Background: Both lactylation and m6A modification have important implications for the development of clear cell renal cell carcinoma (ccRCC), and we aimed to use crosstalk genes of both to reveal the prognostic and immunological features of ccRCC.Methods: Our first step was to look for lactylation-related genes that differed between normal and tumor tissues, and then by correlation analysis, we found the genes associated with M6A. Following that, ccRCC subtypes will be identified and risk models will be constructed to compare the prognosis and tumor microenvironment among different subgroups. A nomogram was constructed to predict the prognosis of ccRCC, and in vitro, experiments were conducted to validate the expression and function of key genes.Results: We screened 100 crosstalk genes and identified 2 ccRCC subtypes. A total of 11 prognostic genes were screened for building a risk model. we observed higher immune scores, elevated tumor mutational burden, and microsatellite instability scores in the high-risk group. Therefore, individuals classified as high-risk would derive greater benefits from immunotherapy. The nomogram’s ability to predict overall survival with a 1-year AUC of 0.863 demonstrates its significant practical utility. In addition, HIBCH was identified as a potential therapeutic target and its expression and function were verified by in vitro experiments.Conclusion: In addition to developing a precise prognostic nomogram for patients with ccRCC, our study also discovered the potential of HIBCH as a biomarker for the disease.

Studies have shown that the stimulator of interferon genes (STING) is critical in tumorigenesis, and development. This study aimed to investigate the immune profile and prognostic significance of STING-mediated immune senescence in bladder cancer (BLCA). We identified differential genes between tumor and normal tissue based on the Cancer Genome Atlas database, and used consensus clustering to identify BLCA subtypes. The genes most associated with overall survival were screened by further analysis and used to construct risk models. Then, comparing the immune microenvironment, tumor mutational load (TMB), and microsatellite instability (MSI) scores between different risk groups. Eventually, a nomogram was constructed based on clinical information and risk scores. The model was validated using receiver operating curves (ROC) and calibration plots. We identified 160 differential genes, including 13 genes most associated with prognosis. Three subtypes of bladder cancer with different clinical and immunological features were identified. Immunotherapy was more likely to benefit the low-risk group, which had higher TMB and MSI scores. The nomogram was found to be highly predictive based on ROC analysis and calibration plots. The risk model and nomogram not only predict the prognosis of BLCA patients but also can guide the treatment.

Numerous studies have shown that local therapy can improve long-term survival in patients with metastatic prostate cancer. However, it is unclear which patients are the potential beneficiaries. We obtained information on prostate cancer patients from the Surveillance, Epidemiology, and End Results database and divided eligible patients into the local treatment group and non-local treatment group. Propensity score matching (PSM) was used to reduce the influence of confounding factors. In the matched local treatment (LT) group, if the median overall survival time (OS) was longer than the Nonlocal treatment (NLT) group, it was defined as a benefit group, otherwise, it was a non-benefit group. Then, univariate and multivariate logistic regression were used to screen out predictors associated with benefits, and a nomogram model was constructed based on these factors. The accuracy and clinical value of the models were assessed through calibration plots and decision curve analysis. The study enrolled 7255 eligible patients, and after PSM, each component included 1923 patients. After matching, the median OS was still higher in the LT group than in the NLT group [42 (95% confidence interval: 39–45) months vs 40 (95% confidence interval: 38–42) months, p = 0.03]. The independent predictors associated with benefit were age, PSA, Gleason score, T stage, N stage, and M stage. The nomogram model has high accuracy and clinical application value in both the training set (C-index = 0.725) and the validation set (C-index = 0.664). The nomogram model we constructed can help clinicians identify patients with potential benefits from LT and formulate a reasonable treatment plan.

Distant metastasis is the main cause of death in patients with clear cell renal carcinoma (ccRCC). The dysregulation of the tumor microenvironment is responsible for tumorigenesis and metastasis in ccRCC. The role of long non‑coding RNAs in the tumor immune of ccRCC remains unclear. The present study screened differentially expressed protein‑coding genes and non‑coding genes between ccRCC and normal tissues based on three datasets. The commonly deregulated genes were used to identify distant metastasis‑related long non‑coding RNAs (lncRNAs) and prognostic lncRNAs. Pearson correlation analysis was used to identify immune‑related lncRNAs. A competing endogenous RNA network was constructed and hub lncRNAs were identified. A total of 1650 coding genes, 821 lncRNAs and 62 miRNAs were commonly deregulated in the three datasets. A total of 408 lncRNAs associated with the overall survival of patients with ccRCC were identified. Among them, 82 lncRNAs were distant metastasis‑related. Further analysis identified 52 lncRNAs associated with the immune pathway. Functional analyses concordantly demonstrated the role of the 52 lncRNAs in metastasis and tumor immunology. The ceRNA network analysis indicated lncRNA DSCR9 as the key lncRNA regulator. Univariate and multivariate analysis in two independent cohorts validated that DSCR9 could be an independent risk factor for the progression‑free survival of patients with ccRCC. Further analyses indicated that DSCR9 might be associated with the immunotherapeutic response. reverse transcription‑quantitative PCR demonstrated that the RNA expression level of DSCR9 was upregulated in ccRCC compared with normal kidney samples. The present study demonstrated the potential of LncRNA DSCR9 in assessing the prognosis and developing future immunotherapy for patients with metastatic ccRCC.