Abstract
Renal cell carcinoma (RCC) has the high mortality rate among urological malignancies. The development of RCC cannot be effectively reduced by molecular targeted therapies based on nutrient deprivation, such as inhibition of tumor angiogenesis. The objective of this study was to identify predictive biomarkers of poor prognosis and therapeutic molecular targets in patients with RCC. Two independent cohorts were analyzed in the present study. Global transcriptomics were used in the first cohort (43 patients with RCC) to identify biomarker genes. Each identified biomarker was subsequently analyzed using immunohistochemistry in the second cohort (97 patients with RCC). Following transcriptomics, biomarkers were evaluated using receiver operating characteristic curve analysis. Predictive accuracy for poor survivals was assessed using the log-rank test and Cox multivariate analysis. Global transcriptomic analysis in the first cohort focusing on cases with survival periods <2 years after initial diagnosis of metastasis detected seven overexpressed genes, which correlated with poor prognosis. The ADP-ribosylation factor-like 4C (ARL4C) exhibited the best accuracy in the receiver operating characteristic curve analysis and predicted poor survival in the first cohort (log-rank test, P<0.001; Cox multivariate analysis, hazard ratio =167, P=0.005). In the second cohort, the expression of ARL4C was semi-quantitatively evaluated through immunohistochemistry. Twenty-seven cases showed high levels of ARL4C, confirming a significant association with shorter survivals (log-rank test, P<0.001; Cox multivariate analysis, hazard ratio =9.41, P=0.004). ARL4C was shown to be a predictive biomarker for poor prognosis in patients with RCC and may be a novel target in the treatment of RCC.