Transcriptomics in RCC
Transcriptomics in RCC
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DOI：
10.1016/j.urolonc.2019.12.003
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发表时间：
2020-10-01
影响因子：
2.7
通讯作者：
Shuch, Brian
中科院分区：
文献类型：
--
作者：
Syed, Jamil S.;Brito, Joseph;Shuch, Brian
化学、分子生物学、遗传学和生物信息学的进步使得转录组学分析得到了广泛的应用。了解核糖核酸（RNA）转录本的群体可以提供与肾癌护理相关的重要临床信息。这包括更好地了解肾癌亚型和这些类别中的不同集群。RNA测序（RNA-seq）通常在肿瘤内的一个区域进行，该区域代表数千至数百万个异质细胞和微环境的各种成分。计算工具可以对这些种群进行解卷积，以提供对微环境的洞察。缺氧、增殖、血管生成和免疫浸润的特异性特征可以预测反应和存活。预后特征可以对肿瘤进行风险分层，以帮助识别可能从辅助治疗中获益的患者。随着测序成本的持续下降和改进的生物信息学工具的开发，临床使用转录组数据的障碍继续崩溃。在这里，我们回顾了目前的文献中使用的转录组学在肾癌的诊断和管理。(C)2019由Elsevier Inc.出版
Improvements in chemistry, molecular biology, genetics, and bioinformatics have allowed broad use of transcriptomic profiling. Understanding the population of ribonucleic acid (RNA) transcripts can provide important clinical information relevant to kidney cancer care. This includes a better understanding of kidney cancer subtype and distinct clusters within these categories. RNA-sequencing (RNA-seq) is typically done on a region within the tumor, which represents thousands to millions of heterogeneous cells and various components of the microenvironment. Computational tools can deconvolute these populations to provide insight into the microenvironment. Specific signatures of hypoxia, proliferation, angiogenesis and immune infiltration can predict response and survival. Prognostic signatures can risk stratify tumors to aid in identification of patients who might derive benefit from adjuvant therapy. As the cost of sequencing continues to decline and improved bioinformatic tools are developed, the barriers to clinical use of transcriptomic data continue to crumble. Here we review the current literature around the use of transcriptomics in kidney cancer diagnosis and management. (C) 2019 Published by Elsevier Inc.