MicroRNA Prediction and Validation In Order to Understand Racial Health Disparities in Prostate Cancer

clinical cancer research coverIt is well documented that African American (AA) men have higher incidence and mortality in cancers of the prostate. Additionally, these cancers tend to be more aggressive when compared with European American (EA) men. Investigators at George Washington University, Duke University, the National Institute of Arthritis and Musculoskeletal and Skin Diseases, and the National Institute of Dental and Craniofacial Research have collaborated on a project looking to identify novel molecular genes and pathways that may contribute to these clinical observations. Published online and in advance last month in Clinical Cancer Research, researchers identified novel miRNA-mRNA networks that offer molecular insight into aggressive prostate cancer in AA men.

The report, entitled ‘Identification and Functional Validation of Reciprocal microRNA-mRNA Pairings in African American Prostate Cancer Disparities’, exemplifies the successful use of microRNA prediction analysis, bioinformatic data mining, and in vitro and ex vivo experimentation to discover and validate novel molecular players in prostate cancer. Using microarray gene expression analysis of matched tumor and adjacent normal prostate tissue from AA and EA cancer patients, Wang et. al. identified hundreds of altered microRNAs and mRNAs in prostate cancer. TargetScan, coupled with the Global Test and Gene Set Enrichment Analysis algorithms, identified dozens of predicted miRNA-mRNA pathways in which both genes were found to be differentially expressed in prostate cancer and/or by race. The authors focused on miRNA-mRNA pairs exhibiting reciprocal expression, where a microRNA is up-regulated in prostate cancer tissue and the predicted target mRNA is down regulated, or vice-versa. Target gene expression was validated in an additional cohort using real-time PCR. The authors reported strong concordance in the real-time expression values with their microarray results. Interestingly, in pathways important to cancer, including calcium signaling and PI3K-Akt signaling, AAs had higher global expression of numerous pathway genes compared with EAs. Reported were dozens of genes involved in these pathways including MCL1 and STAT1, to name a few.

Taking their investigators a step further, the authors identified gene expression similarities with their tissue microarray dataset and gene expression levels in prostate cancer cell lines derived from either AA or EA prostate cancer patients. Their bioinformatic predictions of miR-133a targeting MCL1 and miR-513c targeting STAT1 were confirmed in these cell lines and mimic and inhibitor studies validated not only the prediction analysis, but also the important role these pathways play in cell proliferation and response to docetaxel treatment. Importantly, genes such as MCL1 and STAT1 are significantly upregulated in prostate cancers in AAs compared with EAs and exemplify specific racial differences in gene expression that may contribute to the known aggressiveness of prostate cancer in African American specifically.

Together, the research presented in this article integrates microRNA prediction, validation, and large-scale bioinformatic analysis to help researchers identify and target novel pathways that could be important players in prostate cancer. This report provides a working approach that can be used as a model to help understand other cancers and diseases, especially those with known racial disparities including cardiovascular disorders and diabetes. Ideally this will help isolate novel molecular pathways that can be targeted in a patient-specific manner in order to enhance patient response to drug treatments and improve disparate health outcomes.


[1]1. Wang, B.D., et al., Identification and Functional Validation of Reciprocal microRNA-mRNA Pairings in African American Prostate Cancer Disparities. Clin Cancer Res, 2015.

Subscribe to the miRNA blog

Thank you for subscribing.

Something went wrong.

Related Posts

Add Comment