Asset Details
Do you wish to reserve the book?
Frequency, underdiagnosis, and heterogeneity of epidermal growth factor receptor exon 20 insertion mutations using real‐world genomic datasets
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Frequency, underdiagnosis, and heterogeneity of epidermal growth factor receptor exon 20 insertion mutations using real‐world genomic datasets
Do you wish to request the book?
Frequency, underdiagnosis, and heterogeneity of epidermal growth factor receptor exon 20 insertion mutations using real‐world genomic datasets
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Frequency, underdiagnosis, and heterogeneity of epidermal growth factor receptor exon 20 insertion mutations using real‐world genomic datasets
2023
Overview
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. Three next‐generation sequencing (NGS) databases (GENIE, FoundationInsights and GuardantINFORM) were analyzed to estimate the frequency of exon 20 insertion (ex20ins) variants in epidermal growth factor receptor (EGFR)–mutant non‐small cell lung cancer (NSCLC). Results indicate ~ 50% of ex20ins identified by NGS would have been missed by PCR and the near loop is the most frequent insertion site.
