Somatic mutations can induce a noninflamed tumour microenvironment via their original gene functions, despite deriving neoantigens

Published in Cancer
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Cancer is characterized by the acquisition of immune escape mechanisms (1). Cancer immunotherapy with immune checkpoint inhibitors (ICIs) improves dysfunctional cytotoxic effector CD8+ T cells, leading to tumor regression (2, 3). ICIs have been demonstrated to be effective against diverse cancer types, leading to a paradigm shift in cancer treatment (4-6). However, more than half of patients do not respond to ICIs. Therefore, the need to identify biomarkers to predict the response to ICIs is imperative in clinical settings. Despite numerous basic and clinical studies on biomarkers, accurate prediction of response remains elusive.

Somatic mutation-derived neoantigens, which can be recognized as non-self, elicit strong immune responses (7, 8). Thus, neoantigens are presumed to induce an inflamed tumor microenvironment (TME), which is essential for the ICI response, and the number of neoantigens is reportedly correlated with the inflamed TME (8-10). Therefore, tumor mutational burden (TMB) is one of the predictive biomarker candidates for ICIs (9, 11, 12). However, there have been some conflicting data about this neoantigen theory (13, 14). Tumors also evade antitumor immunity through “immune editing”, which involves the elimination of highly immunogenic tumor cells or mutation of their own human leukocyte antigen (HLA) molecules to decrease antigen presentation (15-18). Furthermore, in the process of accumulating somatic mutations, certain cancer signaling pathways promote immune evasion (19-24).

In this study, we evaluated 88 MSI-H colorectal cancer patients and identified that fs mutations in the driver gene RNF43 were shared neoantigens among patients, as previously reported (25). Tumors with neoantigens derived from these RNF43 frameshift (fs) mutations tended to have an inflamed TME, which is consistent with the neoantigen theory. However, our study revealed variations in the TME among the different RNF43 frameshift mutations. RNF43 is a tumor suppressor gene that suppresses the WNT/β-catenin signaling pathway, which previously reported to suppress antitumor immunity (20, 23). We demonstrated that RNF43 117fs is a loss-of-function mutation that activates the WNT/β-catenin signaling pathway, while RNF43 659fs was comparable to RNF43 WT (26-30). In addition, the WNT/β-catenin signaling pathway activation resulting from loss-of-function fs mutations led to a noninflamed TME even in the presence of neoantigens and resistance to PD-1 blockade in mouse models. We also validated these results using The Cancer Genome Atlas (TCGA) datasets, and demonstrated that passenger rather than driver gene mutations were related to the inflamed TME. Thus, even if such functional driver gene mutations become neoantigens, patients with these neoantigens could have a noninflamed TME because of gene functions.

In summary, we propose a novel concept of “paradoxical neoantigenic mutations” that can induce the noninflamed TME due to their original gene functions, despite deriving neoantigens. Our findings highlight the importance of evaluating the qualities as well as quantities of neoantigenic mutations.

 

