亚型
结直肠癌
间质细胞
计算生物学
基因表达
基因表达谱
分类器(UML)
癌症研究
生物
生物信息学
医学
基因
癌症
内科学
计算机科学
遗传学
人工智能
程序设计语言
作者
Peter W. Eide,Jarle Bruun,Ragnhild A. Lothe,Anita Sveen
标识
DOI:10.1038/s41598-017-16747-x
摘要
Colorectal cancers (CRCs) can be divided into four gene expression-based biologically distinct consensus molecular subtypes (CMS). This classification provides a potential framework for stratified treatment, but to identify novel CMS-drug associations, translation of the subtypes to pre-clinical models is essential. The currently available classifier is dependent on gene expression signals from the immune and stromal compartments of tumors and fails to identify the poor-prognostic CMS4-mesenchymal group in immortalized cell lines, patient-derived organoids and xenografts. To address this, we present a novel CMS classifier based on a filtered set of cancer cell-intrinsic, subtype-enriched gene expression markers. This new classifier, referred to as CMScaller, recapitulated the subtypes in both in vitro and in vivo models (551 in total). Importantly, by analyzing public drug response data from patient-derived xenografts and cell lines, we show that the subtypes are predictive of response to standard CRC drugs. CMScaller is available as an R package.
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