Abstract 2226: Precise stratification of immunotherapy outcomes using response-associated somatic mutations

Abstract

Abstract Background: Immune checkpoint inhibitors (ICIs) have demonstrated efficacy in a variety of cancer types. However, enhanced predictors of response are needed to identify patients who are likely to respond, while sparing others from unnecessary toxicity. Predictors of response have been identified, including tumor mutation burden (TMB), microsatellite instability (MSI) and PD-L1 expression. Studies looking for somatic mutations associated with ICI response have thus far been limited to single cancer types. Here, we used a clinical-genomic database combining ICI treatment outcomes with next-generation sequencing of tumors to identify somatic mutations associated with ICI response across 12 cancer types. Methods and Results: The cohort consisted 1,525 patients with 12 cancer types, derived from the cohort published by Samstein et al. (Nature Genetics, 2019). All patients had received at least one dose of an ICI (anti-PD-1/PD-L1, anti-CTLA-4 or both) and had a next-generation sequencing panel performed on matched tumor and normal tissue to identify somatic mutations. Using multivariable Cox regression–stratified by cancer type and including age, sex, ICI type, and TMB as covariates–we identified 14 ICI-response associated genes (IRAGs) across 6 cancer types. We verified that these IRAGs were predictive rather than prognostic; they were not associated with overall survival in the non-ICI-treated TCGA cohort. In order to determine whether these IRAGs could be used in conjunction with TMB or MSI to more precisely predict ICI outcomes, we stratified the cohort by MSI and TMB status and repeated the regression analysis. MSI-H was defined as MSIsensor score ≥ 10, while TMB-H was defined as the top 20th percentile within each cancer type. When stratifying by MSI status, we found that RNF43 was independently associated with improved survival among MSI-H COADREAD patients, while 11 IRAGs were associated with worse outcomes in MSI-L tumors. When stratifying by both MSI and TMB status, we found that among TMB-L/MSI-L patients, 3 IRAGs in BLCA and 2 in LUAD were independently associated with worse outcomes. Conclusions: Our results suggest that these IRAGs could be used in combination with MSI and/or TMB status to more precisely predict ICI treatment outcomes. Validation in other ICI-treated cohorts should be pursued. Genes associated with immunotherapy response, stratified by MSI and/or TMB statusCancerGeneSubgroupPatientsMutated (%)HR (95% CI)PCOADREADRNF43MSI-H2919 (66%)0.11 (0.02-0.73)0.023BLCAELF3MSI-L20713 (6%)5.56 (2.03-15.2)<0.001BLCANOTCH1MSI-L20713 (6%)3.72 (1.82-7.61)<0.001BLCAPIK3CAMSI-L20743 (21%)1.99 (1.20-3.32)0.008BRCAKMT2DMSI-L445 (11%)5.33 (1.12-25.4)0.035BRCAPIK3CAMSI-L4414 (32%)3.04 (1.05-8.79)0.04COADREADNCOR1MSI-L815 (6%)8.66 (1.83-41.0)0.007HNSCROS1MSI-L1346 (4%)4.23 (1.35-13.2)0.003HNSCSMARCA4MSI-L1346 (4%)5.13 (1.74-15.1)0.003LUADBRAFMSI-L29322 (8%)2.1 (1.19-3.73)0.011LUADKEAP1MSI-L29364 (22%)1.53 (1.07-2.18)0.021LUADPBRM1MSI-L29316 (5%)2.8 (1.54-.511)<0.001BLCAELF3TMB-L/MSI-L16811 (7%)4.97 (1.63-15.2)0.005BLCANOTCH1TMB-L/MSI-L1686 (4%)5.21 (1.98-13.7)<0.001BLCAPIK3CATMB-L/MSI-L16827 (16%)2.15 (1.17-3.94)0.013LUADBRAFTMB-L/MSI-L23013 (6%)2.65 (1.35-5.18)0.004LUADPBRM1TMB-L/MSI-L2307 (3%)3.2 (1.45-7.08)0.004 Citation Format: Tomi Jun, Tao Qing, Robert Samstein, Carlos Cordon-Cardo, Lajos Pusztai, Kuan-Lin Huang. Precise stratification of immunotherapy outcomes using response-associated somatic mutations [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2226.