Long non-coding RNAs (lncRNAs) have emerged as new gene regulators and prognostic markers in various cancers. Although the lncRNA nuclear enriched abundant transcript 1 (NEAT1) has been associated with tumorigenesis, its functions in renal cell carcinoma (RCC) have not been elucidated. We determined that NEAT1 is up-regulated in RCC tissue compared to corresponding non-tumor tissue. High NEAT1 expression was associated with tumor progression and poor survival in RCC patients. NEAT1 knockdown suppressed RCC cell proliferation by inhibiting cell cycle progression, and inhibited RCC cell migration and invasion by reversing the epithelial-to-mesenchymal transition phenotype. Down-regulation of NEAT1 increased the sensitivity of RCC cells to sorafenib in vitro. Mechanistic analysis revealed that NEAT1 acts as a competitive sponge for miR-34a, which prevents inhibition of c-Met. Thus, NEAT1 promotes RCC progression through the miR-34a/c-Met axis.

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Clear cell renal cell carcinoma (ccRCC) has long been considered as a metabolic disease characterized by metabolic reprogramming due to the abnormal accumulation of lipid droplets in the cytoplasm. However, the prognostic value of metabolism-related genes in ccRCC remains unclear. In our study, we investigated the associations between metabolism-related gene profile and prognosis of ccRCC patients in the Cancer Genome Atlas (TCGA) database. Importantly, we first constructed a metabolism-related prognostic model based on ten genes (ALDH6A1, FBP1, HAO2, TYMP, PSAT1, IL4I1, P4HA3, HK3, CPT1B, and CYP26A1) using Lasso cox regression analysis. The Kaplan-Meier analysis revealed that our model efficiently predicts prognosis in TCGA_KIRC Cohort and the clinical proteomic tumor analysis consortium (CPTAC_ccRCC) Cohort. Using time-dependent ROC analysis, we showed the model has optimal performance in predicting long-term survival. Besides, the multivariate Cox regression analysis demonstrated our model is an independent prognostic factor. The risk score calculated for each patient was significantly associated with various clinicopathological parameters. Notably, the gene set enrichment analysis indicated that fatty acid metabolism was enriched considerably in low-risk patients. In contrast, the high-risk patients were more associated with nonmetabolic pathways. In summary, our study provides novel insight into metabolism-related genes' roles in ccRCC. Clear cell renal cell carcinoma (ccRCC), the most common renal cell carcinoma (RCC) subtype, exhibits global health issues due to its growing incidence, extreme heterogeneity among patients and high mortality. It is estimated that 90% of the ccRCC patients died of tumor-specific recurrence and metastasis 1. Regarding this, considerable research efforts have focused on developing a model to predict the prognosis of ccRCC patients; however, these prognosis tools still require improvements to attain a high degree of accuracy 2-4. Therefore, novel and robust prognostic models are urgently needed in clinical practice. Metabolism is fundamental in maintaining all the biological processes necessary for life 5. Tumors are typified by metabolic abnormalities as proliferating cells rewire their mechanism to sustain growth 6. Notably, the rapidly proliferating cells in malignancies take up abundant glucose and glutamine to generate the proteins, lipids, and nucleic acids to support cell growth 7. RCC is regarded as a metabolic disease with diabetes, obesity, and atherosclerosis considered as the risk factors 8,9. CcRCC is a unique RCC subtypes based on the abnormally accumulated lipid droplets in the cytoplasm with research evidence implicating the lipid accumulation in disease progression 10,11. Nevertheless, the underlying mechanism and the prognostic role of these metabolic genes remain largely unknown. In the present study, we screened the differentially expressed metabolism-related genes and evaluated their clinical value based on the cancer genome atlas (TCGA) kidney renal clear ...

Urinary brain-derived neurotrophic factor (BDNF), an ubiquitous neurotrophin, was found to rise in patients with benign prostatic hyperplasia (BPH). We hypothesized that the urinary level of BDNF could be a potential biomarker for lower urinary tract symptoms (LUTS) in patients with BPH. Totally, 76 patients with BPH-caused LUTS and 32 male control subjects without BPH were enrolled. International Prostate Symptom Score (IPSS) was applied to assess the symptom severity of LUTS. Urodynamic tests were performed for the diagnosis of underlying detrusor overactivity (DO) in the patients with BPH. Urine samples were collected from all subjects. Urinary BDNF levels were measured using enzyme-linked immunosorbent assays and normalized by urinary creatinine (Cr) levels. Seventy-six BPH patients were divided into moderate LUTS group (n=51, 720) according to the IPSS. Of the 76 BPH patients, DO was present in 34 (44.7%) according to the urodynamic test. The urinary BDNF/Cr levels were significantly higher in BPH patients with moderate LUTS (8.29±3.635, P<0.0001) and severe LUTS (11.8±6.44, P<0.0001) than normal controls (1.71±0.555). Patients with severe LUTS tended to have higher urinary BDNF/Cr levels than patients with moderate LUTS (11.8±6.44 vs. 8.29±3.635, P=0.000). The conditions of BPH with LUTS correlated with elevated urinary BDNF levels, and urinary BDNF levels were even higher in BPH-DO patients. The results of this study have provided evidence to suggest that urinary BDNF level test could evaluate the severity of LUTS in BPH patients, and BDNF level can be used as a biomarker for the diagnosis of DO in BPH patients.