A novel risk model of three SUMOylation genes based on RNA expression for potential prognosis and treatment sensitivity prediction in kidney cancer.

Introduction: Kidney cancer is one of the most common and lethal urological malignancies. Discovering a biomarker that can predict prognosis and potential drug treatment sensitivity is necessary for managing patients with kidney cancer. SUMOylation is a type of posttranslational modification that could impact many tumor-related pathways through the mediation of SUMOylation substrates. In addition, enzymes that participate in the process of SUMOylation can also influence tumorigenesis and development. Methods: We analyzed the clinical and molecular data which were obtanied from three databases, The Cancer Genome Atlas (TCGA), the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC), and ArrayExpress. Results: Through analysis of differentially expressed RNA based on the total TCGA-KIRC cohort, it was found that 29 SUMOylation genes were abnormally expressed, of which 17 genes were upregulated and 12 genes were downregulated in kidney cancer tissues. A SUMOylation risk model was built based on the discovery TCGA cohort and then validated successfully in the validation TCGA cohort, total TCGA cohort, CPTAC cohort, and E-TMAB-1980 cohort. Furthermore, the SUMOylation risk score was analyzed as an independent risk factor in all five cohorts, and a nomogram was constructed. Tumor tissues in different SUMOylation risk groups showed different immune statuses and varying sensitivity to the targeted drug treatment. Discussion: In conclusion, we examined the RNA expression status of SUMOylation genes in kidney cancer tissues and developed and validated a prognostic model for predicting kidney cancer outcomes using three databases and five cohorts. Furthermore, the SUMOylation model can serve as a biomarker for selecting appropriate therapeutic drugs for kidney cancer patients based on their RNA expression.

Telomere-related gene risk model for prognosis and drug treatment efficiency prediction in kidney cancer.

Kidney cancer is one of the most common urological cancers worldwide, and kidney renal clear cell cancer (KIRC) is the major histologic subtype. Our previous study found that von-Hippel Lindau (VHL) gene mutation, the dominant reason for sporadic KIRC and hereditary kidney cancer-VHL syndrome, could affect VHL disease-related cancers development by inducing telomere shortening. However, the prognosis role of telomere-related genes in kidney cancer has not been well discussed. In this study, we obtained the telomere-related genes (TRGs) from TelNet. We obtained the clinical information and TRGs expression status of kidney cancer patients in The Cancer Genome Atlas (TCGA) database, The International Cancer Genome Consortium (ICGC) database, and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Totally 353 TRGs were differential between tumor and normal tissues in the TCGA-KIRC dataset. The total TCGA cohort was divided into discovery and validation TCGA cohorts and then using univariate cox regression, lasso regression, and multivariate cox regression method to conduct data analysis sequentially, ten TRGs (ISG15, RFC2, TRIM15, NEK6, PRKCQ, ATP1A1, ELOVL3, TUBB2B, PLCL1, NR1H3) risk model had been constructed finally. The kidney patients in the high TRGs risk group represented a worse outcome in the discovery TCGA cohort (p<0.001), and the result was validated by these four cohorts (validation TCGA cohort, total TCGA cohort, ICGC cohort, and CPTAC cohort). In addition, the TRGs risk score is an independent risk factor for kidney cancer in all these five cohorts. And the high TRGs risk group correlated with worse immune subtypes and higher tumor mutation burden in cancer tissues. In addition, the high TRGs risk group might benefit from receiving immune checkpoint inhibitors and targeted therapy agents. Moreover, the proteins NEK6, RF2, and ISG15 were upregulated in tumors both at the RNA and protein levels, while PLCL1 and PRKCQ were downregulated. The other five genes may display the contrary expression status at the RNA and protein levels. In conclusion, we have constructed a telomere-related genes risk model for predicting the outcomes of kidney cancer patients, and the model may be helpful in selecting treatment agents for kidney cancer patients.

Identification of a Hypoxia-Related Gene Model for Predicting the Prognosis and Formulating the Treatment Strategies in Kidney Renal Clear Cell Carcinoma.

PURPOSE: The present study aimed to establish a hypoxia related genes model to predict the prognosis of kidney clear cell carcinoma (KIRC) patients using data accessed from The Cancer Genome Atlas (TCGA) database and International Cancer Genome Consortium (ICGC) database. METHODS: Patients' data were downloaded from the TCGA and ICGC databases, and hypoxia related genes were accessed from the Molecular Signatures Database. The differentially expressed genes were evaluated and then the differential expressions hypoxia genes were screened. The TCGA cohort was randomly divided into a discovery TCGA cohort and a validation TCGA cohort. The discovery TCGA cohort was used for constructing the hypoxia genes risk model through Lasso regression, univariate and multivariate Cox regression analysis. Receiver operating characteristic (ROC) curves were used to assess the reliability and sensitivity of our model. Then, we established a nomogram to predict the probable one-, three-, and five-year overall survival rates. Lastly, the Tumor Immune Dysfunction and Exclusion (TIDE) score of patients was calculated. RESULTS: We established a six hypoxia-related gene prognostic model of KIRC patients in the TCGA database and validated in the ICGC database. The patients with high riskscore present poorer prognosis than those with low riskscore in the three TCGA cohorts and ICGC cohort. ROC curves show our six-gene model with a robust predictive capability in these four cohorts. In addition, we constructed a nomogram for KIRC patients in the TCGA database. Finally, the high risk-group had a high TIDE score than the patients with low riskscore. CONCLUSIONS: We established a six hypoxia-related gene risk model for independent prediction of the prognosis of KIRC patients was established and constructed a robust nomogram. The different riskscores might be a biomarker for immunotherapy strategy.

