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• W2912941711 abstract "A subset of men with prostate cancer develops aggressive disease. We sought to determine whether miR-182, an miRNA with reported oncogenic functions in the prostate, is associated with biochemical recurrence and aggressive disease. Prostate epithelial miR-182 expression was quantified via in situ hybridization of two prostate tissue microarrays and by laser-capture microdissection of prostate epithelium. miR-182 was significantly higher in cancer epithelium than adjacent benign epithelium (P < 0.0001). The ratio of cancer to benign miR-182 expression per patient was inversely associated with recurrence in a multivariate logistic regression model (odds ratio = 0.18; 95% CI, 0.03–0.89; P = 0.044). Correlation of miR-182 with mRNA expression in laser-capture microdissected benign prostate epithelium was used to predict prostatic miR-182 targets. Genes that were negatively correlated with miR-182 were enriched for its predicted targets and for genes previously identified as up-regulated in prostate cancer metastases. miR-182 expression was also negatively correlated with genes previously identified as up-regulated in primary prostate tumors from African American patients, who are at an increased risk of developing aggressive prostate cancer. Taken together, these results suggest that although miR-182 is expressed at higher levels in localized prostate cancer, its levels are lower in aggressive cancers, suggesting a biphasic role for this miRNA that may be exploited for prognostic and/or therapeutic purposes to reduce prostate cancer progression. A subset of men with prostate cancer develops aggressive disease. We sought to determine whether miR-182, an miRNA with reported oncogenic functions in the prostate, is associated with biochemical recurrence and aggressive disease. Prostate epithelial miR-182 expression was quantified via in situ hybridization of two prostate tissue microarrays and by laser-capture microdissection of prostate epithelium. miR-182 was significantly higher in cancer epithelium than adjacent benign epithelium (P < 0.0001). The ratio of cancer to benign miR-182 expression per patient was inversely associated with recurrence in a multivariate logistic regression model (odds ratio = 0.18; 95% CI, 0.03–0.89; P = 0.044). Correlation of miR-182 with mRNA expression in laser-capture microdissected benign prostate epithelium was used to predict prostatic miR-182 targets. Genes that were negatively correlated with miR-182 were enriched for its predicted targets and for genes previously identified as up-regulated in prostate cancer metastases. miR-182 expression was also negatively correlated with genes previously identified as up-regulated in primary prostate tumors from African American patients, who are at an increased risk of developing aggressive prostate cancer. Taken together, these results suggest that although miR-182 is expressed at higher levels in localized prostate cancer, its levels are lower in aggressive cancers, suggesting a biphasic role for this miRNA that may be exploited for prognostic and/or therapeutic purposes to reduce prostate cancer progression. Prostate cancer (PCa) has the highest incidence of any cancer in men, and although most patients have organ-confined disease, approximately 1 in 10 patients will die of their cancer.1Siegel R.L. Miller K.D. Jemal A. Cancer statistics, 2018.CA Cancer J Clin. 2018; 68: 7-30Crossref PubMed Scopus (6444) Google Scholar Classifying prostate tumors as indolent or aggressive remains a challenge both biologically and clinically. For localized or regional PCa, radical prostatectomy and radiation therapy are potentially curative. However, these treatments often cause morbidities.2Lardas M. Liew M. van den Bergh R.C. De Santis M. Bellmunt J. Van den Broeck T. Cornford P. Cumberbatch M.G. Fossati N. Gross T. Henry A.M. Bolla M. Briers E. Joniau S. Lam T.B. Mason M.D. Mottet N. van der Poel H.G. Rouviere O. Schoots I.G. Wiegel