Open AccessDevelopment of a miRNA‐based classifier for detection of colorectal cancer molecular subtypes
Author(s) -
Adam Ronja S.,
Poel Dennis,
Ferreira Moreno Leandro,
Spronck Joey M. A.,
Back Tim R.,
Torang Arezo,
Gomez Barila Patricia M.,
Hoorn Sanne,
Markowetz Florian,
Wang Xin,
Verheul Henk M. W.,
Buffart Tineke E.,
Vermeulen Louis
Publication year - 2022
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 - 10.1002/1878-0261.13210
Subject(s) - microrna , wnt signaling pathway , computational biology , biology , classifier (uml) , colorectal cancer , transcriptome , bioinformatics , artificial intelligence , computer science , gene expression , cancer , genetics , gene
Previously, colorectal cancer (CRC) has been classified into four distinct molecular subtypes based on transcriptome data. These consensus molecular subtypes (CMSs) have implications for our understanding of tumor heterogeneity and the prognosis of patients. So far, this classification has been based on the use of messenger RNAs (mRNAs), although microRNAs (miRNAs) have also been shown to play a role in tumor heterogeneity and biological differences between CMSs. In contrast to mRNAs, miRNAs have a smaller size and increased stability, facilitating their detection. Therefore, we built a miRNA‐based CMS classifier by converting the existing mRNA‐based CMS classification using machine learning (training dataset of n = 271). The performance of this miRNA‐assigned CMS classifier (CMS‐miRaCl) was evaluated in several datasets, achieving an overall accuracy of ~ 0.72 (0.6329–0.7987) in the largest dataset ( n = 158). To gain insight into the biological relevance of CMS‐miRaCl, we evaluated the most important features in the classifier. We found that miRNAs previously reported to be relevant in microsatellite‐instable CRCs or Wnt signaling were important features for CMS‐miRaCl. Following further studies to validate its robustness, this miRNA‐based alternative might simplify the implementation of CMS classification in clinical workflows.