Detection of somatic variants and EGFR mutations in cell-free DNA from non-small cell lung cancer patients by ultra-deep sequencing using the ion ampliseq cancer hotspot panel and droplet digital polymerase chain reaction

利用离子扩增测序癌症热点panel和液滴数字聚合酶链式反应技术,通过超深度测序检测非小细胞肺癌患者游离DNA中的体细胞变异和EGFR突变

阅读:1

Abstract

Highly sensitive genotyping assays can detect mutations in cell-free DNA (cfDNA) from cancer patients, reflecting the biology of each patient's cancer. Because circulating tumor DNA comprises a small, variable fraction of DNA circulating in the blood, sensitive parallel multiplexing tests are required to determine mutation profiles. We prospectively examined the clinical utility of ultra-deep sequencing analysis of cfDNA from 126 non-small cell lung cancer (NSCLC) patients using the Ion AmpliSeq Cancer Hotspot Panel v2 (ICP) and validated these findings with droplet digital polymerase chain reaction (ddPCR). ICP results were compared with tumor tissue genotyping (TTG) results and clinical outcomes. A total of 853 variants were detected, with a median of four variants per patient. Overall concordance of ICP and TTG analyses was 90% for EGFR exon 19 deletion and 88% for the L858R mutation. Of 34 patients with a well-defined EGFR activating mutation defined based on the results of ICP and TTG, 31 (81.6%) showed long-term disease control with EGFR TKI treatment. Of 56 patients treated with an EGFR tyrosine kinase inhibitor (TKI), the presence of the de novo T790M mutation was confirmed in 28 (50%). Presence of this de novo mutation did not have a negative effect on EGFR TKI treatment. Ultra-deep sequencing analysis of cfDNA using ICP combined with confirmatory ddPCR was effective at defining driver genetic changes in NSCLC patients. Comprehensive analysis of tumor DNA and cfDNA can increase the specificity of molecular diagnosis, which could translate into tailored treatment.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。