, 2009).

  22. Shukla, S. A. et al. Comprehensive analysis of cancer-associated somatic mutations in class i HLA genes. Nat. Biotechnol. 33, 1152–1158 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Szolek, A. et al. OptiType: precision HLA typing from next-generation sequencing data. Bioinformatics 30, 3310–3316 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Bai, Y., Wang, D. & Fury, W. PHLAT: inference of high-resolution HLA types from RNA and whole exome sequencing. Methods Mol. Biol. 1802, 193–201 (2018).

    CAS  PubMed  Google Scholar 

  25. Ka, S. et al. HLAscan: genotyping of the HLA region using next-generation sequencing data. BMC Bioinformatics 18, 258 (2017).

    PubMed  PubMed Central  Google Scholar 

  26. Buchkovich, M. L. et al. HLAProfiler utilizes k-mer profiles to improve HLA calling accuracy for rare and common alleles in RNA-seq data. Genome Med. 9, 86 (2017).

    PubMed  PubMed Central  Google Scholar 

  27. Jurtz, V. et al. NetMHCpan-4.0: improved peptide–MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data. J. Immunol. 199, 3360–3368 (2017).

    CAS  PubMed  Google Scholar 

  28. Rajasagi, M. et al. Systematic identification of personal tumor-specific neoantigens in chronic lymphocytic leukemia. Blood 124, 453–462 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Soria-Guerra, R. E. et al. An overview of bioinformatics tools for epitope prediction: implications on vaccine development. J. Biomed. Inform. 53, 405–414 (2015).

    PubMed  Google Scholar 

  30. Zhang, Q. et al. Immune epitope database analysis resource (IEDB-AR). Nucleic Acids Res. 36, W513–W518 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Linnebacher, M. et al. Frameshift peptide-derived T cell epitopes: a source of novel tumor-specific antigens. Int. J. Cancer 93, 6–11 (2001).

    CAS  PubMed  Google Scholar 

  32. Thibodeau, S. N., Bren, G. & Schaid, D. Microsatellite instability in cancer of the proximal colon. Science 260, 816–819 (1993).

    CAS  PubMed  Google Scholar 

  33. Ionov, Y. et al. Ubiquitous somatic mutations in simple repeated sequences reveal a new mechanism for colonic carcinogenesis. Nature 363, 558–561 (1993).

    CAS  PubMed  Google Scholar 

  34. Sakurada, K. et al. RIZ, the retinoblastoma protein interacting zinc finger gene, is mutated in genetically unstable cancers of the pancreas, stomach, and colorectum. Genes Chromosomes Cancer 30, 207–211 (2001).

    CAS  PubMed  Google Scholar 

  35. De Smedt, L. et al. Microsatellite instable versus stable colon carcinomas: analysis of tumour heterogeneity, inflammation and angiogenesis. Br. J. Cancer 113, 500–509 (2015).

    PubMed  PubMed Central  Google Scholar 

  36. Dolcetti, R. et al. High prevalence of activated intraepithelial cytotoxic T lymphocytes and increased neoplastic cell apoptosis in colorectal carcinomas with microsatellite instability. Am. J. Pathol. 154, 1805–1813 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Maby, P. et al. Correlation between density of CD8+ T cell infiltrate in microsatellite unstable colorectal cancers and frameshift mutations: a rationale for personalized immunotherapy. Cancer Res. 75, 3446–3455 (2015).

    CAS  PubMed  Google Scholar 

  38. Tougeron, D. et al. Tumor-infiltrating lymphocytes in colorectal cancers with microsatellite instability are correlated with the number and spectrum of frameshift mutations. Mod. Pathol. 22, 1186–1195 (2009).

    CAS  PubMed  Google Scholar 

  39. Saeterdal, I. et al. TGF betaRII frameshift-mutation-derived CTL epitope recognised by HLA-A2-restricted CD8+ T cells. Cancer Immunol. Immunother. 50, 469–476 (2001).

    CAS  PubMed  Google Scholar 

  40. Le, D. T. et al. PD-1 blockade in tumors with mismatch-repair deficiency. N. Engl. J. Med. 372, 2509–2520 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Gong, J. et al. Development of PD-1 and PD-L1 inhibitors as a form of cancer immunotherapy: a comprehensive review of registration trials and future considerations. J. Immunother. Cancer 6, 8 (2018).

    PubMed  PubMed Central  Google Scholar 

  42. Motzer, R. J. et al. Nivolumab versus everolimus in advanced renal-cell carcinoma. N. Engl. J. Med. 373, 1803–1813 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Hundal, J. et al. pVAC-Seq: a genome-guided in silico approach to identifying tumor neoantigens. Genome Med. 8, 11 (2016).

    PubMed  PubMed Central  Google Scholar 

  44. Kim, S. et al. Neopepsee: accurate genome-level prediction of neoantigens by harnessing sequence and amino acid immunogenicity information. Ann. Oncol. 29, 1030–1036 (2018).

    CAS  PubMed  Google Scholar 

  45. Bjerregaard, A. M. et al. MuPeXI: prediction of neo-epitopes from tumor sequencing data. Cancer Immunol. Immunother. 66, 1123–1130 (2017).

