Dataset Information

Screening key microRNAs for castration-resistant prostate cancer based on miRNA/mRNA functional synergistic network.

ABSTRACT: High-throughput methods have been used to explore the mechanisms by which androgen-sensitive prostate cancer (ASPC) develops into castration-resistant prostate cancer (CRPC). However, it is difficult to interpret cryptic results by routine experimental methods. In this study, we performed systematic and integrative analysis to detect key miRNAs that contribute to CRPC development. From three DNA microarray datasets, we retrieved 11 outlier microRNAs (miRNAs) that had expression discrepancies between ASPC and CRPC using a specific algorithm. Two of the miRNAs (miR-125b and miR-124) have previously been shown to be related to CRPC. Seven out of the other nine miRNAs were confirmed by quantitative PCR (Q-PCR) analysis. MiR-210, miR-218, miR-346, miR-197, and miR-149 were found to be over-expressed, while miR-122, miR-145, and let-7b were under-expressed in CRPC cell lines. GO and KEGG pathway analyses revealed that miR-218, miR-197, miR-145, miR-122, and let-7b, along with their target genes, were found to be involved in the PI3K and AKT3 signaling network, which is known to contribute to CRPC development. We then chose five miRNAs to verify the accuracy of the analysis. The target genes of each miRNA were altered significantly upon transfection of specific miRNA mimics in the C4-2 CRPC cell line, which was consistent with our pathway analysis results. Finally, we hypothesized that miR-218, miR-145, miR-197, miR-149, miR-122, and let-7b may contribute to the development of CRPC through the influence of Ras, Rho proteins, and the SCF complex. Further investigation is needed to verify the functions of the identified novel pathways in CRPC development.

SUBMITTER: Zhu J

PROVIDER: S-EPMC4791269 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Screening key microRNAs for castration-resistant prostate cancer based on miRNA/mRNA functional synergistic network.

Zhu Jin J Wang Sugui S Zhang Wenyu W Qiu Junyi J Shan Yuxi Y Yang Dongrong D Shen Bairong B

Oncotarget 20151201 41

High-throughput methods have been used to explore the mechanisms by which androgen-sensitive prostate cancer (ASPC) develops into castration-resistant prostate cancer (CRPC). However, it is difficult to interpret cryptic results by routine experimental methods. In this study, we performed systematic and integrative analysis to detect key miRNAs that contribute to CRPC development. From three DNA microarray datasets, we retrieved 11 outlier microRNAs (miRNAs) that had expression discrepancies bet ...[more]

PMID: 26540468

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Project description:Prostate cancer (PC) is one of the major male cancers. Differential diagnosis of PC is indispensable for the individual therapy, i.e., Gleason score (GS) that describes the grade of cancer can be used to choose the appropriate therapy. However, the current techniques for PC diagnosis and prognosis are not always effective. To identify potential markers that could be used for differential diagnosis of PC, we analyzed miRNA-mRNA interactions and we build specific networks for PC onset and progression. Key differentially expressed miRNAs for each GS were selected by calculating three parameters of network topology measures: the number of their single regulated mRNAs (NSR), the number of target genes (NTG) and NSR/NTG. miRNAs that obtained a high statistically significant value of these three parameters were chosen as potential biomarkers for computational validation and pathway analysis. 20 miRNAs were identified as key candidates for PC. 8 out of 20 miRNAs (miR-25-3p, miR-93-3p, miR-122-5p, miR-183-5p, miR-615-3p, miR-7-5p, miR-375, and miR-92a-3p) were differentially expressed in all GS and proposed as biomarkers for PC onset. In addition, "Extracellular-receptor interaction", "Focal adhesion", and "microRNAs in cancer" were significantly enriched by the differentially expressed target genes of the identified miRNAs. miR-10a-5p was found to be differentially expressed in GS 6, 7, and 8 in PC samples. 3 miRNAs were identified as PC GS-specific differentially expressed miRNAs: miR-155-5p was identified in PC samples with GS 6, and miR-142-3p and miR-296-3p in PC samples with GS 9. The efficacy of 20 miRNAs as potential biomarkers was revealed with a Random Forest classification using an independent dataset. The results demonstrated our 20 miRNAs achieved a better performance (AUC: 0.73) than miRNAs selected with Boruta algorithm (AUC: 0.55), a method for the automated feature extraction. Studying miRNA-mRNA associations, key miRNAs were identified with a computational approach for PC onset and progression. Further experimental validations are needed for future translational development.