T. Willemse P.M. Yuan C.Y. Bourke L. Quality of life outcomes after primary treatment for clinically localised prostate cancer: a systematic review.Eur Urol. 2017; 72: 869-885Abstract Full Text Full Text PDF PubMed Scopus (142) Google Scholar Tissue-based biomarker panels can be used to complement clinical nomograms to guide treatment decisions3Cooperberg M.R. Pasta D.J. Elkin E.P. Litwin M.S. Latini D.M. Du Chane J. Carroll P.R. The University of California, San Francisco cancer of the prostate risk assessment score: a straightforward and reliable preoperative predictor of disease recurrence after radical prostatectomy.J Urol. 2005; 173: 1938-1942Crossref PubMed Scopus (520) Google Scholar, 4Carroll P.R. Parsons J.K. Andriole G. Bahnson R.R. Castle E.P. Catalona W.J. Dahl D.M. Davis J.W. Epstein J.I. Etzioni R.B. Farrington T. Hemstreet 3rd, G.P. Kawachi M.H. Kim S. Lange P.H. Loughlin K.R. Lowrance W. Maroni P. Mohler J. Morgan T.M. Moses K.A. Nadler R.B. Poch M. Scales C. Shaneyfelt T.M. Smaldone M.C. Sonn G. Sprenkle P. Vickers A.J. Wake R. Shead D.A. Freedman-Cass D.A. NCCN guidelines insights: prostate cancer early detection, version 2.2016.J Natl Compr Canc Netw. 2016; 14: 509-519Crossref PubMed Scopus (235) Google Scholar and have shown utility for predicting disease recurrence after prostatectomy.5Cullen J. Rosner I.L. Brand T.C. Zhang N. Tsiatis A.C. Moncur J. Ali A. Chen Y. Knezevic D. Maddala T. Lawrence H.J. Febbo P.G. Srivastava S. Sesterhenn I.A. McLeod D.G. A biopsy-based 17-gene genomic prostate score predicts recurrence after radical prostatectomy and adverse surgical pathology in a racially diverse population of men with clinically low- and intermediate-risk prostate cancer.Eur Urol. 2015; 68: 123-131Abstract Full Text Full Text PDF PubMed Scopus (229) Google Scholar, 6Freedland S.J. Gerber L. Reid J. Welbourn W. Tikishvili E. Park J. Younus A. Gutin A. Sangale Z. Lanchbury J.S. Salama J.K. Stone S. Prognostic utility of cell cycle progression score in men with prostate cancer after primary external beam radiation therapy.Int J Radiat Oncol Biol Phys. 2013; 86: 848-853Abstract Full Text Full Text PDF PubMed Scopus (146) Google Scholar, 7Den R.B. Yousefi K. Trabulsi E.J. Abdollah F. Choeurng V. Feng F.Y. Dicker A.P. Lallas C.D. Gomella L.G. Davicioni E. Karnes R.J. Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy.J Clin Oncol. 2015; 33: 944-951Crossref PubMed Scopus (163) Google Scholar The expression of miRNAs, small noncoding RNAs that regulate mRNA translation,8Selbach M. Schwanhausser B. Thierfelder N. Fang Z. Khanin R. Rajewsky N. Widespread changes in protein synthesis induced by microRNAs.Nature. 2008; 455: 58-63Crossref PubMed Scopus (2783) Google Scholar is dysregulated in many cancers, including PCa.9Lu J. Getz G. Miska E.A. Alvarez-Saavedra E. Lamb J. Peck D. Sweet-Cordero A. Ebert B.L. Mak R.H. Ferrando A.A. Downing J.R. Jacks T. Horvitz H.R. Golub T.R. MicroRNA expression profiles classify human cancers.Nature. 2005; 435: 834-838Crossref PubMed Scopus (8201) Google Scholar Currently, no miRNA biomarker test for PCa is used clinically, although several studies have described promising results that tissue or serum miRNAs have diagnostic and/or prognostic utility for PCa.10Mihelich B.L. Maranville J.C. Nolley R. Peehl D.M. Nonn L. Elevated serum microRNA levels associate with absence of high-grade prostate cancer in a retrospective cohort.PLoS One. 2015; 10: e0124245Crossref PubMed Scopus (64) Google Scholar, 11Ren Q. Liang J. Wei J. Basturk O. Wang J. Daniels G. Gellert L.L. Li Y. Shen Y. Osman I. Zhao J. Melamed J. Lee P. Epithelial and stromal expression of miRNAs during prostate cancer progression.Am J Transl Res. 2014; 6: 329-339PubMed Google Scholar, 12Fabris L. Ceder Y. Chinnaiyan A.M. Jenster G.W. Sorensen K.D. Tomlins S. Visakorpi T. Calin G.A. The potential of microRNAs as prostate cancer biomarkers.Eur Urol. 2016; 70: 312-322Abstract Full Text Full Text PDF PubMed Scopus (199) Google Scholar, 13Bonci D. Coppola V. Patrizii M. Addario A. Cannistraci A. Francescangeli F. Pecci R. Muto G. Collura D. Bedini R. Zeuner A. Valtieri M. Sentinelli S. Benassi M.S. Gallucci M. Carlini P. Piccolo S. De Maria R. A microRNA code for prostate cancer metastasis.Oncogene. 