Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome.
Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome.
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DOI：
10.1186/s13058-017-0812-y
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发表时间：
2017-03-29
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影响因子：
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通讯作者：
OSBREAC
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作者：
Aure MR;Vitelli V;Jernström S;Kumar S;Krohn M;Due EU;Haukaas TH;Leivonen SK;Vollan HK;Lüders T;Rødland E;Vaske CJ;Zhao W;Møller EK;Nord S;Giskeødegård GF;Bathen TF;Caldas C;Tramm T;Alsner J;Overgaard J;Geisler J;Bukholm IR;Naume B;Schlichting E;Sauer T;Mills GB;Kåresen R;Mælandsmo GM;Lingjærde OC;Frigessi A;Kristensen VN;Børresen-Dale AL;Sahlberg KK;OSBREAC
乳腺癌在临床和分子水平上是一种异质性疾病。在这项研究中，我们整合了从五个不同的分子水平提取的分类，以确定综合亚型。来自Oslo 2研究的425名原发性乳腺癌患者的肿瘤组织被切割和混合，并被分成用于DNA、RNA和蛋白质分离和代谢组学的部分，从而获得代表性和可比性的分子数据。使用各种聚类方法，根据患者的肿瘤特征从五个不同的分子水平将患者分层。最后，所有以前确定的和新确定的亚组结合在一个多层次的分类使用“集群的集群”的方法与共识聚类。基于DNA拷贝数数据，根据复杂臂畸变指数将肿瘤分为三组。mRNA表达谱根据PAM 50亚型将肿瘤分为五个分子亚组，基于microRNA表达的聚类显示了四个亚组。反相蛋白质阵列数据将肿瘤分为五个亚组。肿瘤代谢谱的层次聚类显示三个聚类。结合DNA拷贝数和mRNA表达，基于通路活性水平将肿瘤分为七个簇，并且使用整合聚类将肿瘤分为十个亚型。合并所有上述亚型的最终共识聚类揭示了六个主要群体。5个与mRNA亚型对应良好，而第六组由管腔A亚型的分裂产生;这些肿瘤属于不同的microRNA簇。使用MCF-7细胞的功能获得研究表明，在管腔A簇之间差异表达的microRNA对癌细胞存活很重要。这些microRNA用于验证四个独立乳腺癌队列中管腔A肿瘤的分裂。在两个队列中，microRNA将肿瘤分为具有显著不同结果的亚组，并且在另一个队列中观察到趋势。六个综合亚型确认乳腺癌的异质性，并显示亚型的细分是显而易见的。越来越多地了解腔A亚型的异质性可能会增加指导治疗选择的关键信息，显然使我们更接近改善这个最大乳腺癌亚组的治疗。本文的在线版本（doi：10.1186/s13058-017-0812-y）包含补充材料，可供授权用户使用。
Breast cancer is a heterogeneous disease at the clinical and molecular level. In this study we integrate classifications extracted from five different molecular levels in order to identify integrated subtypes. Tumor tissue from 425 patients with primary breast cancer from the Oslo2 study was cut and blended, and divided into fractions for DNA, RNA and protein isolation and metabolomics, allowing the acquisition of representative and comparable molecular data. Patients were stratified into groups based on their tumor characteristics from five different molecular levels, using various clustering methods. Finally, all previously identified and newly determined subgroups were combined in a multilevel classification using a “cluster-of-clusters” approach with consensus clustering. Based on DNA copy number data, tumors were categorized into three groups according to the complex arm aberration index. mRNA expression profiles divided tumors into five molecular subgroups according to PAM50 subtyping, and clustering based on microRNA expression revealed four subgroups. Reverse-phase protein array data divided tumors into five subgroups. Hierarchical clustering of tumor metabolic profiles revealed three clusters. Combining DNA copy number and mRNA expression classified tumors into seven clusters based on pathway activity levels, and tumors were classified into ten subtypes using integrative clustering. The final consensus clustering that incorporated all aforementioned subtypes revealed six major groups. Five corresponded well with the mRNA subtypes, while a sixth group resulted from a split of the luminal A subtype; these tumors belonged to distinct microRNA clusters. Gain-of-function studies using MCF-7 cells showed that microRNAs differentially expressed between the luminal A clusters were important for cancer cell survival. These microRNAs were used to validate the split in luminal A tumors in four independent breast cancer cohorts. In two cohorts the microRNAs divided tumors into subgroups with significantly different outcomes, and in another a trend was observed. The six integrated subtypes identified confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing knowledge of the heterogeneity of the luminal A subtype may add pivotal information to guide therapeutic choices, evidently bringing us closer to improved treatment for this largest subgroup of breast cancer. The online version of this article (doi:10.1186/s13058-017-0812-y) contains supplementary material, which is available to authorized users.