Prognostic characteristics of disulfidptosis-related genes across cancers and their potential implications in...

ObjectiveDisulfidptosis, a newly discovered mechanism of cell death, may play a significant role in cancer initiation, progression, and prognosis. However, studies on the prognostic role of Disulfidptosis-Related Genes (DRGs) across cancers remain limited. This study aims to systematically explore the prognostic value of DRGs in various cancer types by constructing a prognosis model based on DRGs and analyzing their associations with tumor biological characteristics.MethodsThis was a pan-cancer bioinformatics study combined with in vitro qRT-PCR validation. Public transcriptomic and clinical data from cancer patients were obtained from The Cancer Genome Atlas (TCGA). Samples were randomly divided into training and validation cohorts at a 1:1 ratio. In the training cohort, least absolute shrinkage and selection operator (LASSO) regression was used to identify prognosis-related DRGs, followed by multivariate Cox regression to construct a DRG-based risk score. The prognostic value of the risk score was evaluated using Cox regression, Kaplan-Meier survival analysis, and nomogram construction. Gene set activity analysis was performed to assess the associations between the DRG score and tumor-related biological processes, including angiogenesis, epithelial-mesenchymal transition (EMT), and cell cycle activity. To further validate the expression patterns of key DRGs in osteosarcoma, osteosarcoma-related transcriptomic data from TARGET and normal tissue data from GTEx were analyzed. The 16 selected DRGs were intersected with osteosarcoma-related differentially expressed genes, and 10 overlapping genes were further validated by qRT-PCR in osteosarcoma cell lines and normal osteoblasts.ResultsKey DRGs identified via LASSO regression showed significant prognostic value in pan-cancer analysis. The resulting risk model effectively stratified patients by survival outcomes and performed well in both training and validation cohorts, indicating strong clinical potential. SsGSEA revealed associations between DRG risk scores and malignant tumor features such as angiogenesis, EMT, and cell cycle dysregulation. Differential expression and GO enrichment analyses indicated that related genes were involved in metabolism, apoptosis, and immune processes. qRT-PCR validation in normal osteoblasts (hFOB) and seven osteosarcoma cell lines showed that NDUFA11 and NDUFS1 were generally downregulated, whereas ACTB, WASF2, FLNA, PRC1, ACTN4, PGD, RAC1, and FLNB were generally upregulated in most osteosarcoma cell lines compared with hFOB cells. These expression patterns were broadly consistent with the bioinformatics results and support the potential relevance of these genes in osteosarcoma progression.ConclusionBy constructing a prognostic model based on DRGs, this study reveals the significant prognostic value of DRGs across pan-cancers and further validates their association with tumor malignant characteristics. The results suggest that DRG score can serve as an effective prognostic indicator for cancer patient survival and have specific implications in osteosarcoma. In the future, DRG-based scoring systems may serve as novel biomarkers and therapeutic targets.