    CAS  PubMed  Google Scholar 

  46. Rubinsteyn, A. et al. Computational pipeline for the PGV-001 neoantigen vaccine trial. Front. Immunol. 8, 1807 (2018).

    PubMed  PubMed Central  Google Scholar 

  47. Rech, A. J. et al. Tumor immunity and survival as a function of alternative neopeptides in human cancer. Cancer Immunol. Res. 6, 276–287 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Zhou, Z. et al. TSNAD: an integrated software for cancer somatic mutation and tumour-specific neoantigen detection. R. Soc. Open Sci. 4, 170050 (2017).

    PubMed  PubMed Central  Google Scholar 

  49. Saunders, C. T. et al. Strelka: Accurate somatic small-variant calling from sequenced tumor-normal sample pairs. Bioinformatics 28, 1811–1817 (2012).

    Google Scholar 

  50. Saeterdal, I. et al. Frameshift-mutation-derived peptides as tumor-specific antigens in inherited and spontaneous colorectal cancer. Proc. Natl Acad. Sci. USA 98, 13255–13260 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Inderberg, E. M. et al. T cell therapy targeting a public neoantigen in microsatellite instable colon cancer reduces in vivo tumor growth. Oncoimmunology 6, e1302631 (2017).

    PubMed  PubMed Central  Google Scholar 

  52. Jayasinghe, R. G. et al. Systematic analysis of splice-site-creating mutations in cancer. Cell Rep. 23, 270–281 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Yang, Y. et al. Aberrant splicing induced by missense mutations in BRCA1: clues from a humanized mouse model. Hum. Mol. Genet. 12, 2121–2131 (2003).

    CAS  PubMed  Google Scholar 

  54. Nyström-Lahti, M. et al. Missense and nonsense mutations in codon 659 of MLHI cause aberrant splicing of messenger RNA in HNPCC kindreds. Genes Chromosomes Cancer 26, 372–375 (1999).

    PubMed  Google Scholar 

  55. Zhang, K. et al. Patterns of missplicing caused by RB1 gene mutations in patients with retinoblastoma and association with phenotypic expression. Hum. Mutat. 29, 475–484 (2008).

    CAS  PubMed  Google Scholar 

  56. Wadt, K. et al. A cryptic BAP1 splice mutation in a family with uveal and cutaneous melanoma, and paraganglioma. Pigment Cell Melanoma Res. 25, 815–818 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Chen, L. L. et al. A mutation-created novel intra-exonic pre-mRNA splice site causes constitutive activation of KIT in human gastrointestinal stromal tumors. Oncogene 24, 4271–4280 (2005).

    CAS  PubMed  Google Scholar 

  58. Smart, A. C. et al. Intron retention is a source of neoepitopes in cancer. Nat. Biotechnol. 36, 1056–1058 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Jung, H. et al. Intron retention is a widespread mechanism of tumor-suppressor inactivation. Nat. Genet. 47, 1242–1248 (2015).

    CAS  PubMed  Google Scholar 

  60. Dvinge, H. & Bradley, R. K. Widespread intron retention diversifies most cancer transcriptomes. Genome Med. 7, 45 (2015).

    PubMed  PubMed Central  Google Scholar 

  61. Kawakami, S. A. et al. The intronic region of an incompletely spliced gp100 gene transcript encodes an epitope recognized by melanoma-reactive tumor-infiltrating lymphocytes. J. Immunol. 159, 303–308 (1997).

    PubMed  Google Scholar 

  62. Coulie, P. G. et al. A mutated intron sequence codes for an antigenic peptide recognized by cytolytic T lymphocytes on a human melanoma. Proc. Natl Acad. Sci. USA 92, 7976–7980 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Uenaka, A. et al. Cryptic CTL epitope on a murine sarcoma Meth A generated by exon extension as a novel mechanism. J. Immunol. 170, 4862–4868 (2003).

    CAS  PubMed  Google Scholar 

  64. Boultwood, J. et al. The role of splicing factor mutations in the pathogenesis of the myelodysplastic syndromes. Adv. Biol. Regul. 54, 153–161 (2014).

    CAS  PubMed  Google Scholar 

  65. Yip, B. H. et al. Impact of splicing factor mutations on pre-mRNA splicing in the myelodysplastic syndromes. Curr. Pharm. Des. 22, 2333–2344 (2016).

    CAS  PubMed  Google Scholar 

  66. Weiss, R. B. et al. Slippery runs, shifty stops, backward steps, and forward hops: -2, -1, +1, +2, +5, and +6 ribosomal frameshifting. Cold Spring Harb. Symp. Quant. Biol. 52, 687–693 (1987).

    CAS  PubMed  Google Scholar 

  67. Saulquin, X. et al. +1 Frameshifting as a novel mechanism to generate a cryptic cytotoxic T lymphocyte epitope derived from human interleukin 10. J. Exp. Med. 195, 353–358 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Macejak, D. G. & Sarnow, P. Internal initiation of translation mediated by the 5’ leader of a cellular mRNA. Nature 353, 90–94 (1991).

