Evidence map›Paper›PMID 33193579›Full record

ArticleFrontiers in genetics2020

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

Tianyi You, Kai Song, Wenbing Guo, Yelin Fu, Kai Wang, Hailong Zheng, Jing Yang, Liangliang Jin, Lishuang Qi, Zheng Guo and 1 more

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Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Tianyi YouDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Kai SongDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Wenbing GuoDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yelin FuDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Kai WangDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Hailong ZhengDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Jing YangDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Liangliang JinDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Lishuang QiDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Zheng GuoDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Wenyuan ZhaoDepartment of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

CpG island methylator phenotypegene pairsrelative expression orderingright-sided colon cancerthe qualitative transcriptional signature

Identifiers

PMID33193579
PMCPMC7658404

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