ArticleOxidative medicine and cellular longevity2023
Identification of Gene Signature-Related Oxidative Stress for Predicting Prognosis of Colorectal Cancer.
Article in Oxidative medicine and cellular longevity, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 3 citations in OpenAlex.
- Establishment of a Lactylation-Related Gene Signature for Hepatocellular Carcinoma Applying Bulk and Single-Cell RNA Sequencing Analysis.International journal of genomics · 2025Article
- Tumor-infiltrating immune cell signature score reveals prognostic biomarkers and therapeutic targets for colorectal cancer.Frontiers in immunology · 2025Article
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4 authors at 2 institutions in 1 country.
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Abstract
Background: Colorectal cancer (CRC) is the third most common cancer. Nearly a decade of studies had shown that cancer regimens tailored to molecular and pathological features lead to improved overall survival. Oxidative stress (OS) refers to a state in which oxidation and antioxidant effects are unbalanced in the body. However, the molecular mechanism of OS-related CRC remains unclear. Methods: Univariate Cox regression analysis gained OS signature genes related to CRC prognosis, and then, different CRC molecular subtypes were obtained by consensus clustering analysis. Differential expression analysis and least absolute shrinkage and selection operator (LASSO) algorithm were used to obtain prognostic-related signature genes. Significantly, risk score was calculated by RiskScore = Results: 63 OS-related prognostic genes were obtained, and four distinct molecular subtypes of CRC were identified based on the expression characteristics. 230 differentially expressed genes (DEGs) between different molecular subtypes were compressed by LASSO algorithm, and finally, 6 OS-related genes were obtained. The Kaplan-Meier survival analysis indicated that the high RiskScore groups had poorer prognosis and the RiskScore model showed better predictive performance in all three other independent datasets. Moreover, immunotherapy/chemosensitivity analysis found that the low-risk group was more sensitive to different treatment options and could achieve better treatment outcomes. Conclusion: Oxidative stress-related RiskScore model built in this work has good predictive performance for CRC.
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