Dataset Information

MicroRNA-1205 Regulation of FRYL in Prostate Cancer.

ABSTRACT: High mortality rates of prostate cancer (PCa) are associated with metastatic castration-resistant prostate cancer (CRPC) due to the maintenance of androgen receptor (AR) signaling despite androgen deprivation therapies (ADTs). The 8q24 chromosomal locus is a region of very high PCa susceptibility that carries genetic variants associated with high risk of PCa incidence. This region also carries frequent amplifications of the PVT1 gene, a non-protein coding gene that encodes a cluster of microRNAs including, microRNA-1205 (miR-1205), which are largely understudied. Herein, we demonstrate that miR-1205 is underexpressed in PCa cells and tissues and suppresses CRPC tumors in vivo. To characterize the molecular pathway, we identified and validated fry-like (FRYL) as a direct molecular target of miR-1205 and observed its overexpression in PCa cells and tissues. FRYL is predicted to regulate dendritic branching, which led to the investigation of FRYL in neuroendocrine PCa (NEPC). Resistance toward ADT leads to the progression of treatment related NEPC often characterized by PCa neuroendocrine differentiation (NED), however, this mechanism is poorly understood. Underexpression of miR-1205 is observed when NED is induced in vitro and inhibition of miR-1205 leads to increased expression of NED markers. However, while FRYL is overexpressed during NED, FRYL knockdown did not reduce NED, therefore revealing that miR-1205 induces NED independently of FRYL.

SUBMITTER: Naidoo M

PROVIDER: S-EPMC8354587 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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MicroRNA-1205 Regulation of FRYL in Prostate Cancer.

Naidoo Michelle M Levine Fayola F Gillot Tamara T Orunmuyi Akintunde T AT Olapade-Olaopa E Oluwabunmi EO Ali Thahmina T Krampis Konstantinos K Pan Chun C Dorsaint Princesca P Sboner Andrea A Ogunwobi Olorunseun O OO

Frontiers in cell and developmental biology 20210727

High mortality rates of prostate cancer (PCa) are associated with metastatic castration-resistant prostate cancer (CRPC) due to the maintenance of androgen receptor (AR) signaling despite androgen deprivation therapies (ADTs). The 8q24 chromosomal locus is a region of very high PCa susceptibility that carries genetic variants associated with high risk of PCa incidence. This region also carries frequent amplifications of the PVT1 gene, a non-protein coding gene that encodes a cluster of microRNAs ...[more]

PMID: 34386489

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Project description:MicroRNAs are a class of small non-coding regulatory RNA molecules that regulate mRNAs post-transcriptionally. Recent evidence has shown that miRNAs target entire functionally related proteins such as protein complexes and biological pathways. However, characterizing the influence of miRNAs on genes whose encoded proteins are part of protein complexes has not been studied in the context of disease. We propose an entropy-based framework to identify miRNA-mediated dysregulation of functionally related proteins during prostate cancer progression. The proposed framework uses experimentally verified miRNA-target interactions, functionally related proteins and expression data to identify miRNA-influenced protein complexes in prostate cancer, and identify genes that are dysregulated as a result. The framework constructs correlation matrixes between functionally related proteins and miRNAs that have targets in the complex, and assesses the changes in the Shannon entropy of the modules across different stages of prostate cancer. Results reveal that SMAD4 and HDAC containing protein complexes are highly affected and disrupted by miRNAs, particularly miRNA-1 and miRNA-16. Using biological pathways to define functionally related proteins reveals that NF-kB-, RAS-, and Syndecan-mediated pathways are dysregulated due to miRNA-1- and miRNA-16-mediated regulation. These results suggest that miRNA-1 and miRNA-16 are important master regulators of miRNA-mediated regulation in prostate cancer. Moreover, results reveal that miRNAs with high-influence on the disrupted protein complexes are diagnostic and prognostic biomarker candidates for prostate cancer progression. The observation of miRNA-mediated protein complex regulation and miRNA-mediated pathway regulation, with partial experimental verification from previous studies, demonstrates that our framework is a promising approach for the identification of novel miRNAs and protein complexes related to disease progression.

