The molecular basis of breast cancer pathological phenotypes.
The molecular basis of breast cancer pathological phenotypes.
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DOI：
10.1002/path.4847
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发表时间：
2017-02
期刊：
影响因子：
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通讯作者：
Beck AH
中科院分区：
文献类型：
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作者：
Heng YJ;Lester SC;Tse GM;Factor RE;Allison KH;Collins LC;Chen YY;Jensen KC;Johnson NB;Jeong JC;Punjabi R;Shin SJ;Singh K;Krings G;Eberhard DA;Tan PH;Korski K;Waldman FM;Gutman DA;Sanders M;Reis-Filho JS;Flanagan SR;Gendoo DM;Chen GM;Haibe-Kains B;Ciriello G;Hoadley KA;Perou CM;Beck AH
乳腺肿瘤形态学特征的组织病理学评价提供了指导治疗的预后信息。辅助分子分析提供进一步的诊断、预后和预测信息。然而，浸润性乳腺癌的形态表型的分子基础的知识有限。本研究整合了基因组学、转录组学和蛋白质数据，为乳腺癌的形态学特征提供了一个全面的分子分析。15位病理学家评估了来自癌症基因组图谱（TCGA）的850例浸润性乳腺癌病例。形态学特征与基因组改变、DNA甲基化亚型、PAM 50和microRNA亚型、增殖评分、基因表达和/或反相蛋白测定亚型显著相关。显著的核多形性、坏死、炎症和高有丝分裂计数与基底样亚型相关，并且具有相似的分子基础。基于OMIC的签名被构造为预测形态特征。首先使用乳腺癌国际联盟（METABRIC）分子分类数据集评估了雌激素受体（ER）阳性和ER阴性乳腺癌中形态学转录组特征与总生存期的相关性;在METABRIC多变量分析中保持预后的特征在另外5个数据集中进一步评估。在ER阳性乳腺癌中，低分化上皮小管的转录组特征是预后的。ER阴性乳腺癌无预后标志。这项研究为乳腺癌形态表型的分子基础提供了新的见解。形态学与分子数据的整合有可能改善乳腺癌分类，预测对治疗的反应，增强我们对乳腺癌生物学的理解，并改善临床管理。这项工作是公开访问www.dx.ai/tcga_breast。
The histopathological evaluation of morphological features in breast tumours provides prognostic information to guide therapy. Adjunct molecular analyses provide further diagnostic, prognostic and predictive information. However, there is limited knowledge of the molecular basis of morphological phenotypes in invasive breast cancer. This study integrated genomic, transcriptomic and protein data to provide a comprehensive molecular profiling of morphological features in breast cancer. Fifteen pathologists assessed 850 invasive breast cancer cases from The Cancer Genome Atlas (TCGA). Morphological features were significantly associated with genomic alteration, DNA methylation subtype, PAM50 and microRNA subtypes, proliferation scores, gene expression and/or reverse-phase protein assay subtype. Marked nuclear pleomorphism, necrosis, inflammation and a high mitotic count were associated with the basal-like subtype, and had a similar molecular basis. Omics-based signatures were constructed to predict morphological features. The association of morphology transcriptome signatures with overall survival in oestrogen receptor (ER)-positive and ER-negative breast cancer was first assessed by use of the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset; signatures that remained prognostic in the METABRIC multivariate analysis were further evaluated in five additional datasets. The transcriptomic signature of poorly differentiated epithelial tubules was prognostic in ER-positive breast cancer. No signature was prognostic in ER-negative breast cancer. This study provided new insights into the molecular basis of breast cancer morphological phenotypes. The integration of morphological with molecular data has the potential to refine breast cancer classification, predict response to therapy, enhance our understanding of breast cancer biology, and improve clinical management. This work is publicly accessible at www.dx.ai/tcga_breast.