    CAS  PubMed  Google Scholar 

  69. Bullock, T. N. J. et al. Initiation codon scanthrough versus termination codon readthrough demonstrates strong potential for major histocompatibility complex class I–restricted cryptic epitope expression. J. Exp. Med. 186, 1051–1058 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Bullock, T. N. Ribosomal scanning past the primary initiation codon as a mechanism for expression of CTL epitopes encoded in alternative reading frames. J. Exp. Med. 184, 1319–1329 (1996).

    CAS  PubMed  Google Scholar 

  71. Malarkannan, S. et al. Presentation of out-of-frame peptide/MHC class I complexes by a novel translation initiation mechanism. Immunity 10, 681–690 (1999).

    CAS  PubMed  Google Scholar 

  72. Van Den Eynde, B. J. et al. A new antigen recognized by cytolytic T lymphocytes on a human kidney tumor results from reverse strand transcription. J. Exp. Med. 190, 1793–1800 (1999).

    PubMed Central  Google Scholar 

  73. Bruce, A., Atkins, J. & Gesteland, R. tRNA anticodon replacement experiments show that ribosomal frameshifting can be caused by doublet decoding. Proc. Natl Acad. Sci. USA 83, 5062–5066 (1986).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. Dalet, A. et al. An antigenic peptide produced by reverse splicing and double asparagine deamidation. Proc. Natl Acad. Sci. USA 108, E323–E331 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Hanada, K. I., Yewdell, J. W. & Yang, J. C. Immune recognition of a human renal cancer antigen through post-translational protein splicing. Nature 427, 252–256 (2004).

    CAS  PubMed  Google Scholar 

  76. Liepe, J. et al. A large fraction of HLA class I ligands are proteasome-generated spliced peptides. Science 354, 354–358 (2016).

    CAS  PubMed  Google Scholar 

  77. Kahles, A. et al. Comprehensive analysis of alternative splicing across tumors from 8,705 patients. Cancer Cell 34, 211–224 (2018).

    CAS  PubMed  Google Scholar 

  78. Shukla, G. C. & Singh, J. Mutations of RNA splicing factors in hematological malignancies. Cancer Lett. 409, 1–8 (2017).

    CAS  PubMed  Google Scholar 

  79. Ley, T. J. et al. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N. Engl. J. Med. 368, 2059–2074 (2013).

    PubMed  Google Scholar 

  80. Adamia, S. et al. A genome-wide aberrant RNA Splicing in patients with acute myeloid leukemia identifies novel potential disease markers and therapeutic targets. Clin. Cancer Res. 20, 1135–1145 (2014).

    CAS  PubMed  Google Scholar 

  81. Wang, L. et al. SF3B1 and other novel cancer genes in chronic lymphocytic leukemia. N. Engl. J. Med. 365, 2497–2506 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  82. Yoshida, K. et al. Frequent pathway mutations of splicing machinery in myelodysplasia. Nature 478, 64–69 (2011).

    CAS  PubMed  Google Scholar 

  83. Kar, S. A. et al. Spliceosomal gene mutations are frequent events in the diverse mutational spectrum of chronic myelomonocytic leukemia but largely absent in juvenile myelomonocytic leukemia. Haematologica 98, 107–113 (2013).

    PubMed  PubMed Central  Google Scholar 

  84. Visconte, V. et al. Emerging roles of the spliceosomal machinery in myelodysplastic syndromes and other hematological disorders. Leukemia 26, 2447–2454 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  85. Quesada, V. et al. Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia. Nat. Genet. 44, 47–52 (2012).

    CAS  Google Scholar 

  86. Lee, S. C. W. et al. Modulation of splicing catalysis for therapeutic targeting of leukemia with mutations in genes encoding spliceosomal proteins. Nat. Med. 22, 672–678 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Lim, K. H. & Fairbrother, W. G. Spliceman - a computational web server that predicts sequence variations in pre-mRNA splicing. Bioinformatics 28, 1031–1032 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Mort, M. et al. MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing. Genome Biol. 15, R19 (2014).

    PubMed  PubMed Central  Google Scholar 

  89. Brooks, A. N. et al. Conservation of an RNA regulatory map between Drosophila and mammals. Genome Res. 21, 193–202 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Rogers, M. F. et al. SpliceGrapher: detecting patterns of alternative splicing from RNA-Seq data in the context of gene models and EST data. Genome Biol. 13, R4 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  91. Shen, S. et al. rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data. Proc. Natl Acad. Sci. USA 111, E5593–E5601 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Kahles, A. et al. SplAdder: identification, quantification and testing of alternative splicing events from RNA-Seq data. Bioinformatics 32, 1840–1847 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  93. Denti, L. et al. ASGAL: aligning RNA-Seq data to a splicing graph to detect novel alternative splicing events. BMC Bioinformatics 19, 444 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  94. US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT02721043 (2019).

  95. Shyu, A. B., Wilkinson, M. F. & Van Hoof, A. Messenger RNA regulation: to translate or to degrade. EMBO J. 27, 471–481 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  96. Crainie, M. et al. Overexpression of the receptor for hyaluronan-mediated motility (RHAMM) characterizes the malignant clone in multiple myeloma: identification of three distinct RHAMM variants. Blood 93, 1684–1696 (1999).

