Evidence map›Paper›PMID 39095620›Full record

ArticleDiscover oncology2024

Predictive role of oxidative stress-related genes in colon cancer: a retrospective cohort study based on The Cancer Genome Atlas.

Yajie Wang, Lin Xiao, Yisheng Pan

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Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yajie WangDepartment of Gastrointestinal Surgery, Peking University First Hospital, 8 Xishku Street, Xicheng District, Beijing, 100034, People's Republic of China.
Lin XiaoDepartment of Gastrointestinal Surgery, Peking University First Hospital, 8 Xishku Street, Xicheng District, Beijing, 100034, People's Republic of China.
Yisheng PanDepartment of Gastrointestinal Surgery, Peking University First Hospital, 8 Xishku Street, Xicheng District, Beijing, 100034, People's Republic of China. yisheng_pan@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to elucidate the predictive role of an oxidative stress-related genes (OSRGs) model in colon cancer. MATERIALS AND

methodsFirst, OSRGs that were differentially expressed between tumor and normal tissues were identified using The Cancer Genome Atlas (TCGA)-(Colorectal Adenocarcinoma) COAD dataset. Then, Lasso COX regression was performed to develop an optimal prognostic model patients were stratified into high- and low-risk groups based on the expression patterns of these genes. The model's validity was confirmed through Kaplan-Meier survival curves and receiver operating characteristic curve (ROC) analysis. Additionally, enrichment analyses were performed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) to uncover underlying mechanisms.

resultsA totally of 115 differentially expressed OSRGs were identified within the TCGA cohort, with 17 significantly linked to overall survival. These 17 genes were used to formulate a prognostic model that differentiated patients into distinct risk groups, with the high-risk group demonstrating a notably inferior overall survival rate. The risk score, when integrated with clinical and pathological data, emerged as an independent prognostic indicator of colon cancer. Further analyses revealed that the disparity in prognostic outcomes between risk groups could be attributed to the reactive oxygen species pathway and the p53 signaling pathway.

conclusionA new prediction model was established based on OSRGs. CYP19A1, NOL3 and UCN were found to be highly expressed in tumor tissues and substantial clinical predictive significance. These findings offer new insights into the role of oxidative stress in colon cancer.

Indexed as

Colon cancerOxidative stressPrognostic modelThe Cancer Genome Atlas (TCGA)

Identifiers

PMID39095620
PMCPMC11297001

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