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Prostate cancer (PCa) remains the secondary highest cause of cancer‐related death in the United States in men. It has been reported that microRNAs can serve as key regulators in tumor development and progression in various cancers including PCa. In this study, we examined the effect of miR‐498 on proliferation, radiosensitivity, invasion, and migration of PCa cells. The proliferation of LNCaP and DU‐145 PCa cells with altered expression of miR‐498 was evaluated by MTT assay. The invasion and migration of LNCaP and DU‐145 PCa cells were assess by matrigel invasion assay and transwell migration assay. The protein expression level in PCa cells was examined by western blot. The function of miR‐498 on radiation‐induced apoptosis in LNCaP and DU‐145 PCa cells was detected by Caspase‐Glo3/7 assay. Forced expression of miR‐498 improved the proliferation, invasion and migration in PCa cells. Furthermore, miR‐498 decreased the sensitivity of PCa cells after ionizing radiation treatment. MiR‐498 reduced the radiation‐induced apoptosis in PCa cells by regulation of BAX and Bcl‐2 expression. Meanwhile, miR‐498 altered the expression of E‐cadherin, N‐cadherin, snail, and Vimentin in both LNCaP and DU‐145 PCa cells and regulated epithelial to mesenchymal transition (EMT). Further study showed that aberrant expression of miR‐498 changed the expression levels of phosphatase and tensin homolog and p‐AKT in LNCaP and DU‐145 PCa cells. In a summary, miR‐498 displayed important roles in tumor development and progression in PCa cells, and might act as a potential prognostic biomarker and predict radiotherapy response in PCa. [ABSTRACT FROM AUTHOR]

Insulin-like growth factor 1 receptor (IGF1R) is an attractive drug target for cancer therapy and research on IGF1R inhibitors has had success in clinical trials. A particular challenge in the development of specific IGF1R inhibitors is interference from insulin receptor (IR), which has a nearly identical sequence. A few potent inhibitors that are selective for IGF1R have been discovered experimentally with the aid of computational methods. However, studies on the rapid identification of IGF1R-selective inhibitors using virtual screening and confidence-level inspections of ligands that show different interactions with IGF1R and IR in docking analysis are rare. In this study, we established virtual screening and binding-mode prediction workflows based on benchmark results of IGF1R and several kinase receptors with IGF1R-like structures. We used comprehensive analysis of the known complexes of IGF1R and IR with their binding ligands to screen specific IGF1R inhibitors. Using these workflows, 17 of 139,735 compounds in the NCI (National Cancer Institute) database were identified as potential specific inhibitors of IGF1R. Calculations of the potential of mean force (PMF) with GROMACS were further conducted for three of the identified compounds to assess their binding affinity differences towards IGF1R and IR.