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531 Identifying genetic factors for resistance and response to immune checkpoint inhibitors (icis) in advanced non-small cell lung cancer (nsclc) patients using real-world data
  1. Neeraj Singh,
  2. Smita Agrawal and
  3. Babu Narayanan
  1. ConcertAI, Bangalore, India


Background ICIs are a promising class of drugs that have improved the treatment of a broad spectrum of cancers. Biomarkers such as high Tumor Mutation Burden (TMB), high PD-L1 expression, or high Microsatellite Instability (MSI) are predictive of improved response to ICIs.1-3 However, not all patients with these biomarkers respond well to ICIs and some develop resistance over time. The underlying molecular mechanisms of resistance are poorly known. We leveraged our deeply curated real world clinico-genomics database (ConcertAI Genome360TM) of NSCLC patients treated with ICIs to identify the drivers of resistance and response.

Methods This retrospective study used the ConcertAI Genome360TM NSCLC dataset. The eligible patients had advanced NSCLC treated with ICIs (N=2532). A subset of these patients also had high TMB/PD-L1/MSI (TPM) status (N=986). The following analysis was performed for both the TPM unselected and high TPM populations. The patients were subdivided into responder and non-responder cohorts based on their response to ICIs. For each patient in both cohorts, genes with pathogenic mutations, fusions and copy number changes were identified and enrichment analysis was performed between cohorts. Biomarkers with p value less than 0.05 were further considered for pathway analysis along with the immune signaling network to identify pathways and genes responsible for response and resistance to ICIs in-spite of TPM high status.

Results We identified segments which predicted response or resistance to ICIs (table 1). TERT promoter mutations and loss of function (LOF) mutations in STAG2 promote high TMB and PD-L1 expression respectively.4,5 We also see them enriched in our overall responder cohort, however, the effect of STAG2 LOF mutations towards response to ICIs is seen even in the TPM high population indicating the effect is due to more than just upregulation of PD-L1. LOF mutations in ATM/ATR genes were also enriched in the overall responder cohort in-line with previous observations in murine cells.6,7 Gene amplifications in CDK12 and CEBPA genes were predictive of resistance to ICIs and interestingly, amplifications in CDK12 and RET were also highly predictive of resistance to ICIs in the TPM high cohort which was heavily biased towards response to therapy.

Pathway analysis on the combined results identified that genes in the cGAS-STING pathway are playing a vital role in determining response.

Conclusions Our analysis highlights some of the underlying mechanisms for response or resistance to ICIs which can provide clues for designing new combination trials for patients whose tumor progresses on ICIs.


  1. Xu Y, Wan B, Chen X, Zhan P, Zhao Y, Zhang T, Liu H, Afzal MZ, Dermime S, Hochwald SN, Hofman P, Borghaei H, Lin D, Lv T, Song Y; written on behalf of AME Lung Cancer Collaborative Group. The association of PD-L1 expression with the efficacy of anti-PD-1/PD-L1 immunotherapy and survival of non-small cell lung cancer patients: a meta-analysis of randomized controlled trials. Transl Lung Cancer Res. 2019 Aug;8(4):413–428.

  2. Petrelli F, Ghidini M, Ghidini A, Tomasello G. Outcomes Following Immune Checkpoint Inhibitor Treatment of Patients With Microsatellite Instability-High Cancers: A Systematic Review and Meta-analysis. JAMA Oncol. 2020 Jul 1;6(7):1068–1071.

  3. Palmeri M, Mehnert J, Silk AW, Jabbour SK, Ganesan S, Popli P, Riedlinger G, Stephenson R, de Meritens AB, Leiser A, Mayer T, Chan N, Spencer K, Girda E, Malhotra J, Chan T, Subbiah V, Groisberg R. Real-world application of tumor mutational burden-high (TMB-high) and microsatellite instability (MSI) confirms their utility as immunotherapy biomarkers. ESMO Open. 2022 Feb;7(1):100336.

  4. Li H, Li J, Zhang C, Zhang C, Wang H. TERT mutations correlate with higher TMB value and unique tumor microenvironment and may be a potential biomarker for anti-CTLA4 treatment. Cancer Med. 2020 Oct;9(19):7151–7160.

  5. Nie Z, Gao W, Zhang Y, Hou Y, Liu J, Li Z, Xue W, Ye X, Jin A. STAG2 loss-of-function mutation induces PD-L1 expression in U2OS cells. Ann Transl Med. 2019 Apr;7(7):127.

  6. Hu M, Zhou M, Bao X, Pan D, Jiao M, Liu X, Li F, Li CY. ATM inhibition enhances cancer immunotherapy by promoting mtDNA leakage and cGAS/STING activation. J Clin Invest. 2021 Feb 1;131(3):e139333.

  7. Sheng H, Huang Y, Xiao Y, Zhu Z, Shen M, Zhou P, Guo Z, Wang J, Wang H, Dai W, Zhang W, Sun J, Cao C. ATR inhibitor AZD6738 enhances the antitumor activity of radiotherapy and immune checkpoint inhibitors by potentiating the tumor immune microenvironment in hepatocellular carcinoma. J Immunother Cancer. 2020 May;8(1):e000340.

Abstract 531 Table 1

Genomic segment of response towards ICIs treatment

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