亚型
生物
结直肠癌
表型
LGR5型
干细胞
癌症干细胞
计算生物学
间质细胞
癌症
遗传学
癌症研究
生物信息学
基因
计算机科学
程序设计语言
作者
Sudhir B. Malla,Ryan M. Byrne,Maxime W. Lafarge,Shania M. Corry,Natalie C. Fisher,Petros Tsantoulis,Megan L. Mills,Rachel A. Ridgway,Tamsin R.M. Lannagan,Arafath K. Najumudeen,Kathryn Gilroy,Raheleh Amirkhah,Sarah Maguire,Eoghan J. Mulholland,Hayley L. Belnoue-Davis,Elena Grassi,Marco Viviani,Emily Rogan,Keara L. Redmond,Svetlana Sakhnevych
出处
期刊:Nature Genetics
[Nature Portfolio]
日期:2024-02-13
卷期号:56 (3): 458-472
被引量:22
标识
DOI:10.1038/s41588-024-01654-5
摘要
Abstract Molecular stratification using gene-level transcriptional data has identified subtypes with distinctive genotypic and phenotypic traits, as exemplified by the consensus molecular subtypes (CMS) in colorectal cancer (CRC). Here, rather than gene-level data, we make use of gene ontology and biological activation state information for initial molecular class discovery. In doing so, we defined three pathway-derived subtypes (PDS) in CRC: PDS1 tumors, which are canonical/LGR5 + stem-rich, highly proliferative and display good prognosis; PDS2 tumors, which are regenerative/ANXA1 + stem-rich, with elevated stromal and immune tumor microenvironmental lineages; and PDS3 tumors, which represent a previously overlooked slow-cycling subset of tumors within CMS2 with reduced stem populations and increased differentiated lineages, particularly enterocytes and enteroendocrine cells, yet display the worst prognosis in locally advanced disease. These PDS3 phenotypic traits are evident across numerous bulk and single-cell datasets, and demark a series of subtle biological states that are currently under-represented in pre-clinical models and are not identified using existing subtyping classifiers.
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