2016; 35: 1180-1192Crossref PubMed Scopus (109) Google Scholar Thus, miRNAs may augment existing PCa prognostic tools and provide insight into cellular pathways that differentiate indolent and aggressive PCa. miR-182, a member of the miR-183 family, is considered an oncomiR and is consistently present at high levels in PCa.14Mihelich B.L. Khramtsova E.A. Arva N. Vaishnav A. Johnson D.N. Giangreco A.A. Martens-Uzunova E. Bagasra O. Kajdacsy-Balla A. Nonn L. Mir-183-96-182 cluster is overexpressed in prostate tissue and regulates zinc homeostasis in prostate cells.J Biol Chem. 2011; 286: 44503-44511Crossref PubMed Scopus (116) Google Scholar, 15Tsuchiyama K. Ito H. Taga M. Naganuma S. Oshinoya Y. Nagano K. Yokoyama O. Itoh H. Expression of micrornas associated with Gleason grading system in prostate cancer: mir-182-5p is a useful marker for high grade prostate cancer.Prostate. 2013; 73: 827-834Crossref PubMed Scopus (51) Google Scholar, 16Sun Y. Jia X. Hou L. Liu X. Screening of differently expressed miRNA and mRNA in prostate cancer by integrated analysis of transcription data.Urology. 2016; 94: 313.e1-313.e6Abstract Full Text Full Text PDF Scopus (22) Google Scholar, 17Hirata H. Ueno K. Shahryari V. Deng G. Tanaka Y. Tabatabai Z.L. Hinoda Y. Dahiya R. MicroRNA-182-5p promotes cell invasion and proliferation by down regulating FOXF2, RECK and MTSS1 genes in human prostate cancer.PLoS One. 2013; 8: e55502Crossref PubMed Scopus (129) Google Scholar, 18Yao J. Xu C. Fang Z. Li Y. Liu H. Wang Y. Xu C. Sun Y. Androgen receptor regulated microrna Mir-182-5p promotes prostate cancer progression by targeting the ARRDC3/ITGB4 pathway.Biochem Biophys Res Commun. 2016; 474: 213-219Crossref PubMed Scopus (55) Google Scholar miR-182 regulates genes involved in proliferation and the Wnt and PI3K pathways, which are known drivers of PCa.14Mihelich B.L. Khramtsova E.A. Arva N. Vaishnav A. Johnson D.N. Giangreco A.A. Martens-Uzunova E. Bagasra O. Kajdacsy-Balla A. Nonn L. Mir-183-96-182 cluster is overexpressed in prostate tissue and regulates zinc homeostasis in prostate cells.J Biol Chem. 2011; 286: 44503-44511Crossref PubMed Scopus (116) Google Scholar, 17Hirata H. Ueno K. Shahryari V. Deng G. Tanaka Y. Tabatabai Z.L. Hinoda Y. Dahiya R. MicroRNA-182-5p promotes cell invasion and proliferation by down regulating FOXF2, RECK and MTSS1 genes in human prostate cancer.PLoS One. 2013; 8: e55502Crossref PubMed Scopus (129) Google Scholar, 18Yao J. Xu C. Fang Z. Li Y. Liu H. Wang Y. Xu C. Sun Y. Androgen receptor regulated microrna Mir-182-5p promotes prostate cancer progression by targeting the ARRDC3/ITGB4 pathway.Biochem Biophys Res Commun. 2016; 474: 213-219Crossref PubMed Scopus (55) Google Scholar, 19Dambal S. Baumann B. McCray T. Williams L. Richards Z. Deaton R. Prins G.S. Nonn L. The Mir-183 family cluster alters zinc homeostasis in benign prostate cells, organoids and prostate cancer xenografts.Sci Rep. 2017; 7: 7704Crossref PubMed Scopus (14) Google Scholar, 20Wang D. Lu G. Shao Y. Xu D. Mir-182 promotes prostate cancer progression through activating Wnt/Beta-catenin signal pathway.Biomed Pharmacother. 2018; 99: 334-339Crossref PubMed Scopus (44) Google Scholar, 21Wallis C.J. Gordanpour A. Bendavid J.S. Sugar L. Nam R.K. Seth A. Mir-182 is associated with growth, migration and invasion in prostate cancer via suppression of FOXO1.J Cancer. 