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识别癌症的病因学不同亚型:一项涉及乳腺癌的示范项目

Identifying Etiologically Distinct Sub-Types of Cancer: A Demonstration Project Involving Breast Cancer.

作者信息

Begg Colin B, Orlow Irene, Zabor Emily C, Arora Arshi, Sharma Ajay, Seshan Venkatraman E, Bernstein Jonine L

机构信息

Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, New York.

出版信息

Cancer Med. 2015 Sep;4(9):1432-9. doi: 10.1002/cam4.456. Epub 2015 May 13.

Abstract

With the advent of increasingly detailed molecular portraits of tumor specimens, much attention has been directed toward identifying clinically distinct subtypes of cancer. Subtyping of tumors can also be accomplished with the goal of identifying distinct etiologies. We demonstrate the use of new methodologies to identify genes that distinguish etiologically heterogeneous subtypes of breast cancer using data from the case-control Cancer and Steroid Hormone Study. Tumor specimens were evaluated using a breast cancer expression panel of 196 genes. Using a statistical measure that distinguishes the degree of etiologic heterogeneity in tumor subtypes, each gene is ranked on the basis of its ability to distinguish etiologically distinct subtypes. This is accomplished independently using case-control comparisons and by examining the concordance odds ratios in double primaries. The estrogen receptor gene, and others in this pathway with expression levels that correlated strongly with estrogen receptor levels, demonstrate high degrees of etiologic heterogeneity in both methods. Our results are consistent with a growing literature that confirms the distinct etiologies of breast cancers classified on the basis of estrogen receptor expression levels. This proof-of-principle project demonstrates the viability of new strategies to identify genomic features that distinguish subtypes of cancer from an etiologic perspective.

摘要

随着肿瘤标本分子特征越来越详细,人们将大量注意力投向识别临床上不同的癌症亚型。肿瘤亚型分类也可旨在识别不同病因。我们利用病例对照的癌症与类固醇激素研究数据,展示了使用新方法来识别区分乳腺癌病因异质性亚型的基因。使用包含196个基因的乳腺癌表达谱对肿瘤标本进行评估。利用一种区分肿瘤亚型病因异质性程度的统计方法,根据每个基因区分病因不同亚型的能力对其进行排名。这通过病例对照比较独立完成,并通过检查双原发癌中的一致性比值比来实现。雌激素受体基因以及该通路中其他表达水平与雌激素受体水平密切相关的基因,在两种方法中均显示出高度的病因异质性。我们的结果与越来越多的文献一致,这些文献证实了基于雌激素受体表达水平分类的乳腺癌具有不同病因。这个原理验证项目证明了从病因角度识别区分癌症亚型的基因组特征的新策略的可行性。

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