    CAS  PubMed  Google Scholar 

  97. Busse, A. et al. Wilms’ tumor gene 1 (WT1) expression in subtypes of acute lymphoblastic leukemia (ALL) of adults and impact on clinical outcome. Ann. Hematol. 88, 1199–1205 (2009).

    CAS  PubMed  Google Scholar 

  98. Kramarzova, K. et al. Real-time PCR quantification of major Wilms tumor gene 1 (WT1) isoforms in acute myeloid leukemia, their characteristic expression patterns and possible functional consequences. Leukemia 26, 2086–2095 (2012).

    CAS  PubMed  Google Scholar 

  99. Siehl, J. M. et al. Expression of Wilms’ tumor gene 1 at different stages of acute myeloid leukemia and analysis of its major splice variants. Ann. Hematol. 83, 745–750 (2004).

    PubMed  Google Scholar 

  100. Mailänder, V. et al. Complete remission in a patient with recurrent acute myeloid leukemia induced by vaccination with WT1 peptide in the absence of hematological or renal toxicity. Leukemia 18, 165–166 (2004).

    PubMed  Google Scholar 

  101. Kohrt, H. E. et al. Donor immunization with WT1 peptide augments antileukemic activity after MHC-matched bone marrow transplantation. Blood 118, 5319–5329 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  102. Oka, Y. et al. Wilms tumor gene peptide-based immunotherapy for patients with overt leukemia from myelodysplastic syndrome (MDS) or MDS with myelofibrosis. Int. J. Hematol. 78, 56–61 (2003).

    CAS  PubMed  Google Scholar 

  103. Rosenfeld, C., Cheever, M. A. & Gaiger, A. WT1 in acute leukemia, chronic myelogenous leukemia and myelodysplastic syndrome: therapeutic potential of WT1 targeted therapies. Leukemia 17, 1301–1312 (2003).

    CAS  PubMed  Google Scholar 

  104. Chapuis, A. G. et al. Transferred WT1-reactive CD8+ T cells can mediate antileukemic activity and persist in post-transplant patients. Sci. Transl Med. 5, 174ra27 (2013).

    PubMed  PubMed Central  Google Scholar 

  105. Tsuboi, A. et al. WT1 peptide-based immunotherapy for patients with lung cancer: report of two cases. Microbiol. Immunol. 48, 175–184 (2004).

    CAS  PubMed  Google Scholar 

  106. Iiyama, T. et al. WT1 (Wilms’ tumor 1) peptide immunotherapy for renal cell carcinoma. Microbiol. Immunol. 51, 519–530 (2007).

    CAS  PubMed  Google Scholar 

  107. Kawase, T. et al. Alternative splicing due to an intronic SNP in HMSD generates a novel minor histocompatibility antigen. Blood 110, 1055–1063 (2007).

    CAS  PubMed  Google Scholar 

  108. Vauchy, C. et al. CD20 alternative splicing isoform generates immunogenic CD4 helper T epitopes. Int. J. Cancer 137, 116–126 (2015).

    CAS  PubMed  Google Scholar 

  109. Rowley, J. D. A new consistent chromosomal abnormality in chronic myelogenous leukaemia identified by quinacrine fluorescence and Giemsa staining. Nature 243, 290–293 (1973).

    CAS  PubMed  Google Scholar 

  110. Williams, S. V., Hurst, C. D. & Knowles, M. A. Oncogenic FGFR3 gene fusions in bladder cancer. Hum. Mol. Genet. 22, 795–803 (2013).

    CAS  PubMed  Google Scholar 

  111. Tognon, C. et al. Expression of the ETV6-NTRK3 gene fusion as a primary event in human secretory breast carcinoma. Cancer Cell 2, 367–376 (2002).

    CAS  PubMed  Google Scholar 

  112. The Cancer Genome Atlas Network. Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 499, 43–49 (2013).

    Google Scholar 

  113. Seshagiri, S. et al. Recurrent R-spondin fusions in colon cancer. Nature 488, 660–664 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  114. Young, L. C. et al. Identification of novel isoforms of the EML4-ALK transforming gene in non-small cell lung cancer. Cancer Res. 68, 4971–4976 (2008).

    Google Scholar 

  115. Lyu, X. et al. Detection of 22 common leukemic fusion genes using a single-step multiplex qRT-PCR-based assay. Diagn. Pathol. 12, 55 (2017).

    PubMed  PubMed Central  Google Scholar 

  116. Xiao, X. et al. Advances in chromosomal translocations and fusion genes in sarcomas and potential therapeutic applications. Cancer Treat. Rev. 63, 61–70 (2018).

    CAS  PubMed  Google Scholar 

  117. Worley, B. S. et al. Antigenicity of fusion proteins from sarcoma-associated. Cancer Res. 61, 6868–6875 (2001).

    CAS  PubMed  Google Scholar 

  118. Druker, B. J. et al. Efficacy and safety of a specific inhibitor of the BCR–ABL tyrosine kinase in chronic myeloid leukemia. N. Engl. J. Med. 344, 1031–1037 (2001).

    CAS  PubMed  Google Scholar 

  119. Jamal-Hanjani, M. et al. Tracking the evolution of non–small-cell lung cancer. N. Engl. J. Med. 376, 2109–2121 (2017).