Project description:Purpose: Most prostate cancers (PCs) initially respond to androgen deprivation therapy (ADT), but eventually many PC patients develop castration resistant PC (CRPC). Currently, available drugs that have been approved for the treatment of CRPC patients are limited. Computational drug repositioning methods using public databases represent a promising and efficient tool for discovering new uses for existing drugs. The purpose of the present study is to predict drug candidates that can treat CRPC using a computational method that integrates publicly available gene expression data of tumors from CRPC patients, drug-induced gene expression data and drug response activity data. Methods: Gene expression data from tumoral and normal or benign prostate tissue samples in CRPC patients were downloaded from the Gene Expression Omnibus (GEO) and differentially expressed genes (DEGs) in CRPC were determined with a meta-signature analysis by a metaDE R package. Additionally, drug activity data were downloaded from the ChEMBL database. Furthermore, the drug-induced gene expression data were downloaded from the LINCS database. The reversal relationship between the CRPC and drug gene expression signatures as the Reverse Gene Expression Scores (RGES) were computed. Drug candidates to treat CRPC were predicted using summarized scores (sRGES). Additionally, synergic effects of drug combinations were predicted with a Target Inhibition interaction using the Minimization and Maximization Averaging (TIMMA) algorithm. Results: The drug candidates of sorafenib, olaparib, elesclomol, tanespimycin, and ponatinib were predicted to be active for the treatment of CRPC. Meanwhile, CRPC-related genes, in this case MYL9, E2F2, APOE, and ZFP36, were identified as having gene expression data that can be reversed by these drugs. Additionally, lenalidomide in combination with pazopanib was predicted to be most potent for CRPC. Conclusion: These findings support the use of a computational reversal gene expression approach to identify new drug and drug combination candidates that can be used to treat CRPC.

Project description:Docetaxel chemotherapy remains a standard of care for metastatic castration-resistant prostate cancer (CRPC). Docetaxel modestly increases survival, yet results in frequent occurrence of side effects and resistant disease. An alternate chemotherapy with greater efficacy and minimal side effects is needed. Acquisition of metabolic aberrations promoting increased survival and metastasis in CRPC cells includes constitutive activation of Akt, loss of adenosine monophosphate-activated protein kinase (AMPK) activity due to Ser-485/491 phosphorylation, and overexpression of 3-hydroxy-3-methylglutaryl-Coenzyme A reductase (HMG-CoAR). We report that combination of simvastatin and metformin, within pharmacologic dose range (500 nmol/L to 4 μmol/L simvastatin and 250 μmol/L to 2 mmol/L metformin), significantly and synergistically reduces C4-2B3/B4 CRPC cell viability and metastatic properties, with minimal adverse effects on normal prostate epithelial cells. Combination of simvastatin and metformin decreased Akt Ser-473 and Thr-308 phosphorylation and AMPKα Ser-485/491 phosphorylation; increased Thr-172 phosphorylation and AMPKα activity, as assessed by increased Ser-79 and Ser-872 phosphorylation of acetyl-CoA carboxylase and HMG-CoAR, respectively; decreased HMG-CoAR activity; and reduced total cellular cholesterol and its synthesis in both cell lines. Studies of C4-2B4 orthotopic NCr-nu/nu mice further demonstrated that combination of simvastatin and metformin (3.5-7.0 μg/g body weight simvastatin and 175-350 μg/g body weight metformin) daily by oral gavage over a 9-week period significantly inhibited primary ventral prostate tumor formation, cachexia, bone metastasis, and biochemical failure more effectively than 24 μg/g body weight docetaxel intraperitoneally injected every 3 weeks, 7.0 μg/g/day simvastatin, or 350 μg/g/day metformin treatment alone, with significantly less toxicity and mortality than docetaxel, establishing combination of simvastatin and metformin as a promising chemotherapeutic alternative for metastatic CRPC.

Dataset Information

Screening key microRNAs for castration-resistant prostate cancer based on miRNA/mRNA functional synergistic network.

Publications

Screening key microRNAs for castration-resistant prostate cancer based on miRNA/mRNA functional synergistic network.

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