Metabolism-Associated Molecular Classification of Colorectal Cancer.

ABSTRACT: The high heterogeneity of colorectal cancer (CRC) is the main clinical challenge for individualized therapies. Molecular classification will contribute to drug discovery and personalized management optimizing. Here, we aimed to characterize the molecular features of CRC by a classification system based on metabolic gene expression profiles. 435 CRC samples from the Genomic Data Commons data portal were chosen as training set while 566 sample in GSE39582 were selected as testing set. Then, a non-negative matrix factorization clustering was performed, and three subclasses of CRC (C1, C2, and C3) were identified in both training set and testing set. Results showed that subclass C1 displayed high metabolic activity and good prognosis. Subclass C2 was associated with low metabolic activities an

SUBMITTER: Zhang M 

PROVIDER: S-EPMC7746835 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature