Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin.
Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin.
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DOI：
10.1016/j.cell.2014.06.049
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发表时间：
2014-08-14
期刊：
影响因子：
64.5
通讯作者：
Stuart JM
中科院分区：
文献类型：
--
作者：
Hoadley KA;Yau C;Wolf DM;Cherniack AD;Tamborero D;Ng S;Leiserson MDM;Niu B;McLellan MD;Uzunangelov V;Zhang J;Kandoth C;Akbani R;Shen H;Omberg L;Chu A;Margolin AA;Van't Veer LJ;Lopez-Bigas N;Laird PW;Raphael BJ;Ding L;Robertson AG;Byers LA;Mills GB;Weinstein JN;Van Waes C;Chen Z;Collisson EA;Cancer Genome Atlas Research Network;Benz CC;Perou CM;Stuart JM
最近对病理定义的肿瘤类型的基因组分析确定了“组织内”疾病亚型。然而，基因组特征在组织间共享的程度仍不清楚。我们使用5个全基因组平台和1个蛋白质组学平台对来自12种癌症类型的3527个样本进行了综合分析，揭示了11个主要亚型的统一分类。五种亚型几乎与它们的组织起源对应物相同，但发现几种不同的癌症类型收敛为常见亚型。肺鳞癌、头颈癌和膀胱癌合并为一个亚型，以TP53改变、TP63扩增以及免疫和增殖途径基因的高表达为特征。值得注意的是，膀胱癌分为三种泛癌症亚型。多平台分类虽然与组织来源相关，但为预测临床结果提供了独立的信息。所有数据集都可以从统一的资源中进行数据挖掘，以支持进一步的生物学发现和对新治疗策略的见解。
Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies.
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影响因子：
158.5
作者：
Lynch, TJ;Bell, DW;Haber, DA
通讯作者：
Haber, DA
影响因子：
4.6
作者：
通讯作者：
--
关于癌症基因组地图集的泛伴奏蛋白质组学观点。
影响因子：
16.6
作者：
Akbani, Rehan;Ng, Patrick Kwok Shing;Werner, Henrica M. J.;Shahmoradgoli, Maria;Zhang, Fan;Ju, Zhenlin;Liu, Wenbin;Yang, Ji-Yeon;Yoshihara, Kosuke;Li, Jun;Ling, Shiyun;Seviour, Elena G.;Ram, Prahlad T.;Minna, John D.;Diao, Lixia;Tong, Pan;Heymach, John V.;Hill, Steven M.;Dondelinger, Frank;Stadler, Nicolas;Byers, Lauren A.;Meric-Bernstam, Funda;Weinstein, John N.;Broom, Bradley M.;Verhaak, Roeland G. W.;Liang, Han;Mukherjee, Sach;Lu, Yiling;Mills, Gordon B.
通讯作者：
Mills, Gordon B.
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
45.3
作者：
Scagliotti, Giorgio Vittorio;Parikh, Purvish;Gandara, David
通讯作者：
Gandara, David