    CAS  PubMed  Google Scholar 

  120. McGranahan, N. et al. Allele-Specific HLA loss and immune escape in lung cancer evolution. Cell 171, 1259–1271 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  121. Rosenthal, R. et al. Neoantigen-directed immune escape in lung cancer evolution. Nature 567, 479–485 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  122. Yu, Y. P. et al. Identification of recurrent fusion genes across multiple cancer types. Sci. Rep. 9, 1074 (2019).

    PubMed  PubMed Central  Google Scholar 

  123. Wang, Q. et al. Application of next generation sequencing to human gene fusion detection: computational tools, features and perspectives. Brief. Bioinform. 14, 506–519 (2013).

    CAS  PubMed  Google Scholar 

  124. Zhang, J., Mardis, E. R. & Maher, C. A. INTEGRATE-neo: a pipeline for personalized gene fusion neoantigen discovery. Bioinformatics 33, 555–557 (2017).

    CAS  PubMed  Google Scholar 

  125. Chang, T. C. et al. The neoepitope landscape in pediatric cancers. Genome Med. 9, 78 (2017).

    PubMed  PubMed Central  Google Scholar 

  126. Pinilla-Ibarz, J. et al. Vaccination of patients with chronic myelogenous leukemia with bcr–abl oncogene breakpoint fusion peptides generates specific immune responses. Blood 95, 1781–1787 (2000).

    CAS  PubMed  Google Scholar 

  127. Cathcart, K. et al. A multivalent bcr–abl fusion peptide vaccination trial in patients with chronic myeloid leukemia. Blood 103, 1037–1042 (2004).

    CAS  PubMed  Google Scholar 

  128. Mackall, C. L. et al. A pilot study of consolidative immunotherapy in patients with high-risk pediatric sarcomas. Clin. Cancer Res. 14, 4850 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  129. Bocchia, M. et al. Effect of a p210 multipeptide vaccine associated with imatinib or interferon in patients with chronic myeloid leukaemia and persistent residual disease: a multicentre observational trial. Lancet 365, 657–662 (2005).

    CAS  PubMed  Google Scholar 

  130. Rojas, J. M. et al. Clinical evaluation of BCR–ABL peptide immunisation in chronic myeloid leukaemia: results of the EPIC study. Leukemia 21, 2287–2295 (2007).

    CAS  PubMed  Google Scholar 

  131. Yang, W. et al. Immunogenic neoantigens derived from gene fusions stimulate T cell responses. Nat. Med. 25, 767–775 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  132. Goodier, J. L. & Kazazian, H. H. Retrotransposons revisited: the restraint and rehabilitation of parasites. Cell 135, 23–35 (2008).

    CAS  PubMed  Google Scholar 

  133. Shen, H. et al. Integrated molecular characterization of testicular germ cell tumors. Cell Rep. 23, 3392–3406 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  134. Florl, A. R. et al. DNA methylation and expression of LINE-1 and HERV-K provirus sequences in urothelial and renal cell carcinomas. Br. J. Cancer 80, 1312–1321 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  135. Brocks, D. et al. DNMT and HDAC inhibitors induce cryptic transcription start sites encoded in long terminal repeats. Nat. Genet. 49, 1052–1060 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  136. Chiappinelli, K. B. et al. Inhibiting DNA methylation causes an interferon response in cancer via dsRNA including endogenous retroviruses. Cell 162, 974–986 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  137. Sheng, W. et al. LSD1 ablation stimulates anti-tumor immunity and enables checkpoint blockade. Cell 174, 549–563 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  138. Goel, S. et al. CDK4/6 inhibition triggers anti-tumour immunity. Nature 548, 471–475 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  139. Jones, P. A. et al. Epigenetic therapy in immune-oncology. Nat. Rev. Cancer 19, 151–161 (2019).

    CAS  PubMed  Google Scholar 

  140. Belgnaoui, S. M. et al. Human LINE-1 retrotransposon induces DNA damage and apoptosis in cancer cells. Cancer Cell Int. 6, 13 (2006).

    PubMed  PubMed Central  Google Scholar 

  141. Scott, E. C. et al. A hot L1 retrotransposon evades somatic repression and initiates human colorectal cancer. Genome Res. 26, 745–755 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  142. Chen, L. et al. Prognostic value of LINE-1 retrotransposon expression and its subcellular localization in breast cancer. Breast Cancer Res. Treat. 136, 129–142 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  143. Patnala, R. et al. Inhibition of LINE-1 retrotransposon-encoded reverse transcriptase modulates the expression of cell differentiation genes in breast cancer cells. Breast Cancer Res. Treat. 143, 239–253 (2014).

    CAS  PubMed  Google Scholar 

  144. Löwer, R., Löwer, J. & Kurth, R. The viruses in all of us: characteristics and biological significance of human endogenous retrovirus sequences. Proc. Natl Acad. Sci. USA 93, 5177–5184 (1996).

    PubMed  PubMed Central  Google Scholar 

  145. Boller, K. et al. Human endogenous retrovirus HERV-K113 is capable of producing intact viral particles. J. Gen. Virol. 89, 567–572 (2008).

