Renal cell carcinoma (RCC) is the most lethal type of genitourinary cancer due to its occult onset and resistance to chemotherapy and radiation. Recently, accumulating evidence has suggested stains, inhibitors of 3-hydroxy-3-methyl glutaryl coenzyme A (HMG-CoA) reductase, were associated with the risk reduction of cancer. In the present study, we aimed to investigate the potential effects of simvastatin on RCC cells and the underlying mechanisms by which simvastatin exerted its actions. With cell viability, colony formation, and flow cytometric apoptosis assays, we found that simvastatin potently suppressed cell growth of A498 and 786-O cells in a time- and dose- dependent manner. Consistently, the xenograft model performed in nude mice exhibited reduced tumor growth with simvastatin treatment. In addition, the inhibitory effects of simvastatin on migration and invasion were also observed in vitro. Mechanically, we presented that simvastatin could suppress the proliferation and motility of RCC cells via inhibiting the phosphorylation of AKT, mTOR, and ERK in a time- and dose- dependent manner. Further investigation of the underlying mechanism revealed simvastatin could exert the anti-tumor effects by suppressing IL-6-induced phosphorylation of JAK2 and STAT3. In conclusion, these findings suggested that simvastatin-induced apoptosis and its anti-metastasis activity in RCC cells were accompanied by inhibition of AKT/mTOR, ERK, and JAK2/STAT3 pathways, which imply that simvastatin may be a potential therapeutic agent for the treatment of RCC patients.

ObjectivesThe aim of this study was to establish comprehensive and practical nomograms, based on significant clinicopathological parameters, for predicting the overall survival (OS) and the disease-specific survival (DSS) of patients with clear cell renal cell carcinoma (ccRCC).Patients and methodsThe data of 35,151 ccRCC patients, diagnosed between 2004 and 2014, were obtained from the database of the Surveillance, Epidemiology, and End Results (SEER) program. The Kaplan–Meier method and Cox proportional hazards regression model were used to evaluate the prognostic effects of multiple clinicopathological variables on survival. Based on Cox models, a nomogram was constructed to predict the probabilities of OS and DSS for an individual patient. The predictive performance of nomograms was evaluated using the concordance index (C-index) and calibration curves.ResultsAccording to univariate and multivariate analyses, age at diagnosis, sex, race, marital status, surgical approach, tumor node metastasis (TNM) stage, and Fuhrman grade significantly correlated with the survival outcomes. These characteristics were used to establish nomograms. The nomograms showed good accuracy in predicting 3-, 5-, and 10-year OS and DSS, with a C-index of 0.79 (95% CI, 0.79–0.80) for OS and 0.87 (95% CI, 0.86–0.88) for DSS. All calibration curves revealed excellent consistency between predicted and actual survival.ConclusionNomograms were developed to predict death from ccRCC treated with nephrectomy. These new prognostic tools could aid in improving the predictive accuracy of survival outcomes, thus leading to reasonable individualized treatment.

No abstract

Background The present study aims to investigate the gene expression changes in papillary renal cell carcinoma(pRCC) and screen several genes and associated pathways of papillary renal cell carcinoma progression. Methods The papillary renal cell carcinoma RNA sequencing (RNA-seq) data set was downloaded from TCGA (The Cancer Genome Atlas). We identified the differentially expressed mRNAs between cancer and normal tissues and performed annotation of differentially expressed mRNAs to figure out the functions and pathways they were enriched in. Then, we constructed a risk score that relied on the 5-mRNA. The optimal value for the patients’classification risk level was identified by ROC analysis. The relationship between mRNA expression and prognosis of papillary renal cell carcinoma was evaluated by univariate Cox regression model. The 5-mRNA based risk score was validated in both complete set and testing set. Result In general, the 5-mRNA (CCNB2, IGF2BP3, KIF18A, PTTG1, and BUB1) were identified and validated, which can predict papillary renal cell carcinoma patient survival. This study revealed the 5-mRNA expression profile and the potential function of a single mRNA as a prognostic target for papillary renal cell carcinoma. Conclusion In addition, these findings may have significant implications for potential treatments options and prognosis for patients with papillary renal cell carcinoma.

No abstract