A Three Protein-Coding Gene Prognostic Model Predicts Overall Survival in Bladder Cancer Patients.

Bladder cancer (BLCA) is the most common urinary tract tumor and is the 11th most malignant cancer worldwide. With the development of in-depth multisystem sequencing, an increasing number of prognostic molecular markers have been identified. In this study, we focused on the role of protein-coding gene methylation in the prognosis of BLCA. We downloaded BLCA clinical and methylation data from The Cancer Genome Atlas (TCGA) database and used this information to identify differentially methylated genes and construct a survival model using lasso regression. We assessed 365 cases, with complete information regarding survival status, survival time longer than 30 days, age, gender, and tumor characteristics (grade, stage, T, M, N), in our study. We identified 353 differentially methylated genes, including 50 hypomethylated genes and 303 hypermethylated genes. After annotation, a total of 227 genes were differentially expressed. Of these, 165 were protein-coding genes. Three genes (zinc finger protein 382 (ZNF382), galanin receptor 1 (GALR1), and structural maintenance of chromosomes flexible hinge domain containing 1 (SMCHD1)) were selected for the final risk model. Patients with higher-risk scores represent poorer survival than patients with lower-risk scores in the training set (HR = 2.37, 95% CI 1.43-3.94, p = 0.001), in the testing group (HR = 1.85, 95% CI 1.16-2.94, p = 0.01), and in the total cohort (HR = 2.06, 95% CI 1.46-2.90, p < 0.001). Further univariate and multivariate analyses using the Cox regression method were conducted in these three groups, respectively. All the results indicated that risk score was an independent risk factor for BLCA. Our study screened the different methylation protein-coding genes in the BLCA tissues and constructed a robust risk model for predicting the outcome of BLCA patients. Moreover, these three genes may function in the mechanism of development and progression of BLCA, which should be fully clarified in the future.

Comorbidity relationship to outcome of radical cystectomy in Chinese: a single institution study with the ACE-27 comorbidity index.

To determine the relationship between comorbidity and outcome after radical cystectomy in Chinese patients by using the Adult Comorbidity Evaluation (ACE)-27 index. Two-hundred-and-forty-six patients treated with radical cystectomy at the Second Xiangya Hospital of Central South University, Hunan Province, China between 2000 and 2010 were retrospectively analyzed. Medical records were reviewed for age, gender, delayed time of radical cystectomy, urinary diversion type, pelvic lymphadenectomy status, TNM stage, and pathological grade. Comorbidity information was assessed by the ACE-27 index. The outcome measurement was overall survival. Univariate and multivariate Cox proportional hazards regression analyses were used to determine the association between comorbidity and outcome. The study population consisted of 215 (87.40%) males and 31 (12.60%) females with a mean age of 62±11 years. Median duration of follow-up was 47±31 months. A total of 151 (61.38%) patents died during follow-up. Of those, 118 (47.97%) had at least one comorbidity. According to the ACE-27 scores, 128 (52.03%) patients had no comorbidity, 79 (32.11%) had mild, 33 (13.41%) had moderate, and 6 (2.45%) had severe comorbidities. Multivariate analysis indicated that moderate (p=0.002) and severe (p<0.001) comorbidity was significantly associated with decreased overall survival. In addition, age ≥70 years (p=0.002), delayed time of radical cystectomy >12 weeks (p=0.044), pelvic lymphadenectomy status (p=0.014), and TNM stage >T3 (p<0.001) were determined to be independent risk factors of overall survival. Increasing severity of comorbidity statistically correlated with decreased overall survival after radical cystectomy.

[Phloroglucinol: safe and effective for the prevention of bladder spasm after TURP].

OBJECTIVE: To evaluate the efficacy of phloroglucinol in preventing bladder spasm after transurethral resection of the prostate (TURP). METHODS: Using the random sampling method, we assigned 74 cases of TURP into a treatment group (n = 39), given 80 mg phloroglucinol every day for 3 days, and a control group (n = 35), left untreated. Then we observed the frequency, duration and pain of bladder spasm within the 3 days and compared them between the two groups. RESULTS: The mean frequency, duration and pain visual analogue score of bladder spasm were (4.3 +/- 1.2) times, (7.2 +/- 2.1) min and 3.2 +/- 1.6 respectively in the treatment group, as compared with (7.5 +/- 2.4) times, (15.6 +/- 6.8) min and 4.7 +/- 2.3 in the control, with statistically significant differences between the two groups (P < 0.05). And no obvious adverse reactions were found in the treatment group. CONCLUSION: Phloroglucinol is safe and effective for the prevention and treatment of bladder spasm following TURP.