    CAS  PubMed  Google Scholar 

  146. Faff, O. et al. Retrovirus-like particles from the human T47D cell line are related to mouse mammary tumour virus and are of human endogenous origin. J. Gen. Virol. 73, 1087–1097 (1992).

    CAS  PubMed  Google Scholar 

  147. Wang-Johanning, F. et al. Expression of multiple human endogenous retrovirus surface envelope proteins in ovarian cancer. Int. J. Cancer 120, 81–90 (2007).

    CAS  PubMed  Google Scholar 

  148. Büscher, K. et al. Expression of human endogenous retrovirus K in melanomas and melanoma cell lines. Cancer Res. 65, 4172–4180 (2005).

    PubMed  Google Scholar 

  149. Wang-Johanning, F. et al. Expression of human endogenous retrovirus K envelope transcripts in human breast cancer. Clin. Cancer Res. 7, 1553–1560 (2001).

    CAS  PubMed  Google Scholar 

  150. Contreras-Galindo, R. et al. Human endogenous retrovirus K (HML-2) elements in the plasma of people with lymphoma and breast cancer. J. Virol. 82, 9329–9336 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  151. Wang-Johanning, F. et al. Detecting the expression of human endogenous retrovirus E envelope transcripts in human prostate adenocarcinoma. Cancer 98, 187–197 (2003).

    CAS  PubMed  Google Scholar 

  152. Yoshida, M., Miyoshi, I. & Hinuma, Y. Isolation and characterization of retrovirus from cell lines of human adult T cell leukemia and its implication in the disease. Proc. Natl Acad. Sci. USA 79, 2031–2035 (1982).

    CAS  PubMed  PubMed Central  Google Scholar 

  153. Kalyanaraman, V. S. et al. A new subtype of human T cell leukemia virus (HTLV-II) associated with a T cell variant of hairy cell leukemia. Science 218, 571–573 (1982).

    CAS  PubMed  Google Scholar 

  154. Sauter, M. et al. Human endogenous retrovirus K10: expression of Gag protein and detection of antibodies in patients with seminomas. J. Virol. 69, 414–421 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  155. Cherkasova, E. et al. Detection of an immunogenic HERV-E envelope with selective expression in clear cell kidney cancer. Cancer Res. 76, 2177–2185 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  156. Takahashi, Y. et al. Regression of human kidney cancer following allogeneic stem cell transplantation is associated with recognition of an HERV-E antigen by T cells. J. Clin. Invest. 118, 1099–1109 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  157. Panda, A. et al. Endogenous retrovirus expression is associated with response to immune checkpoint pathway in clear cell renal cell carcinoma. JCI Insight 3, 121522 (2018).

    PubMed  Google Scholar 

  158. Rooney, M. S. et al. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell 160, 48–61 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  159. Mayer, J., Blomberg, J. & Seal, R. L. A revised nomenclature for transcribed human endogenous retroviral loci. Mob. DNA 2, 7 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  160. Cherkasova, E. et al. Inactivation of the von Hippel–Lindau tumor suppressor leads to selective expression of a human endogenous retrovirus in kidney cancer. Oncogene 30, 4697–4706 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  161. Vargiu, L. et al. Classification and characterization of human endogenous retroviruses; mosaic forms are common. Retrovirology 13, 7 (2016).

    PubMed  PubMed Central  Google Scholar 

  162. Tokuyama, M. et al. ERVmap analysis reveals genome-wide transcription of human endogenous retroviruses. Proc. Natl Acad. Sci. USA 115, 12565–12572 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  163. Smit, A., Hubley, R. & Green, P. RepeatMasker Open — 4.0. RepeatMasker http://www.repeatmasker.org/ (2013).

  164. Paces, J. HERVd: the human endogenous retroviruses database: update. Nucleic Acids Res. 32, 50D (2004).

    Google Scholar 

  165. Kim, T. H. et al. HESAS: HERVs expression and structure analysis system. Bioinformatics 21, 1699–1700 (2005).

    CAS  PubMed  Google Scholar 

  166. Tongyoo, P. et al. EnHERV: enrichment analysis of specific human endogenous retrovirus patterns and their neighboring genes. PLOS ONE 12, e0177119 (2017).

    PubMed  PubMed Central  Google Scholar 

  167. US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03354390 (2019).

  168. Brandle, D. A mutated HLA-A2 molecule recognized by autologous cytotoxic T lymphocytes on a human renal cell carcinoma. J. Exp. Med. 183, 2501–2508 (1996).

    CAS  PubMed  Google Scholar 

  169. Huang, J. et al. T cells associated with tumor regression recognize frameshifted products of the CDKN2A tumor suppressor gene locus and a mutated HLA class I gene product. J. Immunol. 172, 6057–6064 (2014).

    Google Scholar 

  170. Van Hall, T. et al. Selective cytotoxic T-lymphocyte targeting of tumor immune escape variants. Nat. Med. 12, 417–424 (2006).

    PubMed  Google Scholar 

  171. Doorduijn, E. M. et al. TAP-independent self-peptides enhance T cell recognition of immune-escaped tumors. J. Clin. Invest. 126, 784–794 (2016).

