PeerJ · 2025
Construction and verification of a prognostic model for bladder cancer based on disulfidptosis-related angiogenesis genes.
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Zhou Zhihao, Zhang Yuwei, Zhou Yuhua, Gu Jiayu, Li Jufa, Shao Jianfeng, Feng Ninghan
Аннотация
BACKGROUND: Bladder cancer (BLCA) is the most common malignancy of the urinary system and one of the most common cancers worldwide. This study seeks to examine the influence of angiogenesis-related genes (ARGs) linked to disulfidptosis on BLCA patients and to formulate a prognostic model for evaluating their prognosis and response to immunotherapy.
METHODS: This study used sequencing data of BLCA in the Cancer Genome Atlas (TCGA) database. Unsupervised consensus clustering analysis, cox regression analysis, and least absolute shrinkage and selection operator (LASSO) regression analysis were used to screen hub genes and construct a related prognostic risk model. The receiver operating characteristic (ROC) curve and independent prognostic analysis were then used to verify the predictive performance of the signature genes. Clinical characteristics, immune status, and Tumor Mutation Burden (TMB) of the prognostic risk model were evaluated. The expression levels of model genes within standard bladder epithelial cell lines (SV-HUC-1) and bladder cancer cell lines (T24 and SW1710) were quantified through qRT-PCR.
RESULTS: The constructed prognostic risk model can be used as an independent risk indicator for BLCA and was validated in an external dataset. Immune cell infiltration analysis showed that CD8+T cells, Tregs and dendritic cells were significantly different between the two groups. A significant increase was observed in the Stromal score, Immune score and ESTIMATE score in the high-risk group compared with the low-risk group. The Immune Exclusion score and Tumor Immune Dysfunction and Exclusion (TIDE) score of the high-risk group were higher than those of the low-risk score group. Compared with the normal bladder epithelial cell line (SV-HUC-1), the expression levels of 2 model genes (COL5A2 and SCG2) in bladder cancer cell lines (T24 and SW1710) were significantly elevated.
CONCLUSION: This study helps us understand the characteristics of disulfidptosis-related subgroups. The characteristics of disulfidptosis-related ARGs may be used to evaluate the prognosis and immunotherapy response of BLCA patients.
METHODS: This study used sequencing data of BLCA in the Cancer Genome Atlas (TCGA) database. Unsupervised consensus clustering analysis, cox regression analysis, and least absolute shrinkage and selection operator (LASSO) regression analysis were used to screen hub genes and construct a related prognostic risk model. The receiver operating characteristic (ROC) curve and independent prognostic analysis were then used to verify the predictive performance of the signature genes. Clinical characteristics, immune status, and Tumor Mutation Burden (TMB) of the prognostic risk model were evaluated. The expression levels of model genes within standard bladder epithelial cell lines (SV-HUC-1) and bladder cancer cell lines (T24 and SW1710) were quantified through qRT-PCR.
RESULTS: The constructed prognostic risk model can be used as an independent risk indicator for BLCA and was validated in an external dataset. Immune cell infiltration analysis showed that CD8+T cells, Tregs and dendritic cells were significantly different between the two groups. A significant increase was observed in the Stromal score, Immune score and ESTIMATE score in the high-risk group compared with the low-risk group. The Immune Exclusion score and Tumor Immune Dysfunction and Exclusion (TIDE) score of the high-risk group were higher than those of the low-risk score group. Compared with the normal bladder epithelial cell line (SV-HUC-1), the expression levels of 2 model genes (COL5A2 and SCG2) in bladder cancer cell lines (T24 and SW1710) were significantly elevated.
CONCLUSION: This study helps us understand the characteristics of disulfidptosis-related subgroups. The characteristics of disulfidptosis-related ARGs may be used to evaluate the prognosis and immunotherapy response of BLCA patients.