Constructing a PANoptosis-based prognostic signature to evaluate the immune landscape and therapeutic response in clear cell renal cell carcinoma

构建基于PANoptosis的预后特征以评估透明细胞肾细胞癌的免疫微环境和治疗反应

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Abstract

OBJECTIVE: To identify pyroptosis, apoptosis, and necroptosis (PANoptosis)-related genes (PRGs) in clear cell renal cell carcinoma (ccRCC) for patient stratification and prognosis prediction. METHODS: We used differential expression analysis and weighted gene co-expression network analysis (WGCNA) to identify ccRCC-specific PRGs. A prognostic model, the PANoptosis-index (PANI), was constructed using least absolute shrinkage and selection operator (LASSO) and Cox regression. The PANI model, comprising PRGs, was validated through single-cell RNA-sequencing (scRNA-seq), immunohistochemistry, and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Patient cohorts were categorized into high- and low-PANI groups, and the model's performance was appraised using various metrics. External validation was performed with the E-MTAB-1980 dataset. Functional and gene set enrichment analyses distinguished biological differences between groups. Mutational landscapes and tumor immune microenvironments were compared. Sensitivity to immunotherapy and antineoplastic drugs was also predicted using PANI. The effects of Z-DNA-binding protein 1 (ZBP1) on cell proliferation and migration were assessed by cell counting kit-8 (CCK-8) and Transwell assays. RESULTS: We identified five PRGs (ZBP1, tumor necrosis factor superfamily protein 14 (TNFSF14), cyclin-dependent kinase inhibitor 3 (CDKN3), parathyroid hormone-like hormone (PTHLH),and heme-oxygenase 1 (HMOX1)) constituting PANI, independently associated with ccRCC patient prognosis. The PANI-based nomogram, integrated with clinical factors, demonstrated high predictive accuracy for prognosis. High-PANI patients exhibited distinct co-mutation patterns in ccRCC driver genes and lower survival probabilities, with an enriched immune-related functional profile, indicating an activated immune environment. These patients also showed increased sensitivity to immunotherapy and antineoplastic drugs. The knockdown of ZBP1, a key PRG in the PANI, significantly reduced ccRCC cell proliferation and migration. CONCLUSIONS: PANI provides precise prognosis and immunotherapy response predictions for ccRCC patients, facilitating individualized treatment strategies.

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