Lactic acid was previously considered a waste product of glycolysis, and has now become a key metabolite for cancer development, maintenance and metastasis. So far, numerous studies have confirmed that tumor lactic acid levels are associated with increased metastasis, tumor recurrence and poor prognosis. However, the prognostic value of lactic acid metabolism and transporter related genes in patients with clear cell renal cell carcinoma has not been explored. We selected lactic acid metabolism and transporter related twenty-one genes for LASSO cox regression analysis in the E-MTAB-1980 cohort, and finally screened three genes (PNKD, SLC16A8, SLC5A8) to construct a clinical prognostic model for patients with clear cell renal cell carcinoma. Based on the prognostic model we constructed, the over survival (hazard ratio = 4.117, 95% CI: 1.810–9.362, p < 0.0001) of patients in the high-risk group and the low-risk group in the training set E-MTAB-1980 cohort had significant differences, and similar results (hazard ratio = 1.909, 95% CI: 1.414–2.579 p < 0.0001) were also observed in the validation set TGCA cohort. Using the CIBERSORT algorithm to analyze the differences in immune cell infiltration in different risk groups, we found that dendritic cells, M1 macrophages, and CD4⁺ memory cells in the high-risk group were significantly lower than those in the low-risk group, while Treg cells were higher than in the low-risk group. Finally, through gene enrichment analysis, we found that the signal pathway that is strongly related to the prognostic model is the cell cycle.

Cuproptosis is a newly discovered type of cell death. The role and potential mechanism of Cuproptosis-related genes (CRGs) in the prognosis of cancer patients are not fully understood. In this study, we included two cohorts of clear cell renal cell carcinoma patients, TCGA and E-MTAB-1980. The TCGA cohort is used as a training set to construct a CRG signature using the LASSO-cox regression analysis, and E-MTAB-1980 is used as a cohort for verification. A total of eight genes (FDX1, LIAS, LIPT1, DLAT, PDHA1, MTF1, GLS, CDKN2A) were screened to construct a prognostic model in the TCGA cohort. There is a significant difference in OS (p < 0.0001) between the high and low cuproptosis score group, and a similar difference is also observed in the OS (p = 0.0054) of the E-MTAB-1980 cohort. The area under the ROC curves (AUC) were 0.87, 0.82, and 0.78 at 1, 3, and 5 years in the TCGA cohort, respectively. Finally, gene set enrichment analysis revealed that CRGs were associated with cell cycle and mitotic signaling pathways.

Cancer immunotherapy plays a crucial role in bladder cancer (BC) progression. Increasing evidence has elucidated the clinicopathologic significance of the tumor microenvironment (TME) in predicting outcomes and therapeutic efficacy. This study sought to establish a comprehensive analysis of the immune-gene signature combined with TME to assist in BC prognosis. We selected sixteen immune-related genes (IRGs) after a weighted gene co-expression network and survival analysis. Enrichment analysis revealed that these IRGs were actively involved in Mitophagy and Renin secretion pathways. After multivariable COX analysis, the IRGPI comprising NCAM1, CNTN1, PTGIS, ADRB3, and ANLN was established to predict the overall survival of BC, which was validated in both TCGA and GSE13507 cohorts. In addition, a TME gene signature was developed for molecular and prognosis subtyping with unsupervised clustering, followed by a panoramic landscape characterization of BC. In summary, the IRGPI model developed in our study provided a valuable tool with an improved prognosis for BC.