Long non-coding RNA BLACAT1 inhibits prostate cancer cell proliferation through sponging miR-361

LE-MDCAP: A Computational Model to Prioritize Causal miRNA-Disease Associations

MicroRNAs (miRNAs) are associated with various complex human diseases and some miRNAs can be directly involved in the mechanisms of disease. Identifying disease-causative miRNAs can provide novel insight in disease pathogenesis from a miRNA perspective and facilitate disease treatment. To date, various computational models have been developed to predict general miRNA-disease associations, but few models are available to further prioritize causal miRNA-disease associations from non-causal associations. Therefore, in this study, we constructed a Levenshtein-Distance-Enhanced miRNA-disease Causal Association Predictor (LE-MDCAP), to predict potential causal miRNA-disease associations. Specifically, Levenshtein distance matrixes covering the sequence, expression and functional miRNA similarities were introduced to enhance the previous Gaussian interaction profile kernel-based similarity matrix. LE-MDCAP integrated miRNA similarity matrices, disease semantic similarity matrix and known causal miRNA-disease associations to make predictions. For regular causal vs. non-disease association discrimination task, LF-MDCAP achieved area under the receiver operating characteristic curve (AUROC) of 0.911 and 0.906 in 10-fold cross-validation and independent test, respectively. More importantly, LE-MDCAP prominently outperformed the previous MDCAP model in distinguishing causal versus non-causal miRNA-disease associations (AUROC 0.820 vs. 0.695). Case studies performed on diabetic retinopathy and hsa-mir-361 also validated the accuracy of our model. In summary, LE-MDCAP could be useful for screening causal miRNA-disease associations from general miRNA-disease associations.

Roles of Key Epigenetic Regulators in the Gene Transcription and Progression of Prostate Cancer

Prostate cancer (PCa) is a top-incidence malignancy, and the second most common cause of death amongst American men and the fifth leading cause of cancer death in men around the world. Androgen receptor (AR), the key transcription factor, is critical for the progression of PCa by regulating a series of target genes by androgen stimulation. A number of co-regulators of AR, including co-activators or co-repressors, have been implicated in AR-mediated gene transcription and PCa progression. Epigenetic regulators, by modifying chromatin integrity and accessibility for transcription regulation without altering DNA sequences, influence the transcriptional activity of AR and further regulate the gene expression of AR target genes in determining cell fate, PCa progression and therapeutic response. In this review, we summarized the structural interaction of AR and epigenetic regulators including histone or DNA methylation, histone acetylation or non-coding RNA, and functional synergy in PCa progression. Importantly, epigenetic regulators have been validated as diagnostic markers and therapeutic targets. A series of epigenetic target drugs have been developed, and have demonstrated the potential to treat PCa alone or in combination with antiandrogens.