Purpose: The objective of this study aimed to explore whether the original IVC regimen should be continued after the second TURBT or whether the IVC induction phase should be restarted from the beginning. Methods: A retrospective analysis was performed on 137 patients who underwent a second TURBT at the Affiliated Hospital of Xuzhou Medical University between April 2014 and June 2022. Based on the pathological findings, patients were divided into two groups: group A patients, who did not have a residual tumor on pathological examination after the second TURBT; and group B patients, who had residual tumor. Recurrence was determined using cystoscopy and imaging every three months. The endpoint was recurrence-free survival. Result: In the entire cohort, there was a statistically significant difference in the RFS between patients in the two IVC regimens (p = 0.029). The RFS of patients in group B1 was significantly lower than that of patients in group B2 (p = 0.009). There was no significant difference in RFS between the subgroups A1 and A2 (p = 0.560). Multivariate Cox regression analysis confirmed that the IVC regimen after a second TURBT (p = 0.012) and T stage after a second TURBT (p = 0.005) were both independent predictors for patient RFS. Conclusion: If the pathological findings of the second TURBT specimen is benign, patients can continue their previous treatment regimen without restarting an IVC induction phase. Unnecessary IVC can be avoided in these patients. In contrast, for patients with residual tumors in the second TURBT specimen, the need to restart the IVC induction phase should be emphasized to improve patient prognosis.

Introduction: Prostate cancer, notably prostate adenocarcinoma (PARD), has high incidence and mortality rates. Although typically resistant to immunotherapy, recent studies have found immune targets for prostate cancer. Stratifying patients by molecular subtypes may identify those who could benefit from immunotherapy. Methods: We used single-cell and bulk RNA sequencing data from GEO and TCGA databases. We characterized the tumor microenvironment at the single-cell level, analyzing cell interactions and identifying fibroblasts linked to mitophagy. Target genes were narrowed down at the bulk transcriptome level to construct a PARD prognosis prediction nomogram. Unsupervised consensus clustering classified PARD into subtypes, analyzing differences in clinical features, immune infiltration, and immunotherapy. Furthermore, the cellular functions of the genes of interest were verified in vitro. Results: We identified ten cell types and 160 mitophagy-related single-cell differentially expressed genes (MR-scDEGs). Strong interactions were observed between fibroblasts, endothelial cells, CD8⁺ T cells, and NK cells. Fibroblasts linked to mitophagy were divided into six subtypes. Intersection of DEGs from three bulk datasets with MR-scDEGs identified 26 key genes clustered into two subgroups. COX regression analysis identified seven prognostic key genes, enabling a prognostic nomogram model. High and low-risk groups showed significant differences in clinical features, immune infiltration, immunotherapy, and drug sensitivity. In prostate cancer cell lines, CAV1, PALLD, and ITGB8 are upregulated, while CLDN7 is downregulated. Knockdown of PALLD significantly inhibits the proliferation and colony-forming ability of PC3 and DU145 cells, suggesting the important roles of this gene in prostate cancer progression. Conclusions: This study analyzed mitophagy-related genes in PARD, predicting prognosis and aiding in subtype identification and immunotherapy response analysis. This approach offers new strategies for treating prostate cancer with specific molecular subtypes and helps develop potential biomarkers for personalized medicine strategies.