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转录组沉默作为治疗抵抗的潜在机制。

Transcriptomic silencing as a potential mechanism of treatment resistance.

机构信息

Department of Internal Medicine, University of South Florida, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.

Center for Personalized Cancer Therapy and Division of Hematology and Oncology, Department of Medicine, University of California, San Diego, Moores Cancer Center, La Jolla, California, USA.

出版信息

JCI Insight. 2020 Jun 4;5(11):134824. doi: 10.1172/jci.insight.134824.

Abstract

Next-generation sequencing (NGS) has not revealed all the mechanisms underlying resistance to genomically matched drugs. Here, we performed in 1417 tumors whole-exome tumor (somatic)/normal (germline) NGS and whole-transcriptome sequencing, the latter focusing on a clinically oriented 50-gene panel in order to examine transcriptomic silencing of putative driver alterations. In this large-scale study, approximately 13% of the somatic single nucleotide variants (SNVs) were unexpectedly not expressed as RNA; 23% of patients had ≥1 nonexpressed SNV. SNV-bearing genes consistently transcribed were TP53, PIK3CA, and KRAS; those with lower transcription rates were ALK, CSF1R, ERBB4, FLT3, GNAS, HNF1A, KDR, PDGFRA, RET, and SMO. We also determined the frequency of tumor mutations being germline, rather than somatic, in these and an additional 462 tumors with tumor/normal exomes; 33.8% of germline SNVs within the gene panel were rare (not found after filtering through variant information domains) and at risk of being falsely reported as somatic. Both the frequency of silenced variant transcription and the risk of falsely identifying germline mutations as somatic/tumor related are important phenomena. Therefore, transcriptomics is a critical adjunct to genomics when interrogating patient tumors for actionable alterations, because, without expression of the target aberrations, there will likely be therapeutic resistance.

摘要

下一代测序(NGS)并未揭示出所有与基因组匹配药物耐药相关的机制。在这里,我们对 1417 个肿瘤进行了全外显子肿瘤(体细胞)/正常(种系)NGS 和全转录组测序,后者重点关注一个临床导向的 50 个基因面板,以检查潜在驱动突变的转录组沉默。在这项大规模研究中,大约 13%的体细胞单核苷酸变异(SNV)出人意料地没有作为 RNA 表达;23%的患者有≥1 个未表达的 SNV。携带 SNV 的基因始终转录的是 TP53、PIK3CA 和 KRAS;转录率较低的是 ALK、CSF1R、ERBB4、FLT3、GNAS、HNF1A、KDR、PDGFRA、RET 和 SMO。我们还确定了这些肿瘤以及另外 462 个具有肿瘤/正常外显子的肿瘤中基因突变是种系而不是体细胞的频率;基因面板内的 33.8%种系 SNV 是罕见的(在通过变异信息域过滤后未发现),并且有被错误报告为体细胞的风险。沉默变异转录的频率和错误识别种系突变作为体细胞/肿瘤相关的风险都是重要的现象。因此,当对患者肿瘤进行可操作的改变进行检测时,转录组学是基因组学的一个重要辅助手段,因为如果没有目标异常的表达,很可能会出现治疗抵抗。

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