亚型
结直肠癌
外显子
肿瘤科
癌症研究
医学
计算生物学
内科学
生物
计算机科学
遗传学
癌症
基因
程序设计语言
作者
Aslihan Ambeskovic,Matthew N. McCall,Jonathan Woodsmith,Hartmut Juhl,Hartmut Land
标识
DOI:10.1053/j.gastro.2024.08.016
摘要
The identification of colorectal cancer (CRC) molecular subtypes has prognostic and potentially diagnostic value for patients, yet reliable subtyping remains unavailable in the clinic. The current consensus molecular subtype (CMS) classification in CRCs is based on complex RNA expression patterns quantified at the gene level. The clinical application of these methods, however, is challenging due to high uncertainty of single-sample classification and associated costs. Alternative splicing, which strongly contributes to transcriptome diversity, has rarely been used for tissue type classification. Here, we present an AS-based CRC subtyping framework sensitive to differential exon use that can be adapted for clinical application.
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