  1. Dunn GP, Old LJ, Schreiber RD. The immunobiology of cancer immunosurveillance and immunoediting. Immunity. 2004;21(2):137-48.
  2. Tumeh PC, Harview CL, Yearley JH, Shintaku IP, Taylor EJ, Robert L, et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature. 2014;515(7528):568-71.
  3. Zou W, Wolchok JD, Chen L. PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: Mechanisms, response biomarkers, and combinations. Science Translational Medicine. 2016;8(328):328rv4-rv4.
  4. Brahmer JR, Tykodi SS, Chow LQ, Hwu WJ, Topalian SL, Hwu P, et al. Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. N Engl J Med. 2012;366(26):2455-65.
  5. Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF, et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 2012;366(26):2443-54.
  6. Kang Y-K, Boku N, Satoh T, Ryu M-H, Chao Y, Kato K, et al. Nivolumab in patients with advanced gastric or gastro-oesophageal junction cancer refractory to, or intolerant of, at least two previous chemotherapy regimens (ONO-4538-12, ATTRACTION-2): a randomised, double-blind, placebo-controlled, phase 3 trial. The Lancet. 2017;390(10111):2461-71.
  7. Schumacher TN, Schreiber RD. Neoantigens in cancer immunotherapy. Science. 2015;348(6230):69-74.
  8. Matsushita H, Vesely MD, Koboldt DC, Rickert CG, Uppaluri R, Magrini VJ, et al. Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature. 2012;482(7385):400-4.
  9. Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348(6230):124-8.
  10. Rooney Michael S, Shukla Sachet A, Wu Catherine J, Getz G, Hacohen N. Molecular and Genetic Properties of Tumors Associated with Local Immune Cytolytic Activity. Cell. 2015;160(1):48-61.
  11. Cristescu R, Mogg R, Ayers M, Albright A, Murphy E, Yearley J, et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science. 2018;362(6411).
  12. Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky JM, Desrichard A, et al. Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma. New England Journal of Medicine. 2014;371(23):2189-99.
  13. McGrail DJ, Pilié PG, Rashid NU, Voorwerk L, Slagter M, Kok M, et al. High tumor mutation burden fails to predict immune checkpoint blockade response across all cancer types. Ann Oncol. 2021;32:661–72.
  14. Voorwerk L, Slagter M, Horlings HM, Sikorska K, van de Vijver KK, de Maaker M, et al. Immune induction strategies in metastatic triple-negative breast cancer to enhance the sensitivity to PD-1 blockade: the TONIC trial. Nature Medicine. 2019;25(6):920-8.
  15. Milo I, Bedora-Faure M, Garcia Z, Thibaut R, Périé L, Shakhar G, et al. The immune system profoundly restricts intratumor genetic heterogeneity. Sci Immunol. 2018;3(29).
  16. Schreiber RD, Old LJ, Smyth MJ. Cancer immunoediting: integrating immunity's roles in cancer suppression and promotion. Science. 2011;331(6024):1565-70.
  17. Montesion M, Murugesan K, Jin DX, Sharaf R, Sanchez N, Guria A, et al. Somatic HLA Class I Loss Is a Widespread Mechanism of Immune Evasion Which Refines the Use of Tumor Mutational Burden as a Biomarker of Checkpoint Inhibitor Response. Cancer Discov. 2021;11(2):282-92.
  18. Kawazu M, Ueno T, Saeki K, Sax N, Togashi Y, Kaneseki T, et al. HLA Class I analysis provides insight into the genetic and epigenetic background of immune evasion in colorectal cancer with high microsatellite instability. Gastroenterology. 2022;162:799–812.
  19. Keenan TE, Burke KP, Van Allen EM. Genomic correlates of response to immune checkpoint blockade. Nat Med. 2019;25(3):389-402.
  20. Spranger S, Gajewski TF. Impact of oncogenic pathways on evasion of antitumour immune responses. Nat Rev Cancer. 2018;18(3):139-47.
  21. Sugiyama E, Togashi Y, Takeuchi Y, Shinya S, Tada Y, Kataoka K, et al. Blockade of EGFR improves responsiveness to PD-1 blockade in EGFR-mutated non-small cell lung cancer. Sci Immunol. 2020;5(43).
  22. Kumagai S, Togashi Y, Sakai C, Kawazoe A, Kawazu M, Ueno T, et al. An Oncogenic Alteration Creates a Microenvironment that Promotes Tumor Progression by Conferring a Metabolic Advantage to Regulatory T Cells. Immunity. 2020;53(1):187-203.e8.
  23. Spranger S, Bao R, Gajewski TF. Melanoma-intrinsic β-catenin signalling prevents anti-tumour immunity. Nature. 2015;523(7559):231-5.
  24. Takeuchi Y, Tanegashima T, Sato E, Irie T, Sai A, Itahashi K, et al. Highly immunogenic cancer cells require activation of the WNT pathway for immunological escape. Science Immunology. 2021;6(65):eabc6424.
  25. Roudko V, Bozkus CC, Orfanelli T, McClain CB, Carr C, O'Donnell T, et al. Shared Immunogenic Poly-Epitope Frameshift Mutations in Microsatellite Unstable Tumors. Cell. 2020;183(6):1634-49.e17.
  26. Li S, Lavrijsen M, Bakker A, Magierowski M, Magierowska K, Liu P, et al. Commonly observed RNF43 mutations retain functionality in attenuating Wnt/β-catenin signaling and unlikely confer Wnt-dependency onto colorectal cancers. Oncogene. 2020;39(17):3458-72.
  27. Thornton AM, Fang L, Lo A, McSharry M, Haan D, O'Brien C, et al. eVIP2: Expression-based variant impact phenotyping to predict the function of gene variants. PLoS Comput Biol. 2021;17(7):e1009132.
  28. Seeber A, Battaglin F, Zimmer K, Kocher F, Baca Y, Xiu J, et al. Comprehensive Analysis of R-Spondin Fusions and RNF43 Mutations Implicate Novel Therapeutic Options in Colorectal Cancer. Clin Cancer Res. 2022;28(9):1863-70.
  29. Yamamoto D, Oshima H, Wang D, Takeda H, Kita K, Lei X, et al. Characterization of RNF43 frameshift mutations that drive Wnt ligand- and R-spondin-dependent colon cancer. J Pathol. 2022;257(1):39-52.
  30. Tu J, Park S, Yu W, Zhang S, Wu L, Carmon K, et al. The most common RNF43 mutant G659Vfs*41 is fully functional in inhibiting Wnt signaling and unlikely to play a role in tumorigenesis. Sci Rep. 2019;9(1):18557.

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BJC’s Digital Imaging series is open to receiving submissions assessing:
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