2015; 6: 1295-1305Crossref PubMed Scopus (49) Google Scholar, 22Liu R. Li J. Teng Z. Zhang Z. Xu Y. Overexpressed microRNA-182 promotes proliferation and invasion in prostate cancer PC-3 cells by down-regulating N-Myc downstream regulated gene 1 (NDRG1).PLoS One. 2013; 8: e68982Crossref PubMed Scopus (47) Google Scholar miR-182 and other miRNAs in the miR-183 family regulate prostate zinc homeostasis through direct translational inhibition of SLC39A1, which encodes a key zinc transporter.14Mihelich B.L. Khramtsova E.A. Arva N. Vaishnav A. Johnson D.N. Giangreco A.A. Martens-Uzunova E. Bagasra O. Kajdacsy-Balla A. Nonn L. Mir-183-96-182 cluster is overexpressed in prostate tissue and regulates zinc homeostasis in prostate cells.J Biol Chem. 2011; 286: 44503-44511Crossref PubMed Scopus (116) Google Scholar Zinc depletion has been implicated in prostate carcinogenesis,23Costello L.C. Franklin R.B. A comprehensive review of the role of zinc in normal prostate function and metabolism; and its implications in prostate cancer.Arch Biochem Biophys. 2016; 611: 100-112Crossref PubMed Scopus (120) Google Scholar and patients with biochemical recurrence were found in a retrospective study to have 21% lower levels of zinc in tumor-adjacent benign tissue than patients with nonrecurrent disease.24Sarafanov A.G. Todorov T.I. Centeno J.A. Macias V. Gao W. Liang W.M. Beam C. Gray M.A. Kajdacsy-Balla A.A. Prostate cancer outcome and tissue levels of metal ions.Prostate. 2011; 71: 1231-1238Crossref PubMed Scopus (32) Google Scholar In light of these findings with recurrence and the high level of miR-182 in PCa, we hypothesized that miR-182 may associate with biochemical recurrence and that miR-182 in benign tissue may regulate pathways that prime the tissue for aggressive disease. We examined the expression of miR-182 in relation to clinical markers of aggressive PCa, such as high Gleason grade and biochemical recurrence. miR-182 expression was quantified in tissues from patients with PCa through in situ hybridization (ISH) of a prostate tissue microarray (TMA), and quantitative RT-PCR (RT-qPCR) of laser-captured microdissected (LCM) prostate epithelium. Correlation of miR-182 with gene expression in LCM-collected prostate epithelium was used to predict tissue-specific targets. These approaches facilitated investigation of prostate epithelium and avoided analyzing the more prevalent stroma, which can bias results for this epithelial-specific miRNA. Our results suggest that miR-182 is a complex oncomiR that is higher in PCa compared with benign tissues, but within patients with PCa, the levels of the miRNA associated with aggressive tumor characteristics and PCa recurrence are lower. RWPE1 cells were acquired from ATCC (Manassas, VA) in 2014, used at passage <20, and were maintained in RPMI 1640 medium and 10% fetal bovine serum. Cells were transduced with lentivirus that contained full miR-183 family cluster sequence or a control vector and sorted with fluorescence-activated cell sorting for green fluorescent protein expression.19Dambal S. Baumann B. McCray T. Williams L. Richards Z. Deaton R. Prins G.S. Nonn L. The Mir-183 family cluster alters zinc homeostasis in benign prostate cells, organoids and prostate cancer xenografts.Sci Rep. 2017; 7: 7704Crossref PubMed Scopus (14) Google Scholar These cells were grown in a 50% Matrigel (Corning, Corning, NY) suspension for 8 days, dissociated with Dispase (Stemcell Technologies, Vancouver, Canada), suspended in Histogel (Thermo Fisher, Waltham, MA), formalin fixed, and paraffin embedded before ISH. The Outcome TMA was constructed by the National Cancer Institute–sponsored Cooperative Prostate Cancer Tissue Resource.25Kajdacsy-Balla A. Geynisman J.M. Macias V. Setty S. Nanaji N.M. Berman J.J. Dobbin K. Melamed J. Kong X. Bosland M. Orenstein J. Bayerl J. Becich M.J. Dhir R. Datta M.W. Practical aspects of planning, building, and interpreting tissue microarrays: the cooperative prostate cancer tissue resource experience.J Mol Histol. 2007; 38: 113-121Crossref PubMed Scopus (35) Google Scholar, 26Ananthanarayanan V. Deaton R.J. Amatya A. Macias V. Luther E. Kajdacsy-Balla A. Gann P.H. Subcellular localization of p27 and prostate cancer recurrence: automated digital microscopy analysis of tissue microarrays.Hum Pathol. 