    PubMed  PubMed Central  Google Scholar 

  172. Marijt, K. A., Doorduijn, E. M. & van Hall, T. TEIPP antigens for T cell based immunotherapy of immune-edited HLA class Ilow cancers. Mol. Immunol. https://doi.org/10.1016/j.molimm.2018.03.029 (2018).

  173. Doorduijn, E. M. et al. T cells specific for a TAP-independent self-peptide remain naïve in tumor-bearing mice and are fully exploitable for therapy. Oncoimmunology 7, e1382793 (2018).

    PubMed  Google Scholar 

  174. Marijt, K. A. et al. Identification of non-mutated neoantigens presented by TAP-deficient tumors. J. Exp. Med. 215, 2325–2337 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  175. Lansford, J. L. et al. Computational modeling and confirmation of leukemia-associated minor histocompatibility antigens. Blood Adv. 2, 2052–2062 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  176. Kreiter, S. et al. Mutant MHC class II epitopes drive therapeutic immune responses to cancer. Nature 520, 692–696 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  177. Tran, E. et al. Cancer immunotherapy based on mutation-specific CD4+ T cells in a patient with epithelial cancer. Science 344, 641–645 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  178. Andreatta, M. et al. Machine learning reveals a non-canonical mode of peptide binding to MHC class II molecules. Immunology 152, 255–264 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  179. Nielsen, M. & Lund, O. NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction. BMC Bioinformatics 10, 296 (2009).

    PubMed  PubMed Central  Google Scholar 

  180. Andreatta, M. et al. Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification. Immunogenetics 67, 641–650 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  181. Saito, R. et al. Molecular subtype-specific immunocompetent models of high-grade urothelial carcinoma reveal differential neoantigen expression and response to immunotherapy. Cancer Res. 78, 3954–3968 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  182. The problem with neoantigen prediction [editorial]. Nat. Biotechnol. 35, 97 (2017).

  183. Pearson, H. et al. MHC class I-associated peptides derive from selective regions of the human genome. J. Clin. Invest. 126, 4690–4701 (2016).

    PubMed  PubMed Central  Google Scholar 

  184. Creech, A. L. et al. The role of mass spectrometry and proteogenomics in the advancement of HLA epitope prediction. Proteomics 18, e1700259 (2018).

    PubMed  Google Scholar 

  185. Hunt, D. F. et al. Characterization of peptides bound to the class I MHC molecule HLA-A2.1 by mass spectrometry. Science 255, 1261–1263 (1992).

    CAS  PubMed  Google Scholar 

  186. Falk, K. et al. Allele-specific motifs revealed by sequencing of self-peptides eluted from MHC molecules. Nature 351, 290–296 (1991).

    CAS  PubMed  Google Scholar 

  187. Michalski, A., Cox, J. & Mann, M. More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS. J. Proteome Res. 10, 1785–1793 (2011).

    CAS  PubMed  Google Scholar 

  188. Griss, J. et al. Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets. Nat. Methods 13, 651–656 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  189. Yaqüe, J. et al. Peptide rearrangement during quadrupole ion trap fragmentation: added complexity to MS/MS spectra. Anal. Chem. 75, 1524–1535 (2003).

    Google Scholar 

  190. Chawner, R. et al. Peptide scrambling during collision-induced dissociation is influenced by n-terminal residue basicity. J. Am. Soc. Mass Spectrom. 25, 1927–1938 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  191. Yadav, M. et al. Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing. Nature 515, 572–576 (2014).

    CAS  PubMed  Google Scholar 

  192. Polyakova, A., Kuznetsova, K. & Moshkovskii, S. Proteogenomics meets cancer immunology: mass spectrometric discovery and analysis of neoantigens. Expert Rev. Proteomics 12, 533–541 (2015).

    CAS  PubMed  Google Scholar 

  193. Laumont, C. M. et al. Noncoding regions are the main source of targetable tumor-specific antigens. Sci. Transl Med. 10, eaau5516 (2018).

    CAS  PubMed  Google Scholar 

  194. van der Lee, D. I. et al. Mutated nucleophosmin 1 as immunotherapy target in acute myeloid leukemia. J. Clin. Invest. 129, 774–785 (2019).

    PubMed  PubMed Central  Google Scholar 

  195. Matsushita, H. et al. Cancer exome analysis reveals a T cell-dependent mechanism of cancer immunoediting. Nature 482, 400–404 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  196. Castle, J. C. et al. Exploiting the mutanome for tumor vaccination. Cancer Res. 72, 1081–1091 (2012).

    CAS  PubMed  Google Scholar 

  197. Gubin, M. M. et al. Checkpoint blockade cancer immunotherapy targets tumour-specific mutant antigens. Nature 515, 577–581 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  198. Carreno, B. M. et al. A dendritic cell vaccine increases the breadth and diversity of melanoma neoantigen-specific T cells. Science 348, 803–808 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  199. Gao, Q. et al. Driver fusions and their implications in the development and treatment of human cancers. Cell Rep. 23, 227–238 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  200. Selitsky, S. R. et al. Epstein-Barr virus-positive cancers show altered B-cell clonality. mSystems 3, e00081–18 (2018).

    PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was supported by the US National Institutes of Health grants F30 CA225136 (to C.C.S.), U54 CA198999 (to J.S.S.) and P50 CA058223 (to J.S.S.), as well as by a grant from the UNC University Cancer Research Fund (to B.G.V.) and a Susan G. Komen Career Catalyst Research Grant (to B.G.V.).

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Contributions

C.C.S., S.C., S.R.S. and P.M.A. researched the data for the article. All authors provided substantial contributions to discussion of the content. C.C.S. and P.M.A. wrote the article, and C.C.S. generated figures. All authors contributed to the review and editing of the manuscript prior to submission.

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Correspondence to Benjamin G. Vincent or Jonathan S. Serody.

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Nature Reviews Cancer thanks T. Van Hall, L. Delamarre and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Glossary

Apheresis

Medical technique used to purify various components of whole blood. Apheresis can be performed to harvest purified T lymphocytes for subsequent immunotherapeutic application.

Artificial neural networks

A class of computational modelling based on biological neural networks, able to implement change based on training input and output information to form an optimized prediction model.

Binding core

The segment of polypeptide on an antigenic peptide responsible for interaction with the major histocompatibility complex binding groove. The binding core is recognized as an important predictor for binding affinity, but binding is also influenced by other factors of the epitope sequence.

Cancer–testis antigens

Antigens whose expression is limited to cancer cells and reproductive tissues but not adult somatic tissue.

Cytogenic response

A decrease in the number of cells with a particular chromosomal trait (classically associated with the BCR–ABL gene fusion) in response to therapy.

Doublet decoding

Translational process by which an amino acid is translated from a two-base-pair codon rather than the conventional three-base-pair codon. This process can result in -1 frameshifting during translation.

Epitope

Specific portion of the antigen specifically recognized by a T or B cell receptor.

HLA typing

Process for identifying the HLA receptor allele of a particular tissue. This can be performed through a variety of molecular or immunological techniques.

Immunogenomic analysis

Study of the combined genomics of the cancer cell and immune cell components of a tumour.

Insertion or deletion

(INDEL). Insertion of bases into or deletion of them from the genome of an organism, typically in the context of a mutation or genetic variation.

KD

Dissociation constant that measures the concentration of a ligand necessary to reversibly bind half of its corresponding molecular pair. In the context of peptide–major histocompatibility complex (MHC) binding, this refers to the concentration of peptide necessary to bind half of all MHC molecules.

Lynch syndrome

Also known as hereditary nonpolyposis colorectal cancer. An autosomal-dominant genetic disorder of DNA mismatch repair, resulting in increased risk of microsatellite instability-driven colon cancer (among other cancer types).

Myelodysplastic syndrome

A class of low-grade malignancies in which abnormal bone marrow stem cells fail to fully mature.

Negative selection

Process by which self-reactive T lymphocytes are deleted during T cell education in the thymus.

Neoantigens

Antigens specific to the genome of the cancer cell.

Nonsense-mediated decay

Checkpoint by which mRNA transcripts containing premature stop codons are eliminated in order to reduce aberrant translation.

Post-translational splicing

Post-translational excision of polypeptides, with subsequent ligation of the carboxy- and amino-terminal residues.

Predicted neoantigens

Genomically predicted neoantigens with unconfirmed tumour expression and/or in vivo immunogenicity.

Quantitative trait loci

Sections of DNA (loci) that are correlated with particular qualitative traits (or phenotypes) in an organismal population.

Retroelements

Genetic elements capable of self-amplification, found within the genome of eukaryotic organisms. Retrotransposon DNA can be transcribed into RNA, converted back into identical DNA via reverse transcription, and then inserted into the genome at particular target sites. Retroelements include retrotransposons and endogenous retroviruses.

Retrotransposons

A subset of retroelement in eukaryotic cells that possesses some characteristics of retroviruses and transposes through an RNA intermediary.

Ribosomal frameshifting

Process by which codons are translated in an out-of-frame manner via slippage of the ribosome into a +/- 1 or 2 base-pair position.

Segmental duplications

Long segments of repeated DNA (1-400 kb) with highly conserved sequences (>90%) that exist in the genome as a result of duplication events.

Spliceosome

Molecular machinery responsible for removal (splicing) of introns from pre-mRNA.

Tandem mass spectrometry

Multiple-step mass spectrometry (MS), whereby the sample is first ionized for separation in the first MS stage, followed by fragmentation for separation in the second MS stage.

Translocation breakpoints

Locations where two fragments of chromosome(s) are joined subsequent to chromosomal translocation.

Tumour antigens

Any antigen produced by the tumour cell, typically in the setting of enriched or specific expression relative to normal tissue(s).

Tumour-associated antigens

Antigens whose expression is enriched (but not specific) to cancer cells.

Tumour-specific antigens

(TSAs). Antigens (molecules capable of promoting an adaptive immune response) expressed by the tumour with minimal to no expression in normal tissue.

Viral-derived cancer antigens

Antigens expressed by cancer cells derived from an oncogenic viral origin.

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Smith, C.C., Selitsky, S.R., Chai, S. et al. Alternative tumour-specific antigens. Nat Rev Cancer 19, 465–478 (2019). https://doi.org/10.1038/s41568-019-0162-4

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