Weighted Gene Co-expression Network Analysis Identified a Novel Thirteen-Gene Signature Associated With Progression, Prognosis, and Immune Microenvironment of Colon Adenocarcinoma Patients
Colon adenocarcinoma (COAD) is one of the most common malignant tumors and has high migration and invasion capacity. In this study, we attempted to establish a multigene signature for predicting the prognosis of COAD patients. Weighted gene co-expression network analysis and differential gene expres...
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Published in | Frontiers in genetics Vol. 12; p. 657658 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Frontiers Media S.A
12.07.2021
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Subjects | |
Online Access | Get full text |
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Summary: | Colon adenocarcinoma (COAD) is one of the most common malignant tumors and has high migration and invasion capacity. In this study, we attempted to establish a multigene signature for predicting the prognosis of COAD patients. Weighted gene co-expression network analysis and differential gene expression analysis methods were first applied to identify differentially co-expressed genes between COAD tissues and normal tissues from the Cancer Genome Atlas (TCGA)-COAD dataset and GSE39582 dataset, and a total of 309 overlapping genes were screened out. Then, our study employed TCGA-COAD cohort as the training dataset and an independent cohort by merging the GES39582 and GSE17536 datasets as the testing dataset. After univariate and multivariate Cox regression analyses were performed for these overlapping genes and overall survival (OS) of COAD patients in the training dataset, a 13-gene signature was constructed to divide COAD patients into high- and low-risk subgroups with significantly different OS. The testing dataset exhibited the same results utilizing the same predictive signature. The area under the curve of receiver operating characteristic analysis for predicting OS in the training and testing datasets were 0.789 and 0.868, respectively, which revealed the enhanced predictive power of the signature. Multivariate Cox regression analysis further suggested that the 13-gene signature could independently predict OS. Among the 13 prognostic genes,
NAT1
and
NAT2
were downregulated with deep deletions in tumor tissues in multiple COAD cohorts and exhibited significant correlations with poorer OS based on the GEPIA database. Notably,
NAT1
and
NAT2
expression levels were positively correlated with infiltrating levels of CD8+ T cells and dendritic cells, exhibiting a foundation for further research investigating the antitumor immune roles played by
NAT1
and
NAT2
in COAD. Taken together, the results of our study showed that the 13-gene signature could efficiently predict OS and that
NAT1
and
NAT2
could function as biomarkers for prognosis and the immune response in COAD. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Lorenzo Gerratana, University of Udine, Italy This article was submitted to Cancer Genetics, a section of the journal Frontiers in Genetics Reviewed by: Jyoti Sharma, Institute of Bioinformatics (IOB), India; Jinyan Huang, Zhejiang University, China |
ISSN: | 1664-8021 1664-8021 |
DOI: | 10.3389/fgene.2021.657658 |