Abstract
Abstract Background: Non-small cell lung cancer (NSCLC) is the leading cause of global cancer deaths, since a large proportion of cases are initially diagnosed at advanced stages. Therapeutic developments have shifted first-line (1L) therapy in the metastatic setting to immunotherapy (IO)-based regimens, albeit with heterogeneity in response. Patients harboring KEAP1 and STK11 mutations have been reported to exhibit both poorer outcomes and IO treatment resistance. Recent work suggests gene expression signatures which characterize mutant phenotypes may better identify those with compromised IO response. Leveraging a molecular real-world dataset of metastatic NSCLC patients treated with 1L IO, we aimed to evaluate gene expression signatures representing KEAP1 and STK11-mutated phenotypes and their impact on real-world outcomes. Methods: Metastatic NSCLC patients who received 1L anti-PD(L)1 as a monotherapy or in combination were identified from the multimodal real-world database of Tempus Labs, Inc. All patients in the analytical cohort had tissue biopsies sequenced on Tempus targeted DNA and whole transcriptome RNA assays within 90 days prior to the start of the 1L IO regimen. Patients were negative for actionable mutations with record duration of at least 30 days from 1L initiation. KEAP1 and STK11 mutants were identified with likely pathogenic and/or pathogenic mutations as annotated by Tempus bioinformatic pipelines. Gene expression signatures related to these mutations were obtained from recently published literature. Evaluation of mutations or signatures as genomic markers for IO non-response were conducted using real-world progression-free survival (rwPFS) and overall survival (rwOS). Results: A total of 332 patients were included in the study (45% IO monotherapy, 55% IO combination therapy). Previously validated biomarkers, including tumor mutation burden, T-cell inflamed GEP signature, and PD(L)1 expression, were associated with prolonged rwPFS. KEAP1 mutations were observed in 9% of analytical cohort with a higher proportion in non-squamous (11%) compared with squamous (4%) samples. For STK11, 10% were identified as mutants with a similar histology distribution (12% vs. 3%). Neither KEAP1 mutations nor related gene signatures evaluated in this study were significantly associated with real-world survival outcomes. Patients harboring STK11 mutations trended towards poor outcomes; furthermore, those with higher STK11 inactivation signature score were associated with shorter rwPFS and rwOS. Conclusions: STK11 inactivation phenotype described by a gene expression signature was able to distinguish patients with significantly poorer survival outcomes. This finding would need validation in independent cohorts. This real-world cohort study adds supporting evidence for the utility of gene expression signatures encompassing mutant phenotypes for patient stratification. Citation Format: Katherina C. Chua, Assieh Saadatpour, Ariel Chen, Aisha Hasan, Bevan Emma Huang, Stewart Bates. Evaluating biomarkers of immunotherapy response in a real-world metastatic NSCLC cohort [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(6_Suppl):Abstract nr 2543.
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