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前列腺癌基因组亚型。

Prostate Cancer Genomic Subtypes.

机构信息

Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada.

出版信息

Adv Exp Med Biol. 2019;1210:87-110. doi: 10.1007/978-3-030-32656-2_5.

Abstract

Over the last decade, advancements in massively-parallel DNA sequencing and computational biology have allowed for unprecedented insights into the fundamental mutational processes that underlie virtually every major cancer type. Two major cancer genomics consortia-The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC)-have produced rich databases of mutational, pathological, and clinical data that can be mined through web-based portals, allowing for correlative studies and testing of novel hypotheses on well-powered patient cohorts.In this chapter, we will review the impact of these technological developments on the understanding of molecular subtypes that promote prostate cancer initiation, progression, metastasis, and clinical aggression. In particular, we will focus on molecular subtypes that define clinically-relevant patient cohorts and assess how a better understanding of how these subtypes-in both somatic and germline genomes-may influence the clinical course for individual men diagnosed with prostate cancer.

摘要

在过去的十年中,大规模并行 DNA 测序和计算生物学的进步使得人们对几乎所有主要癌症类型的基本突变过程有了前所未有的深入了解。两个主要的癌症基因组学联盟——癌症基因组图谱(TCGA)和国际癌症基因组联盟(ICGC)——已经生成了丰富的突变、病理和临床数据数据库,可以通过基于网络的门户进行挖掘,从而可以在具有强大效力的患者队列中进行相关研究和检验新假说。在本章中,我们将回顾这些技术发展对理解促进前列腺癌起始、进展、转移和临床侵袭的分子亚型的影响。特别是,我们将重点关注定义具有临床相关性的患者队列的分子亚型,并评估更好地了解这些亚型——在体细胞和种系基因组中——如何影响个体被诊断患有前列腺癌的男性的临床病程。

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