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03/22/2024

Molecular Profiling of Advanced Non-Small Cell Lung Cancer in Response to First-Line Immune Checkpoint Inhibitors and/or Chemotherapy Using Multimodal Real-World Data

AACR 2024 PRESENTATION
Authors Xiaoyong Fu, Jordan Kardos, Paola Correa, Min Wang, Li Li, Jackson Egen, Shahed Iqbal

Background: Up to 85% of lung cancer patients have non-small cell lung cancer (NSCLC). Standard of care for NSCLC includes immune checkpoint inhibitors (ICI) and/or platinum-based chemotherapy (CT). However, therapy success is limited with up to 70% of patients not responding to ICI. Mechanisms of resistance across treatments are not fully understood. In this study, we explore real-world data to characterize molecular and genomic changes in advanced NSCLC treated with ICI, ICI+CT, or CT.

Methods: Stage III/IV NSCLC patients receiving first-line (1L) ICI, ICI+CT, or CT were identified from Tempus Labs, Inc.’s de-identified, multimodal real-world database. Patients’ solid tissue biopsies taken pre- or post-1L underwent next generation sequencing with the Tempus xT assays (DNAseq of 648 genes at 500x coverage and whole transcriptome RNAseq). Patients’
clinical and outcome data were abstracted from electronic health records. We analyzed changes in gene expression, pathway enrichment, estimated immune cell components, and somatic mutations in responders (complete/partial response) and non-responders (progression/stable disease) upon 1L treatment.

Results: 1L non-responders (70%, 51%, and 47%) were identified across cohorts (143 ICI, 764 ICI+CT, and 228 CT, respectively). 58% of pre-1L biopsies were taken from distal metastatic tissues. Distinct pathways altered post-1L include the downregulated E2F target pathway in CT cohort, and upregulated TNFα/NFκB signaling and the hypoxia and protein secretion pathways in ICI cohort. Significant (FDR < 0.05) augmented expression was observed for 90, 23, and 65 genes in non-responders vs. responders post ICI, ICI+CT, and CT, respectively. RNAseq deconvolution reveals decreased plasma and CD4+ activated T cell fraction in metastatic biopsies, whereas increased CD4+ activated T cell and monocyte fraction was seen after treatment only in ICI cohort. Genes with oncogenic driver mutations reported in NSCLC were detected including TP53 (68%), KRAS (30%), STK11 (13%), EGFR (11%), CDKN2A (10%), KEAP1 (9%), and NF1 (7%). Of the 250 mutated genes, 72 (29%) were commonly not detected post-1L, whereas 38, 3, and 8 unique genes with loss of detectable mutations were identified post-1L of ICI, ICI+CT, and CT, respectively. Since loss of detectable mutations is a sign of loss of subpopulations of cancer cells hosting such mutations that succumb to therapy, these genetic mutations could be used to select patients who can benefit from such therapy.

Conclusions: Distinct molecular characteristics including tumor immune components and genomic alterations are associated with 1L response in advanced NSCLC. Real-world data analyses provide opportunity to explore distinct mechanisms of therapy resistance and identify potential biomarkers of therapy response for further validation in clinical studies.

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