Open AccessLong noncoding RNA profiles identify five distinct molecular subtypes of colorectal cancer with clinical relevance
Author(s) -
Chen Haoyan,
Xu Jie,
Hong Jie,
Tang Ruqi,
Zhang Xi,
Fang Jing-Yuan
Publication year - 2014
Publication title -
molecular oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.332
H-Index - 88
eISSN - 1878-0261
pISSN - 1574-7891
DOI - 10.1016/j.molonc.2014.05.010
Subject(s) - biology , long non coding rna , clinical significance , colorectal cancer , disease , computational biology , bioinformatics , cancer , rna , genetics , gene , medicine
Colorectal cancer (CRC) is a heterogeneous disease in terms of clinical behavior and response to therapy. Increasing evidence suggests that long noncoding RNAs (lncRNAs) are frequently aberrantly expressed in cancers, and some of them have been implicated in CRC biogenesis and prognosis. Using an lncRNA‐mining approach, we constructed lncRNAs expression profiles in approximately 888 CRC samples. By applying unsupervised consensus clustering to LncRNA expression profiles, we identified five distinct molecular subtypes of CRC with different biological pathways and phenotypically distinct in their clinical outcome in both univariate and multivariate analysis. The prognostic significance of the lncRNA‐based classifier was confirmed in independent patient cohorts. Further analysis revealed that most of the signature lncRNAs positively correlated with somatic copy number alterations (SCNAs). This lncRNAs‐based classification schema thus provides a molecular classification applicable to individual tumors that has implications to influence treatment decisions.