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Updated: Oct 6, 2025

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
Published on: September 8, 2023
Clonal Hematopoiesis in Late-Stage Non-Small-Cell Lung Cancer and Its Impact on Targeted Panel Next-Generation
Stephanie J Yaung1, Frederike Fuhlbrück2, Maureen Peterson3
1Roche Sequencing Solutions, Pleasanton, CA.
Purpose:
Somatic mutations derived from the expansion of clonal populations of blood cells (clonal hematopoiesis of indeterminate potential, or CHIP) may be detected in sequencing of cell-free DNA (cfDNA) samples. We evaluated the potential implications of CHIP in targeted sequencing of plasma samples using matched peripheral blood mononuclear cells (PBMCs) from patients with lung cancer to identify potential CHIP-associated mutations.
Materials And Methods:
A total of 332 plasma and corresponding PBMC samples were collected predose, cycle 1 day 1 (C1D1), from the randomized, phase III study (OAK) comparing atezolizumab versus docetaxel in previously treated patients with non-small-cell lung cancer (NSCLC). The samples were analyzed with the AVENIO ctDNA Surveillance Kit (for research use only; not for use in diagnostic procedures), a 198-kb next-generation sequencing panel targeting cancer-related genes. CHIP variants were assessed by analyzing both plasma and PBMC sequencing data.
Results:
A range of zero to eight CHIP variants (median = one) was detected per cfDNA sample. Most of these variants were not in the Database of Single Nucleotide Polymorphisms (dbSNP). The number of CHIP variants was positively associated with age, and TP53 was the most frequently mutated gene. Furthermore, the allele frequency was less variable over time for CHIP variants than for tumor-derived variants.
Conclusion:
CHIP-derived mutations are present in late-stage NSCLC. However, not all plasma samples had CHIP mutations detected with targeted panel sequencing. Paired PBMC sequencing analysis may be needed to remove CHIP variants for comprehensive genomic profiling using plasma samples to identify true somatic mutations.

