Our findings suggest that PLAC8 may be a potential prognostic indicator and therapeutic target for ccRCC.

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Nucleolar and spindle-associated protein 1 (NUSAP1) is a microtubule-binding protein that plays an essential role in mitosis and cancer. Previous studies have demonstrated that NUSAP1 expression is relatively elevated in several malignancies. However, the biological roles of NUSAP1 in renal cell carcinoma (RCC) remain unknown. In the present study, we firstly performed reverse transcription‑polymerase chain reaction (RT-PCR) and western blot analysis to reveal that the expression of NUSAP1 was relatively elevated in clear cell RCC (ccRCC) tissue specimens and RCC cell lines. Immunohistochemical analysis showed that upregulation of NUSAP1 was significantly correlated with Fuhrman grade (P<0.001), tumor size (P=0.016), clinical stage (P<0.001) and distant metastasis (P=0.023). Additionally, high expression of NUSAP1 was closely associated with a shorter overall survival time of the ccRCC patients (P=0.006). Furthermore, we investigated the biological behaviors of RCC cells in vitro, and we identified that NUSAP1 depletion inhibited RCC cell migration, proliferation and invasion, and apoptosis was induced and the cell cycle was arrested. On the basis of our studies, NUSAP1 was identified as a potential prognostic indicator and a novel therapeutic target for RCC patients.

Polymorphisms in the endothelial nitric oxide synthase (eNOS) gene may influence the risk of cancer, but the results are still debatable. Therefore, we performed a systematic review to provide a more complete picture and conducted a meta-analysis to derive a precise estimation. We searched PubMed, EMBASE, EBSCO, Google Scholar and China National Knowledge Infrastructure (CNKI) databases until April 2014 to identify eligible studies. Thirty-one studies with cancer patients and controls were included in the meta-analysis. Overall, the polled analysis revealed that the T-786C polymorphism was significantly associated with increased cancer risk under multiple genetic models (

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