Current Oncology (Aug 2024)

Repeat Next-Generation Sequencing (15-Gene Panel) in Unifocal, Synchronous, and Metachronous Non-Small-Cell Lung Cancer—A Single-Center Experience

  • Shelley Kuang,
  • Kaitlin Chen,
  • Sachin Sayal,
  • Gajeni Prabahan,
  • Mary R. Rabey,
  • Lisa W. Le,
  • Andrew Seto,
  • Frances A. Shepherd,
  • Geoffrey Liu,
  • Penelope Bradbury,
  • Adrian G. Sacher,
  • Jennifer H. Law,
  • Peter Sabatini,
  • Tracy L. Stockley,
  • Ming S. Tsao,
  • Natasha B. Leighl

DOI
https://doi.org/10.3390/curroncol31080334
Journal volume & issue
Vol. 31, no. 8
pp. 4476 – 4485

Abstract

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In advanced non-squamous non-small-cell lung cancer (NSCLC), routine testing with next-generation sequencing (NGS) is recommended to identify actionable genomic alterations (AGAs). The therapeutic implications of repeated NGS testing on synchronous and metachronous tumors are unclear. Between February 2017 and October 2020, NSCLC samples from a single institution were reflex-tested using a targeted 15-gene NGS panel (TruSight Tumor 15, Illumina). Thirty-eight patients were identified with multiple NGS results from 82 samples: 11% were from single unifocal, 51% were from synchronous, and 38% were from metachronous tumors. Changes in EGFR, KRAS, PI3KCA, and TP53 variants were found in 22 patients’ samples (58%). No changes were seen with longitudinal testing of multiple samples from single unifocal tumors, while changes were observed in 60% of synchronous and 71% of metachronous tumors. Of these, 26% of patients had AGA differences between samples. Acknowledging the limited sample size, a significant difference in overall survival was observed between synchronous separate primaries and metastasis. Repeat NGS testing of synchronous and metachronous NSCLC tumors may identify differing variants in >50% of patients. These changes may reflect separate primary lung carcinomas, tumor heterogeneity among intrapulmonary metastases, and clonal evolution. NGS testing of multiple tumors may enhance the identification of therapeutic targets for treatment decisions.

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