Project description:BACKGROUND: Prostate cancer is one of the leading causes of cancer death in men. Androgen ablation, the most commonly-used therapy for progressive prostate cancer, is ineffective once the cancer cells become androgen-independent. The regulatory mechanisms that cause this transition (from androgen-dependent to androgen-independent) remain unknown. In this study, based on the microarray data comparing global gene expression patterns in the prostate tissue between androgen-dependent and -independent prostate cancer patients, we identify a set of transcription factors and microRNAs that potentially cause such difference, using a model-based computational approach. RESULTS: From 335 position weight matrices in the TRANSFAC database and 564 microRNAs in the microRNA registry, our model identify 5 transcription factors and 7 microRNAs to be potentially responsible for the level of androgen dependency. Of these transcription factors and microRNAs, the estimated function of all the 5 transcription factors are predicted to be inhibiting transcription in androgen-independent samples comparing with the dependent ones. Six out of 7 microRNAs, however, demonstrated stimulatory effects. We also find that the expression levels of three predicted transcription factors, including AP-1, STAT3 (signal transducers and activators of transcription 3), and DBP (albumin D-box) are significantly different between androgen-dependent and -independent patients. In addition, microRNA microarray data from other studies confirm that several predicted microRNAs, including miR-21, miR-135a, and miR-135b, demonstrate differential expression in prostate cancer cells, comparing with normal tissues. CONCLUSION: We present a model-based computational approach to identify transcription factors and microRNAs influencing the progression of androgen-dependent prostate cancer to androgen-independent prostate cancer. This result suggests that the capability of transcription factors to initiate transcription and microRNAs to facilitate mRNA degradation are both decreased in androgen-independent prostate cancer. The proposed model-based approach indicates that considering combinatorial effects of transcription factors and microRNAs in a unified model provides additional transcriptional and post-transcriptional regulatory mechanisms on global gene expression in the prostate cancer with different hormone-dependency.

Project description:Background and objectiveAfter radical prostatectomy (RP), prostate cancer (PCa) patients may experience biochemical recurrence (BCR) and clinical recurrence, which remains a dominant issue in PCa treatment. The purpose of this study was to identify a protein-coding gene classifier associated with microRNA (miRNA)-mediated regulation to provide a comprehensive prognostic index to predict PCa recurrence after RP.MethodsCandidate classifiers were constructed using two machine-learning algorithms (a least absolute shrinkage and selector operation [LASSO]-based classifier and a decision tree-based classifier) based on a discovery cohort (n = 156) from The Cancer Genome Atlas (TCGA) database. After selecting the LASSO-based classifier based on the prediction accuracy, both an internal validation cohort (n = 333) and an external validation cohort (n = 100) were used to examined the classifier using survival analysis, time-dependent receiver operating characteristic (ROC) curve analysis, and univariate and multivariate Cox proportional hazards regression analyses. Functional enrichment analysis of co-expressed genes was carried out to explore the underlying moleculer mechanisms of the genes included in the classifier.ResultsWe constructed a three-gene classifier that included FAM72B, GNE, and TRIM46, and we identified four upstream prognostic miRNAs (hsa-miR-133a-3p, hsa-miR-222-3p, hsa-miR-1301-3p, and hsa-miR-30c-2-3p). The classifier exhibited a remarkable ability (area under the curve [AUC] = 0.927) to distinguish PCa patients with high and low Gleason scores in the discovery cohort. Furthermore, it was significantly associated with clinical recurrence (p < 0.0001, log rank statistic = 20.7, AUC = 0.733) and could serve as an independent prognostic factor of recurrence-free survival (hazard ratio: 1.708, 95% CI: 1.180-2.472, p < 0.001). Additionally, it was a predictor of BCR according to BCR-free survival analysis (p = 0.0338, log rank statistic = 4.51).ConclusionsThe three-gene classifier associated with miRNA-mediated regulation may serve as a novel prognostic biomarker for PCa patients after RP.

Dataset Information

MicroRNA-1205 Regulation of FRYL in Prostate Cancer.

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MicroRNA-1205 Regulation of FRYL in Prostate Cancer.

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