Simvastatin is currently one of the most common drugs for old patients with hyperlipidemia, hypercholesterolemia and atherosclerotic diseases by reducing cholesterol level and anti-lipid properties. Importantly, simvastatin has also been reported to have anti-tumor effect, but the underlying mechanism is largely unknown. We collected several human bladder samples and performed microarray. Data analysis suggested bladder cancer (BCa) was significantly associated with fatty acid/lipid metabolism via PPAR signalling pathway. We observed simvastatin did not trigger BCa cell apoptosis, but reduced cell proliferation in a dose- and time-dependent manner, accompanied by PPARγ-activation. Moreover, flow cytometry analysis indicated that simvastatin induced cell cycle arrest at G0/G1 phase, suggested by downregulation of CDK4/6 and Cyclin D1. Furthermore, simvastatin suppressed BCa cell metastasis by inhibiting EMT and affecting AKT/GSK3β. More importantly, we found that the cell cycle arrest at G0/G1 phase and the alterations of CDK4/6 and Cyclin D1 triggered by simvastatin could be recovered by PPARγ-antagonist (GW9662), whereas the treatment of PPARα-antagonist (GW6471) shown no significant effects on the BCa cells. Taken together, our study for the first time revealed that simvastatin inhibited bladder cancer cell proliferation and induced cell cycle arrest at G1/G0 phase via PPARγ signalling pathway.

Tumor cells rely on aerobic glycolysis as their main energy resource (Warburg effect). Recent research has highlighted the importance of lipid metabolism in tumor progression, and certain cancers even turn to fatty acids as the main fuel. Related studies have identified alterations of fatty acid metabolism in human bladder cancer (BCa). Our microarray analysis showed that fatty acid metabolism was activated in BCa compared with normal bladder. The free fatty acid (FFA) level was also increased in BCa compared with paracancerous tissues. Inhibition of fatty acid oxidation (FAO) with etomoxir caused lipid accumulation, decreased adenosine triphosphate (ATP) and nicotinamide adenine dinucleotide phosphate (NADPH) levels, suppressed BCa cell growth in vitro and in vivo, and reduced motility of BCa cells via affecting epithelial–mesenchymal transition (EMT)-related proteins. Furthermore, etomoxir induced BCa cell cycle arrest at G₀/G₁ phase through peroxisome proliferator-activated receptor (PPAR) γ-mediated pathway with alterations in fatty acid metabolism associated gene expression. The cell cycle arrest could be reversed by PPARγ antagonist GW9662. Taken together, our results suggest that inhibition of FAO with etomoxir may provide a novel avenue to investigate new therapeutic approaches to human BCa.

Clear cell renal cell carcinoma (ccRCC) is the most common solid lesion within kidney, and its prognostic is influenced by the progression covering a complex network of gene interactions. In current study, the microarray data GSE66272 containing ccRCC and adjacent normal tissues was analyzed to identify 4042 differentially expressed genes, on which weighted gene co-expression network analysis was performed. Then 12 co-expressed gene modules were identified. The highest association was found between blue module and pathological stage (r = -0.77) by Pearson's correlation analysis. Functional enrichment analysis revealed that biological processes of blue module focused on inflammatory response, immune response, chemotaxis (all p < 1e-10). In the significant module, a total of 38 network hub genes were identified, FCER1G exhibited the highest correlation (r = 0.95) with ccRCC progression. In addition, FCER1G was hub node in the protein-protein interaction network of the genes in blue module as well. Thus, FCER1G was subsequently selected for validation. In the test set GSE53757 and RNA-sequencing data, FCER1G expression was also positively correlated with four stages of ccRCC progression (p < 0.001). Receiver operating characteristic (ROC) curve indicated that FCER1G could distinguish localized (pathological stage I, II) from non-localized (pathological stage III, IV) ccRCC (AUC=0.74, p < 0.001). Besides, FCER1G could be a prognostic gene in clinical practice as well, revealed by survival analysis based on RNA-sequencing data (p < 0.05). In conclusion, using weighted gene co-expression analysis, FCER1G was identified and validated in association with ccRCC progression and prognosis, which might improve the prognosis by influencing immune-related pathways.

Human clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignant adult kidney tumors. We constructed a weighted gene co-expression network to identify gene modules associated with clinical features of ccRCC (n = 97). Six hub genes (CCNB2, CDC20, CEP55, KIF20A, TOP2A and UBE2C) were identified in both co-expression and protein-protein interaction (PPI) networks, which were highly correlated with pathologic stage. The significance of expression of the hub genes in ccRCC was ranked top 4 among all cancers and correlated with poor prognosis. Functional analysis revealed that the hub genes were significantly enriched in cell cycle regulation and cell division. Gene set enrichment analysis suggested that the samples with highly expressed hub gene were correlated with cell cycle and p53 signaling pathway. Taken together, six hub genes were identified to be associated with progression and prognosis of ccRCC, and they might lead to poor prognosis by regulating p53 signaling pathway.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cancer whose prognostic is affected by the tumor progression associated with complex gene interactions. However, there is currently no available molecular markers associated with ccRCC progression and used or clinical application. In our study, microarray data of 101 ccRCC samples and 95 normal kidney samples were analyzed and 2,425 differentially expressed genes (DEGs) were screened. Weighted gene co-expression network analysis (WGCNA) was then conducted and 11 co-expressed gene modules were identified. Module preservation analysis revealed that two modules (red and black) were found to be most stable. In addition, Pearson's correlation analysis identified the module most relevant to pathological stage(patho-module) (r = 0.44, p = 3e-07). Functional enrichment analysis showed that biological processes of the patho-module focused on cell cycle and cell division related biological process and pathway. In addition, 29 network hub genes highly related to ccRCC progression were identified from the stage module. These 29 hub genes were subsequently validated using 2 other independent datasets including GSE53757 (n = 72) and TCGA (n = 530), and the results indicated that all hub genes were significantly positive correlated with the 4 stages of ccRCC progression. Kaplan-Meier survival curve showed that patients with higher expression of each hub gene had significantly lower overall survival rate and disease-free survival rate, indicating that all hub genes could act as prognosis and recurrence/progression biomarkers of ccRCC. In summary, we identified 29 molecular markers correlated with different pathological stages of ccRCC. They may have important clinical implications for improving risk stratification, therapeutic decision and prognosis prediction in ccRCC patients.

A hallmark of tumor cells, including bladder cancer (BLCA) cells, is metabolic reprogramming toward aerobic glycolysis (Warburg effect). The classical oncogene MYC, which is crucial in regulating glycolysis, is amplified and activated in BLCA. However, direct targeting of the c-Myc oncoprotein, which regulates glycolytic metabolism, presents great challenges and necessitates the discovery of a more clarified regulatory mechanism to develop selective targeted therapy. In this study, a siRNA library targeting deubiquitinases identified a candidate enzyme named USP43, which may regulate glycolytic metabolism and c-Myc transcriptional activity. Further investigation using functional assays and molecular studies revealed a USP43/c-Myc positive feedback loop that contributes to the progression of BLCA. Moreover, USP43 stabilizes c-Myc by deubiquitinating c-Myc at K148 and K289 primarily through deubiquitinase activity. Additionally, upregulation of USP43 protein in BLCA increased the chance of interaction with c-Myc and interfered with FBXW7 access and degradation of c-Myc. These findings suggest that USP43 is a potential therapeutic target for indirectly targeting glycolytic metabolism and the c-Myc oncoprotein consequently enhancing the efficacy of bladder cancer treatment.