RNA序列
桑格测序
转录组
卵巢癌
核糖核酸
计算生物学
基因
生物
小RNA
癌症
遗传学
基因表达
生物信息学
DNA测序
作者
Jinglu Wang,Dylan C. Dean,Francis J. Hornicek,Shi Huirong,Zhenfeng Duan
标识
DOI:10.1016/j.ygyno.2018.10.002
摘要
Despite the surgical and chemotherapeutic advances over the past few decades, ovarian cancer remains the leading cause of gynecological cancer-related mortality. The absence of biomarkers in early detection and the development of drug resistance are principal causes of treatment failure in ovarian cancer. Recent progress in RNA sequencing (RNA-Seq) with Next Generation Sequencing technology has expanded the understanding of the molecular pathogenesis of ovarian cancer. As compared to previous hybridization-based microarray and Sanger sequence-based methods, RNA-Seq provides multiple layers of resolutions and transcriptome complexity, with less background noise and a broader dynamic range of RNA expression. Beyond quantifying gene expression, the data generated by RNA-Seq accelerates the identification of alternatively spliced genes, fusion genes, mutations/SNPs, allele-specific expression, novel transcripts and non-coding RNAs. RNA-Seq has been successfully applied in ovarian cancer research for earlier detection, ascertaining pathological origin, and defining the aberrant genes and dysregulated molecular pathways across patient groups. This review outlines the distinct advantages of RNA-Seq compared to other transcriptomics methods and its recent applications in ovarian cancer.
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