2011; 42: 873-881Crossref PubMed Scopus (14) Google Scholar This TMA was designed as a case-control study for biochemical recurrence after prostatectomy. The specimens were collected between 1988 and 2002. All patients with biochemical nonrecurrence were followed up for a minimum of 5 years and five serum prostate-specific antigen (PSA) measurements. Recurrence was defined as a postsurgical PSA value ≥0.4 ng/mL or two consecutive values ≥0.2 ng/mL. The original TMA contained 404 patients with four tumor cores per patient; however, many cores have been depleted. Data were collected from 133 patients, 56 of whom had both cancer and benign epithelium present. Cores with a diameter of 0.6 mm were taken from tumor regions of tissue. The number of cores analyzed per patient ranged 1 to 4 (mean, 2.4 cores). The TMA is publicly available and completely deidentified through the Cooperative Prostate Cancer Tissue Resource. The Murphy TMA was constructed based on patients undergoing radical prostatectomy at the Jesse Brown Veterans Affairs Medical Center for clinically localized PCa. Collaborating pathologists performed centralized pathologic review and assembled the TMA from the formalin-fixed, paraffin-embedded prostatectomy specimen with pathologic and clinical data. Cores were selected from the highest Gleason grade region of the prostatectomy specimen with care to punch cores from areas of >75% tumor epithelium and from the contralateral normal benign epithelium. The prostatectomy tissues were collected between 2013 and 2017. Cores with a 1-mm diameter were taken from tumor and benign regions of tissue. The TMA contains cores from 66 patients with three tumor cores and two benign cores per patient. Fifty-five patients were analyzed, and the number of cores analyzed per patient ranged 2 to 4 (mean, 3.7 cores). Patients consented to the use of their tissues for PCa research. Specimens are deidentified. The tissue collection was approved by the Jesse Brown Veterans Affairs Institutional Review Board. Additional deidentified prostatectomy tissues analyzed were part of a cohort of University of Illinois at Chicago (UIC) patients and the Cooperative Human Tissue Network approved by the UIC Office for the Protection of Research Subjects under UIC Institutional Review Board 2013-0341 as previously described.27Richards Z. Batai K. Farhat R. Shah E. Makowski A. Gann P.H. Kittles R. Nonn L. Prostatic compensation of the vitamin D axis in African American men.JCI Insight. 2017; 2: e91054Crossref PubMed Scopus (19) Google Scholar A 5-μm tissue section adjacent to the section used for ISH was probed for rabbit polyclonal cytokeratin 5 (KRT5, clone Poly19055, BioLegend, San Diego, CA) and mouse monoclonal pan-cytokeratin AE1/AE3 (ab27988, Abcam, Cambridge, UK) antibodies diluted to 1:200. Antigens were retrieved using sodium citrate buffer, pH 6, 100°C for 5 minutes at 5 psi. Alexafluor 555– and 488–labeled secondaries (Invitrogen, Carlsbad, CA) were used at 1:200, followed by DAPI nuclear counterstain. Slides were imaged on the Vectra Automated Multispectral Imaging System (PerkinElmer, Waltham, MA) at the Research Histology and Tissue Imaging Core at UIC. The other adjacent section was hematoxylin and eosin (H&E) stained and scanned with Aperio AT2 (Leica, Wetzlar, Germany) at the Research Histology and Tissue Imaging Core. The protocol from the miRCURY LNA miRNA ISH optimization kit (Exiqon, Vedbaek, Denmark) was followed with modifications. Formalin-fixed, paraffin-embedded TMA sections (5 μm) were placed onto hydrophilic slides, baked overnight at 60°C, deparaffinized, and incubated for 20 minutes at 37°C with 15 μg/mL of proteinase K for protein digestion. Digoxigenin-labeled miR-182 LNA probe (80 nmol/L), digoxigenin-labeled U6 LNA probe (10 nmol/L) (positive control), or no probe (negative control) was incubated at 48°C for 60 minutes followed by stepwise 5-minute washes in saline-sodium citrate buffer at 42°C (×1, ×−0.5, ×−0.2, and then ×0.2) at room temperature. Slides were blocked and incubated for 60 minutes with alkaline phosphatase–conjugated anti-digoxigenin antibody (Sigma-Aldrich, St. Louis, MO) at 