Identification and Functional Validation of Reciprocal microRNA-mRNA Pairings in African American Prostate Cancer Disparities

RGS12 Is a Novel Tumor-Suppressor Gene in African American Prostate Cancer That Represses AKT and MNX1 Expression

African American (AA) men exhibit a relatively high incidence and mortality due to prostate cancer even after adjustment for socioeconomic factors, but the biological basis for this disparity is unclear. Here, we identify a novel region on chromosome 4p16.3 that is lost selectively in AA prostate cancer. The negative regulator of G-protein signaling RGS12 was defined as the target of 4p16.3 deletions, although it has not been implicated previously as a tumor-suppressor gene. RGS12 transcript levels were relatively reduced in AA prostate cancer, and prostate cancer cell lines showed decreased RGS12 expression relative to benign prostate epithelial cells. Notably, RGS12 exhibited potent tumor-suppressor activity in prostate cancer and prostate epithelial cell lines in vitro and in vivo We found that RGS12 expression correlated negatively with the oncogene MNX1 and regulated its expression in vitro and in vivo Further, MNX1 was regulated by AKT activity, and RGS12 expression decreased total and activated AKT levels. Our findings identify RGS12 as a candidate tumor-suppressor gene in AA prostate cancer, which acts by decreasing expression of AKT and MNX1, establishing a novel oncogenic axis in this disparate disease setting. Cancer Res; 77(16); 4247-57. ©2017 AACR.

Posttranscriptional regulation of FOXO expression: microRNAs and beyond

Forkhead box, class O (FOXO) transcription factors are major regulators of diverse cellular processes, including fuel metabolism, oxidative stress response and redox signalling, cell cycle progression and apoptosis. Their activities are controlled by multiple posttranslational modifications and nuclear-cytoplasmic shuttling. Recently, post-transcriptional regulation of FOXO synthesis has emerged as a new regulatory level of their functions. Accumulating evidence suggests that this post-transcriptional mode of regulation of FOXO activity operates in response to stressful stimuli, including oxidative stress. Here, we give a brief overview on post-transcriptional regulation of FOXO synthesis by microRNAs (miRNAs) and by RNA-binding regulatory proteins, human antigen R (HuR) and quaking (QKI). Aberrant post-transcriptional regulation of FOXOs is frequently connected with various disease states. We therefore discuss characteristic examples of FOXO regulation at the post-transcriptional level under various physiological and pathophysiological conditions, including oxidative stress and cancer. The picture emerging from this summary points to a diversity of interactions between miRNAs/miRNA-induced silencing complexes and RNA-binding regulatory proteins. Better insight into these complexities of post-transcriptional regulatory interactions will add to our understanding of the mechanisms of pathological processes and the role of FOXO proteins.

LINKED ARTICLES

This article is part of a themed section on Redox Biology and Oxidative Stress in Health and Disease. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.12/issuetoc.

Racial disparities in prostate cancer: a molecular perspective

Prostate cancer incidence and mortality rates are remarkably higher in African-American men as compared to their European-Americans counterparts. Despite these recognitions, precise causes underlying such prevalent racial disparities remain poorly understood. Although socioeconomic factors could account for such differences up to a certain extent, it is now being increasingly realized that such disparity has a molecular basis. Indeed, several differences, including genetic polymorphism, gene mutations, epigenetic modifications, miRNAs alterations, etc., have been reported in malignant prostate tissues from patients of diverse racial backgrounds. Here, we attempt to provide a molecular perspective on prostate cancer racial disparities by gathering available information on these associated factors and discussing their potential significance in disproportionate incidence and clinical outcomes.

Classification and Biomarker Genes Selection for Cancer Gene Expression Data Using Random Forest

BACKGROUND & OBJECTIVE

Microarray and next generation sequencing (NGS) data are the important sources to find helpful molecular patterns. Also, the great number of gene expression data increases the challenge of how to identify the biomarkers associated with cancer. The random forest (RF) is used to effectively analyze the problems of large-p and small-n. Therefore, RF can be used to select and rank the genes for the diagnosis and effective treatment of cancer.

METHODS

The microarray gene expression data of colon, leukemia, and prostate cancers were collected from public databases. Primary preprocessing was done on them using limma package, and then, the RF classification method was implemented on datasets separately in R software. Finally, the selected genes in each of the cancers were evaluated and compared with those of previous experimental studies and their functionalities were assessed in molecular cancer processes.

RESULT

The RF method extracted very small sets of genes while it retained its predictive performance. About colon cancer data set DIEXF, GUCA2A, CA7, and IGHA1 key genes with the accuracy of 87.39 and precision of 85.45 were selected. The SNCA, USP20, and SNRPA1 genes were selected for prostate cancer with the accuracy of 73.33 and precision of 66.67. Also, key genes of leukemia data set were BAG4, ANKHD1-EIF4EBP3, PLXNC1, and PCDH9 genes, and the accuracy and precision were 100 and 95.24, respectively.

CONCLUSION

The current study results showed most of the selected genes involved in the processes and cancerous pathways were previously reported and had an important role in shifting from normal cell to abnormal.

