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A Prognostic Model Based on Six Metabolism-Related Genes in Colorectal Cancer
Joint Authors
Sun, Yuan-Lin
Zhang, Yang
Guo, Yu-Chen
Yang, Zi-Hao
Xu, Yue-Chao
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-01
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
An increasing number of studies have shown that abnormal metabolism processes are closely correlated with the genesis and progression of colorectal cancer (CRC).
In this study, we systematically explored the prognostic value of metabolism-related genes (MRGs) for CRC patients.
A total of 289 differentially expressed MRGs were screened based on The Cancer Genome Atlas (TCGA) and the Molecular Signatures Database (MSigDB), and 72 differentially expressed transcription factors (TFs) were obtained from TCGA and the Cistrome Project database.
The clinical samples obtained from TCGA were randomly divided at a ratio of 7 : 3 to obtain the training group (n=306) and the test group (n=128).
After univariate and multivariate Cox regression analyses, we constructed a prognostic model based on 6 MRGs (AOC2, ENPP2, ADA, GPD1L, ACADL, and CPT2).
Kaplan–Meier survival analysis of the training group, validation group, and overall samples proved that the model had statistical significance in predicting the outcomes of patients.
Independent prognosis analysis suggested that this risk score might serve as an independent prognosis factor for CRC patients.
Moreover, we combined the prognostic model and the clinical characteristics in a nomogram to predict the overall survival of CRC patients.
Furthermore, gene set enrichment analysis (GSEA) was conducted to identify the enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in the high- and low-risk groups, which might provide novel therapeutic targets for CRC patients.
We discovered through the protein-protein interaction (PPI) network and TF-MRG regulatory network that 7 hub genes were retrieved from the PPI network and 4 kinds of differentially expressed TFs (NR3C1, MYH11, MAF, and CBX7) positively regulated 4 prognosis-associated MRGs (GSTM5, PTGIS, ENPP2, and P4HA3).
American Psychological Association (APA)
Sun, Yuan-Lin& Zhang, Yang& Guo, Yu-Chen& Yang, Zi-Hao& Xu, Yue-Chao. 2020. A Prognostic Model Based on Six Metabolism-Related Genes in Colorectal Cancer. BioMed Research International،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1135401
Modern Language Association (MLA)
Sun, Yuan-Lin…[et al.]. A Prognostic Model Based on Six Metabolism-Related Genes in Colorectal Cancer. BioMed Research International No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1135401
American Medical Association (AMA)
Sun, Yuan-Lin& Zhang, Yang& Guo, Yu-Chen& Yang, Zi-Hao& Xu, Yue-Chao. A Prognostic Model Based on Six Metabolism-Related Genes in Colorectal Cancer. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1135401
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1135401