Construction of a new prognosis prediction model and immune infiltration analysis of bladder urothelial cancer based on disulfidptosis-related immune genes

Author:

Cen Kenan1,Zhou Jingyao2,Lv Guangjia3,Zhu Hengyue4,Guo Yangyang4,Zhang Hewei5

Affiliation:

1. The First Affiliated Hospital of Ningbo University,Ningbo

2. Taizhou Central Hospital

3. Northeast Forestry University

4. First Affiliated Hospital of Wenzhou Medical University

5. Wenzhou Central Hospital

Abstract

Abstract

Introduction: The intricate nature and varied forms of bladder urothelial carcinoma (BLCA) highlight the need for new signals to define tumor prognosis. Disulfidptosis, a novel cell death form, is closely linked to BLCA progression, prognosis, and treatment outcomes. Our current goal is to develop a novel disulfidptosis-related immune prognostic model to enhance BLCA treatment strategies. Methods RNA-seq data from TCGA included 419 patients, with clinical details and prognostic data (19 normal, 400 tumor samples). Weighted gene co-expression network analysis (WGCNA) identified disulfidptosis-related immune genes. Univariate, multivariate Cox, and LASSO regression established a disulfidptosis-related immune risk score. A nomogram combining risk score and clinical features predicted prognosis. Model performance was validated through curve analysis and independent prediction. Immune checkpoints, cell infiltration, and tumor mutation load were assessed. Differential gene enrichment analysis was conducted. Prognostic genes were validated via in vitro experiments. Results Eight immune genes related to disulfidptosis were identified and verified in BLCA prognosis. A prognostic model outperformed previous ones in predicting overall survival (OS) for high- and low-risk groups. Patients with low risk-scores had higher OS rates and mutation load expression compared to high risk-score patients. CD4 memory T cells, CD8 T cells, M1 macrophages, and resting NK cells were higher in the low-risk group. ICIS treatment may be more effective for the low risk-score group. High risk-score group exhibited stronger correlation with cancer malignant pathways. Knocking out TNFRSF12A inhibits BLAC cell proliferation and invasion, while overexpressing it has the opposite effect. Conclusions We constructed a novel risk score model combining disulfidptosis and immune genes with good prognostic prediction performance. We discovered and verified that the TNFRSF12A gene is an oncogene in BLAC, which may help provide personalized guidance for individualized treatment and immunotherapy selection for BLCA patients to a certain extent.

Publisher

Research Square Platform LLC

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