Abstract 2546: Identifying co-mutational signatures in STK11 mutated advanced non-small cell lung cancer (aNSCLC) patients that help overcome poor response to immune checkpoint inhibitors (ICI’s)

Abstract Background: ICIs, either alone or in combination with chemotherapy, have become the primary treatment options for aNSCLC patients without any targetable mutations. However, not all patients benefit similarly from these therapies even after selection based on the currently approved biomarker PD-L1 expression. Previous studies have shown that mutations in certain genes like STK11 and KEAP1 may predict non-response to these therapies. Mutations in STK11 occur in 25-30% of aNSCLC patients. We have used a real-world clinico-genomics dataset to investigate how this STK11+ aNSCLC patient population responds to ICIs in the context of other underlying co-mutations and whether some beneficial co-mutations may help patients overcome resistance due to their STK11 status. Methods: The ConcertAI Genome360TM NSCLC dataset (N=14193) was used in this retrospective study. aNSCLC patients who tested positive for STK11 mutations and received ICIs were considered (N=377). Based on their response to ICIs, the patients were divided into responder (N= 192) and non-responder (N=185) cohorts. Other genes with pathogenic mutations, fusions, and copy number changes were identified in both cohorts, and enrichment analysis was performed to identify co-mutations significantly enriched in one cohort vs the other. Once significant co-mutations were identified, pathway analysis was performed, taking into account the immune signaling network to help rationalise and validate the results. Results: One potential mechanism by which STK11 mutations influence the response to ICIs is through downregulation of the cGas-Sting pathway, which has been shown to play an important role in ICI response. Our co-mutational analysis also strongly supported this theory. We found that additional mutations that can nullify the effect of STK11 mutations on the cGas-Sting pathway led to a positive response (p=0. 002) within the STK11+ cohort. Two such co-mutational signatures in responder patients identified were co-mutations in STK11/SMARCA4/TP53 (no KEAP1) (p-value = 0. 003) and SKT11/KRAS/RBM10 (p-value = 0. 04). Additionally, co-mutations in the DNA damage pathway genes (ATM, BRCA1, BRIP1, PALB2, STAG2) (p-value = 0. 001) were also predictive of response to ICIs in the STK11+ cohort. Conclusion: By leveraging a real-world clinico-genomics dataset linking the tumor genomic profiles with patient response to ICIs, we have been able to perform a comprehensive co-mutational analysis of STK11+ aNSCLC patients to tease out the interplay of various biomarkers and signaling pathways that determine response to ICIs. Even though 25-30% aNSCLC patients are STK11+, we find that ~23% of these patients could still benefit from ICI treatment due to the presence of other co-mutations. Citation Format: Neeraj Singh, Smita Agrawal. Identifying co-mutational signatures in STK11 mutated advanced non-small cell lung cancer (aNSCLC) patients that help overcome poor response to immune checkpoint inhibitors (ICI’s) abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 2546.