ArticleFrontiers in immunology2024
Experimentally validated oxidative stress -associated prognostic signatures describe the immune landscape and predict the drug response and prognosis of SKCM.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 8 citations in OpenAlex.
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- Integrating cuproptosis- and ferroptosis-related gene signatures to predict prognosis, immunotherapy response, and drug sensitivity in patients with skin cutaneous melanoma.Frontiers in immunology · 2025Article
- Interplay Between Insulin Resistance and Immune Dysregulation in Type 2 Diabetes Mellitus: Implications for Therapeutic Interventions.ImmunoTargets and therapy · 2025Review
- CEACAM6 as a machine learning derived immune biomarker for predicting neoadjuvant chemotherapy response in HR+/HER2- breast cancer.Frontiers in immunology · 2025Article
- Advanced machine learning unveils CD8 + T cell genetic markers enhancing prognosis and immunotherapy efficacy in breast cancer.BMC cancer · 2024Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Skin Cutaneous Melanoma (SKCM) incidence is continually increasing, with chemotherapy and immunotherapy being among the most common cancer treatment modalities. This study aims to identify novel biomarkers for chemotherapy and immunotherapy response in SKCM and explore their association with oxidative stress. Methods: Utilizing TCGA-SKCM RNA-seq data, we employed Weighted Gene Co-expression Network Analysis (WGCNA) and Protein-Protein Interaction (PPI) networks to identify six core genes. Gene co-expression analysis and immune-related analysis were conducted, and specific markers associated with oxidative stress were identified using Gene Set Variation Analysis (GSVA). Single-cell analysis revealed the expression patterns of Oxidative Stress-Associated Genes (OSAG) in the tumor microenvironment. TIDE analysis was employed to explore the association between immune therapy response and OSAG, while CIBERSORT was used to analyze the tumor immune microenvironment. The BEST database demonstrated the impact of the Oxidative Stress signaling pathway on chemotherapy drug resistance. Immunohistochemical staining and ROC curve evaluation were performed to assess the protein expression levels of core genes in SKCM and normal samples, with survival analysis utilized to determine their diagnostic value. Results: We identified six central genes associated with SKCM metastasis, among which the expression of DSC2 and DSC3 involved in the oxidative stress pathway was closely related to immune cell infiltration. DSC2 influenced drug resistance in SKMC patients. Furthermore, downregulation of DSC2 and DSC3 expression enhanced the response of SKCM patients to immunotherapy. Conclusion: This study identified two Oxidative Stress-Associated genes as novel biomarkers for SKCM. Additionally, targeting the oxidative stress pathway may serve as a new strategy in clinical practice to enhance SKCM chemotherapy and sensitivity.
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