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.
Subject(s)
Biomarkers, Tumor , Melanoma , Oxidative Stress , Skin Neoplasms , Tumor Microenvironment , Humans , Tumor Microenvironment/immunology , Melanoma/immunology , Melanoma/drug therapy , Melanoma/genetics , Melanoma/metabolism , Skin Neoplasms/immunology , Skin Neoplasms/drug therapy , Skin Neoplasms/genetics , Skin Neoplasms/mortality , Prognosis , Melanoma, Cutaneous Malignant , Gene Expression Regulation, Neoplastic , Protein Interaction Maps , Female , Male , Gene Expression Profiling , Transcriptome , Drug Resistance, Neoplasm/genetics , Immunotherapy/methods , Middle Aged , Gene Regulatory NetworksABSTRACT
The prognosis of patients with human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) is poorer than those with HPV-positive HNSCC. The present study aimed to identify novel and specific biomarkers of HPV-negative HNSCC using bioinformatics analysis and associated experiments. The gene expression profiles of HPV-negative HNSCC tissues and corresponding clinical data were downloaded from The Cancer Genome Atlas database and used in a weighted gene co-expression network analysis. Genes in clinically significant co-expression modules were used to construct a protein-protein interaction (PPI) network. The genes demonstrating a high degree score in the PPI network and a high correlation with tumor grade were considered hub genes. The diagnostic value of the hub genes associated with HPV-negative and HPV-positive HNSCC was analyzed using differential expression gene (DEG) analysis, immunohistochemical (IHC) staining and a receiver operating characteristic (ROC) curve analysis. Seven genes [Serrate RNA effector molecule (SRRT), checkpoint kinase 2 (CHEK2), small nuclear ribonucleoprotein polypeptide E (SNRPE), proteasome 26S subunit ATPase 2 (PSMC2), origin recognition complex subunit 5 (ORC5), S100 calcium binding protein A7 and keratinocyte differentiation associated protein (KRTDAP)] were demonstrated to be hub genes in clinically significant co-expression modules. DEG, IHC and ROC curve analyses revealed that SRRT, CHEK2 and SNRPE were significantly upregulated in HPV-negative and HPV-positive HNSCC tissues compared with in adjacent tissues, and these genes demonstrated a high diagnostic value for distinguishing HNSCC tissues. However, PSMC2, ORC5 and KRTDAP were the only differentially expressed genes identified in HPV-negative HNSCC tissues, and these genes demonstrated a high diagnostic value for HPV-negative HNSCC. PSMC2, ORC5 and KRTDAP may therefore serve as novel and specific biomarkers for HPV-negative HNSCC, potentially improving the diagnosis and treatment of patients with HPV-negative HNSCC.
