Clinical Interest in Exome-Based Analysis of Somatic Mutational Signatures for Non-Small Cell Lung Cancer

TL;DR

This study explores how exome sequencing can help predict treatment responses in non-small cell lung cancer patients by analyzing genetic mutations.

Contribution

The study identifies specific mutational signatures linked to poor responses to standard therapies in NSCLC patients.

Findings

Certain mutational signatures are associated with poor outcomes in immune checkpoint inhibitor therapy.

Genomic features from exome sequencing correlate with chemotherapy response in NSCLC patients.

Exome data can help identify patients unlikely to benefit from current standard treatments.

Abstract

Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality. This study investigates the clinical interest of whole exome sequencing for analyzing somatic mutational signatures in patients with advanced or metastatic NSCLC treated with the current standard of care. Investigating somatic mutational signatures as well as structural variations, we evaluated the association between genomic features and patient outcomes in a cohort of 132 patients. This study identified specific signatures associated with poor response to immune checkpoint inhibitor (ICI) therapy and chemotherapy, potentially aiding treatment selection and identifying patients unlikely to benefit from these approaches.

Background: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality. This study investigates the clinical interest of whole exome sequencing (WES) for analyzing somatic mutational signatures in patients with advanced or metastatic NSCLC treated with the current standard of care. Methods: Exome sequencing data and clinical characteristics from 132 patients with advanced or metastatic NSCLC were analyzed. Somatic mutational signatures including single base substitutions (SBSs), double base substitutions (DBSs), and copy number signatures were evaluated. Structural variations including tumor mutational burden (TMB), the number of neoantigens, TCR clonality, homologous recombination deficiency (HRD), copy number alterations (CNAs), and microsatellite instability (MSI) score were determined. The association between these genomic features, NSCLC subtypes, and patient outcomes (progression-free and overall survival) was evaluated. Conclusions: Exome sequencing offers valuable insights into somatic mutational signatures in NSCLC. This study identified specific signatures associated with a poor response to immune checkpoint inhibitor (ICI) therapy and chemotherapy, potentially aiding treatment selection and identifying patients unlikely to benefit from these approaches.

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