Frequency, underdiagnosis, and heterogeneity of epidermal growth factor receptor exon 20 insertion mutations using real‐world genomic datasets

Autor: Santiago Viteri, Anna Minchom, Lyudmila Bazhenova, Sai‐Hong Ignatius Ou, Joshua M. Bauml, Scott A. Shell, Michael Schaffer, Junchen Gu, Jennifer B. Rose, Joshua C. Curtin, Parthiv Mahadevia, Nicolas Girard
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Molecular Oncology, Vol 17, Iss 2, Pp 230-237 (2023)
Druh dokumentu: article
ISSN: 1878-0261
1574-7891
DOI: 10.1002/1878-0261.13327
Popis: Epidermal growth factor receptor (EGFR) exon 20 insertion mutations (ex20ins) account for ≤ 12% of all EGFR‐mutant nonsmall cell lung cancers. We analysed real‐world datasets to determine the frequency of ex20ins variants, and the ability of polymerase chain reaction (PCR) and next‐generation sequencing (NGS) to identify them. Three real‐world United States NGS databases were used: GENIE, FoundationInsights, and GuardantINFORM. Mutation profiles consistent with in‐frame EGFR ex20ins were summarized. GENIE, FoundationInsights, and GuardantINFORM datasets identified 180, 627, and 627 patients with EGFR ex20ins respectively. The most frequent insertion region of exon 20 was the near loop (~ 70%), followed by the far loop (~ 30%) and the helical (~ 3–6%) regions. GENIE, FoundationInsights, and GuardantINFORM datasets identified 41, 102, and 96 unique variants respectively. An analysis of variants projected that ~ 50% of EGFR ex20ins identified by NGS would have been missed by PCR‐based assays. Given the breadth of EGFR ex20ins identified in the real‐world US datasets, the ability of PCR to identify these mutations is limited. NGS platforms are more appropriate to identify patients likely to benefit from EGFR ex20ins‐targeted therapies.
Databáze: Directory of Open Access Journals
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