Added Value of Whole-Exome and Transcriptome Sequencing for Clinical Molecular Screenings of Advanced Cancer Patients With Solid Tumors

外显子组测序 外显子组 转录组 生物 DNA测序 基因分型 计算生物学 遗传学 基因 突变 基因表达 基因型
作者
Florence Koeppel,Andrea Varga,Céline Lefèbvre,Marion Pedrero,Marc Deloger,Yannick Boursin,Catherine Richon,Romy Chen-Min-Tao,Guillaume Robert,Guillaume Meurice,Etienne Rouleau,Stefan Michiels,Christophe Massard,Jean–Yves Scoazec,Éric Solary,Jean‐Charles Soria,Fabrice André,Ludovic Lacroix
出处
期刊:The cancer journal [Lippincott Williams & Wilkins]
卷期号:24 (4): 153-162 被引量:19
标识
DOI:10.1097/ppo.0000000000000322
摘要

Comprehensive genomic profiling using high-throughput sequencing brings a wealth of information, and its place in the clinical setting has been increasingly prominent. This review emphasizes the utility of whole-exome sequencing (WES) and transcriptome sequencing (RNAseq) in patient care and clinical research, based on published reports as well as our experience with the MOSCATO-01 (MOlecular Screening for CAncer Treatment Optimization) molecular triage trial at Gustave Roussy Cancer Center. In this trial, all contributive samples of patients with advanced solid tumors were analyzed prospectively with targeted gene sequencing (TGS) and comparative genomic hybridization. In addition, 92 consecutive metastatic patients with contributive biopsies were sequenced for WES and RNAseq and compared with TGS and comparative genomic hybridization. Whole-exome sequencing allowed the reporting of additional variants in relevant genes in 38% of patients. Mutation detection sensitivity of WES was 95% compared with TGS. Additional information derived from WES and RNAseq could influence clinical decision, including fusion transcripts, expression levels, allele-specific expression, alternate transcripts, RNA-based pathogen diagnostic, tumor mutation load, mutational signatures, expression signatures, HLA genotyping, and neoepitope prediction. The current challenge is to be able to process the large-scale data from these comprehensive genome-wide technologies in an efficient way.

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