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A Qualitative Transcriptional Signature for Predicting CpG Island Methylator Phenotype Status of the Right-Sided Colon Cancer

Authors :
Tianyi You
Kai Song
Wenbing Guo
Yelin Fu
Kai Wang
Hailong Zheng
Jing Yang
Liangliang Jin
Lishuang Qi
Zheng Guo
Wenyuan Zhao
Source :
Frontiers in Genetics, Vol 11 (2020)
Publication Year :
2020
Publisher :
Frontiers Media S.A., 2020.

Abstract

A part of colorectal cancer which is characterized by simultaneous numerous hypermethylation CpG islands sites is defined as CpG island methylator phenotype (CIMP) status. Stage II and III CIMP−positive (CIMP+) right-sided colon cancer (RCC) patients have a better prognosis than CIMP−negative (CIMP−) RCC treated with surgery alone. However, there is no gold standard available in defining CIMP status. In this work, we selected the gene pairs whose relative expression orderings (REOs) were associated with the CIMP status, to develop a qualitative transcriptional signature to individually predict CIMP status for stage II and III RCC. Based on the REOs of gene pairs, a signature composed of 19 gene pairs was developed to predict the CIMP status of RCC through a feature selection process. A sample is predicted as CIMP+ when the gene expression orderings of at least 12 gene pairs vote for CIMP+; otherwise the CIMP−. The difference of prognosis between the predicted CIMP+ and CIMP− groups was more significantly different than the original CIMP status groups. There were more differential methylation and expression characteristics between the two predicted groups. The hierarchical clustering analysis showed that the signature could perform better for predicting CIMP status of RCC than current methods. In conclusion, the qualitative transcriptional signature for classifying CIMP status at the individualized level can predict outcome and guide therapy for RCC patients.

Details

Language :
English
ISSN :
16648021
Volume :
11
Database :
Directory of Open Access Journals
Journal :
Frontiers in Genetics
Publication Type :
Academic Journal
Accession number :
edsdoj.4dc488eec3dd486798e7ad241c65249c
Document Type :
article
Full Text :
https://doi.org/10.3389/fgene.2020.00971