Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA.
Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA; Molecular Mechanisms and Experimental Therapeutics in Oncology (ONCOBell), Bellvitge Institute for Biomedical Research, L'Hospitalet de Llobregat, Barcelona 08908, Spain; Program Against Cancer Therapeutics Resistance (ProCURE), Catalan Institute of Oncology, Bellvitge Institute for Biomedical Research, L'Hospitalet de Llobregat, Barcelona 08908, Spain.
Cell. 2021 Jan 21;184(2):334-351.e20. doi: 10.1016/j.cell.2020.11.045. Epub 2021 Jan 11.
Despite considerable efforts, the mechanisms linking genomic alterations to the transcriptional identity of cancer cells remain elusive. Integrative genomic analysis, using a network-based approach, identified 407 master regulator (MR) proteins responsible for canalizing the genetics of individual samples from 20 cohorts in The Cancer Genome Atlas (TCGA) into 112 transcriptionally distinct tumor subtypes. MR proteins could be further organized into 24 pan-cancer, master regulator block modules (MRBs), each regulating key cancer hallmarks and predictive of patient outcome in multiple cohorts. Of all somatic alterations detected in each individual sample, >50% were predicted to induce aberrant MR activity, yielding insight into mechanisms linking tumor genetics and transcriptional identity and establishing non-oncogene dependencies. Genetic and pharmacological validation assays confirmed the predicted effect of upstream mutations and MR activity on downstream cellular identity and phenotype. Thus, co-analysis of mutational and gene expression profiles identified elusive subtypes and provided testable hypothesis for mechanisms mediating the effect of genetic alterations.
尽管付出了相当大的努力，但将基因组改变与癌细胞的转录特征联系起来的机制仍然难以捉摸。通过基于网络的综合基因组分析，从癌症基因组图谱（TCGA）的 20 个队列中确定了 407 种负责将单个样本的遗传学转化为 112 种转录不同的肿瘤亚型的主调控蛋白（MR）。MR 蛋白可以进一步组织成 24 个泛癌主调控模块（MRB），每个模块都调节关键的癌症特征，并能预测多个队列中患者的预后。在每个个体样本中检测到的所有体细胞改变中，>50%被预测会导致异常的 MR 活性，从而深入了解肿瘤遗传学和转录特征之间的联系，并确定非癌基因的依赖性。遗传和药理学验证实验证实了上游突变和 MR 活性对下游细胞特征和表型的预测作用。因此，对突变和基因表达谱的联合分析确定了难以捉摸的亚型，并为介导遗传改变效应的机制提供了可测试的假设。