Racial differences in microRNA and gene expression in hypertensive women

Systemic arterial hypertension is an important cause of cardiovascular disease morbidity and mortality. African Americans are disproportionately affected by hypertension, in fact the incidence, prevalence, and severity of hypertension is highest among African American (AA) women. Previous data suggests that differential gene expression influences individual susceptibility to selected diseases and we hypothesized that this phenomena may affect health disparities in hypertension. Transcriptional profiling of peripheral blood mononuclear cells from AA or white, normotensive or hypertensive females identified thousands of mRNAs differentially-expressed by race and/or hypertension. Predominant gene expression differences were observed in AA hypertensive females compared to AA normotensives or white hypertensives. Since microRNAs play important roles in regulating gene expression, we profiled global microRNA expression and observed differentially-expressed microRNAs by race and/or hypertension. We identified novel mRNA-microRNA pairs potentially involved in hypertension-related pathways and differently-expressed, including MCL1/miR-20a-5p, APOL3/miR-4763-5p, PLD1/miR-4717-3p, and PLD1/miR-4709-3p. We validated gene expression levels via RT-qPCR and microRNA target validation was performed in primary endothelial cells. Altogether, we identified significant gene expression differences between AA and white female hypertensives and pinpointed novel mRNA-microRNA pairs differentially-expressed by hypertension and race. These differences may contribute to the known disparities in hypertension and may be potential targets for intervention.

Identification of More Feasible MicroRNA-mRNA Interactions within Multiple Cancers Using Principal Component Analysis Based Unsupervised Feature Extraction

MicroRNA(miRNA)–mRNA interactions are important for understanding many biological processes, including development, differentiation and disease progression, but their identification is highly context-dependent. When computationally derived from sequence information alone, the identification should be verified by integrated analyses of mRNA and miRNA expression. The drawback of this strategy is the vast number of identified interactions, which prevents an experimental or detailed investigation of each pair. In this paper, we overcome this difficulty by the recently proposed principal component analysis (PCA)-based unsupervised feature extraction (FE), which reduces the number of identified miRNA–mRNA interactions that properly discriminate between patients and healthy controls without losing biological feasibility. The approach is applied to six cancers: hepatocellular carcinoma, non-small cell lung cancer, esophageal squamous cell carcinoma, prostate cancer, colorectal/colon cancer and breast cancer. In PCA-based unsupervised FE, the significance does not depend on the number of samples (as in the standard case) but on the number of features, which approximates the number of miRNAs/mRNAs. To our knowledge, we have newly identified miRNA–mRNA interactions in multiple cancers based on a single common (universal) criterion. Moreover, the number of identified interactions was sufficiently small to be sequentially curated by literature searches.

MicroRNAs Are Involved in the Development of Morphine-Induced Analgesic Tolerance and Regulate Functionally Relevant Changes in Serpini1

Long-term opioid treatment results in reduced therapeutic efficacy and in turn leads to an increase in the dose required to produce equivalent pain relief and alleviate break-through or insurmountable pain. Altered gene expression is a likely means for inducing long-term neuroadaptations responsible for tolerance. Studies conducted by our laboratory (Tapocik et al., 2009) revealed a network of gene expression changes occurring in canonical pathways involved in neuroplasticity, and uncovered miRNA processing as a potential mechanism. In particular, the mRNA coding the protein responsible for processing miRNAs, Dicer1, was positively correlated with the development of analgesic tolerance. The purpose of the present study was to test the hypothesis that miRNAs play a significant role in the development of analgesic tolerance as measured by thermal nociception. Dicer1 knockdown, miRNA profiling, bioinformatics, and confirmation of high value targets were used to test the proposition. Regionally targeted Dicer1 knockdown (via shRNA) had the anticipated consequence of eliminating the development of tolerance in C57BL/6J (B6) mice, thus supporting the involvement of miRNAs in the development of tolerance. MiRNA expression profiling identified a core set of chronic morphine-regulated miRNAs (miR's 27a, 9, 483, 505, 146b, 202). Bioinformatics approaches were implemented to identify and prioritize their predicted target mRNAs. We focused our attention on miR27a and its predicted target serpin peptidase inhibitor clade I (Serpini1) mRNA, a transcript known to be intricately involved in dendritic spine density regulation in a manner consistent with chronic morphine's consequences and previously found to be correlated with the development of analgesic tolerance. In vitro reporter assay confirmed the targeting of the Serpini1 3'-untranslated region by miR27a. Interestingly miR27a was found to positively regulate Serpini1 mRNA and protein levels in multiple neuronal cell lines. Lastly, Serpini1 knockout mice developed analgesic tolerance at a slower rate than wild-type mice thus confirming a role for the protein in analgesic tolerance. Overall, these results provide evidence to support a specific role for miR27a and Serpini1 in the behavioral response to chronic opioid administration (COA) and suggest that miRNA expression and mRNA targeting may underlie the neuroadaptations that mediate tolerance to the analgesic effects of morphine.