BACKGROUND: Urinary pan-cancer system is a general term for tumors of the urinary system including renal cell carcinoma (RCC), prostate cancer (PRAD), and bladder cancer (BLCA). Their location, physiological functions, and metabolism are closely related, making the occurrence and outcome of these tumors highly similar. Cuproptosis is a new type of cell death that is different from apoptosis and plays an essential role in tumors. Therefore, it is necessary to study the molecular mechanism of cuproptosis-related lncRNAs to urinary system pan-cancer for the prognosis, clinical diagnosis, and treatment of urinary tumors. METHOD: In our study, we identified 35 co-expression cuproptosis-related lncRNAs (CRLs) from the urinary pan-cancer system. 28 CRLs were identified as prognostic-related CRLs by univariate Cox regression analysis. Then 11 CRLs were obtained using lasso regression and multivariate cox analysis to construct a prognostic model. We divided patients into high and low-risk groups based on the median risk scores. Next, Kaplan-Meier analysis, principal component analysis (PCA), functional rich annotations, and nomogram were used to compare the differences between the high and low-risk groups. Finally, the prediction of tumor immune dysfunction and rejection, gene mutation, and drug sensitivity were discussed. CONCLUSION: Finally, the candidate molecules of the urinary system pan-cancer were identified. This CRLs risk model may be promising for clinical prediction of prognosis and immunotherapy response in urinary system pan-cancer patients.

Background: Renal clear cell carcinoma is the main type of kidney cancer and its prognosis is poor. The role of cuproptosis as an emerging tumor treatment modality in renal clear cell carcinoma is still unclear. Therefore, it is urgent to discover new prognostic markers and the role of Cuproptosis in renal cancer. Method: The source of cuproptosis-related genes was collected from the reported study from PubMed. RNA expression data and the clinical information of the corresponding patient were obtained from The Cancer Genome Atlas (TCGA) database. We randomly split the whole case into training and testing cohorts. We used three different regression analyses to confirm that lncRNAs with prognostic relevance of KIRC in the training cohort. The test cohort and the whole cohort were also included in the regression analysis to prove the accuracy of the model. eventually, a nomogram on account of clinical characteristics as well as risk scores was constructed to predict survival KIRC. Result: 119 lncRNAs linked to overall survival were gained by univariate cox regression analysis. Furthermore, to further screen for prognosis-related lncRNAs and to optimize the signature, 119 genes were included in LASSO regression as well as multifactorial Cox regression analysis. A new prognostic predictive risk profile containing four lncRNA was produced. Kaplan-Meier (KM) curve showed that patients in the high-risk group showed poor survival in all three components. The area under the curves (AUCs) for 1 year calculated from the roc curve for the three components is 0.754, 0.698, and 0.743. 0.721 and 0. 753. Moreover, the nomogram allows the calculation of 1-, 3-, and 5-year survival rates for patients with renal clear cell carcinoma. Conclusion: A new prognostic signature with four CRLs (MYG1-AS1, MELTF-AS1, AL161782.1, AC112220.2) have significant prognostic value for KIRC was conducted. It may provide a new therapeutic treatment for KIRC patients in the clinical.

Background Urinary pan-cancer system is a general term for tumors of the urinary system including renal cell carcinoma (RCC), prostate cancer (PRAD), and bladder cancer (BLCA). Their location, physiological functions, and metabolism are closely related, making the occurrence and outcome of these tumors highly similar. Cuproptosis is a new type of cell death that is different from apoptosis and plays an essential role in tumors. Therefore, it is necessary to study the molecular mechanism of cuproptosis-related lncRNAs to urinary system pan-cancer for the prognosis, clinical diagnosis, and treatment of urinary tumors. Method In our study, we identified 35 co-expression cuproptosis-related lncRNAs (CRLs) from the urinary pan-cancer system. 28 CRLs were identified as prognostic-related CRLs by univariate Cox regression analysis. Then 12 CRLs were obtained using lasso regression and multivariate cox analysis to construct a prognostic model. We divided patients into high- and low-risk groups based on the median risk scores. Next, Kaplan–Meier analysis, principal component analysis (PCA), functional rich annotations, and nomogram were used to compare the differences between the high- and low-risk groups. Finally, the prediction of tumor immune dysfunction and rejection, gene mutation, and drug sensitivity were discussed. Conclusion Finally, the candidate molecules of the urinary system pan-cancer were identified. This CRLs risk model may be promising for clinical prediction of prognosis and immunotherapy response in urinary system pan-cancer patients.