1:200. Alkaline phosphatase was visualized with Vector Red alkaline phosphatase substrate (Vector Laboratories, Burlingame, CA) for 90 minutes and stopped with KTBT buffer. Slides were counterstained with DAPI. miR-182 ISH was imaged on the Vectra Automated Multispectral Imaging System (PerkinElmer) at the Research Histology and Tissue Imaging Core at UIC. Cores were imaged at ×20 magnification and tiled. Images were unmixed using a spectral library for Vector Red signal created using Nuance software version 3.0.2 (PerkinElmer) with inForm Advanced Image Analysis software version 2.4.1 (PerkinElmer). For the Outcome TMA, cores that could be unambiguously identified and that contained ISH signal were segmented by a pathologist (A.M.A.) using an adjacent H&E reference slide. Epithelium of adenocarcinoma, benign glands, and high-grade prostatic intraepithelial neoplasia (PIN) were manually selected in each core for quantitation of Vector Red fluorescence. Representative areas were circled, and, in cores with more than a single type of epithelium of interest (eg, adenocarcinoma and benign prostate glands), equivalent amounts of each cell type were selected. Adenocarcinoma was identified according to architectural and cytologic parameters: increased nuclear size, decreased nucleocytoplasmic ratio or prominent nucleoli, crowded acini, fused glands, cribriform masses, solid sheets, and/or single infiltrating cells. High-grade PIN was identified by nuclear enlargement, prominent nucleoli, and epithelial cell crowding with visible basal cells and absence of diagnostic criteria for intraductal carcinoma of the prostate.28Guo C.C. Epstein J.I. Intraductal carcinoma of the prostate on needle biopsy: histologic Features and clinical significance.Mod Pathol. 2006; 19: 1528-1535Crossref PubMed Scopus (255) Google Scholar Glands with simple atrophy without inflammation were selected as benign epithelium. All other benign lesions, including histologic variants of atrophy, basal cell hyperplasia, prostatitis, and atypical adenomatous hyperplasia, were excluded. For the Murphy TMA, an adjacent H&E slide was used to select representative benign epithelium, excluding atrophy and PIN from benign cores, and representative adenocarcinoma from tumor cores. Benign epithelium cores were reviewed and approved by a pathologist after segmentation. LCM of benign prostate epithelium from frozen prostatectomy tissue and RNA isolation was performed previously.27Richards Z. Batai K. Farhat R. Shah E. Makowski A. Gann P.H. Kittles R. Nonn L. Prostatic compensation of the vitamin D axis in African American men.JCI Insight. 2017; 2: e91054Crossref PubMed Scopus (19) Google Scholar Briefly, cDNA was synthesized from 60 ng of LCM-collected RNA with Universal RT miRNA reagents (Exiqon). qPCR was run in triplicate for miR-182 using the miRCURY LNA miRNA PCR System (Exiqon) and three housekeeping genes (RNU44, RNU48, and RNU66) using SYBR green (BioRad, Hercules, CA) and QuantStudio 6 (Thermo Fisher) with the following settings: 95°C for 10 minutes (×1), 95°C for 15 seconds (×50), and 60°C for 1 minute (×50). For quality control, patients with low housekeeper correlation were excluded from subsequent analysis (Supplemental Figure S1A). miR-182 relative quantity was calculated by the −ΔΔCt method, using the mean Ct of the housekeeping genes for normalization. RNA from 13 African American and 13 patients of European ancestry were analyzed using GeneChip 1.0 Human Gene ST arrays (Affymetrix, Santa Clara, CA) and previously reported in Richards et al27Richards Z. Batai K. Farhat R. Shah E. Makowski A. Gann P.H. Kittles R. Nonn L. Prostatic compensation of the vitamin D axis in African American men.JCI Insight. 2017; 2: e91054Crossref PubMed Scopus (19) Google Scholar (Gene Expression Omnibus; https://www.ncbi.nlm.nih.gov/geo; accession number GSE91037). Expression data were normalized using Robust Multiarray Average method in the R package Affy.29Gautier L. Cope L. Bolstad B.M. Irizarry R.A. Affy--analysis of Affymetrix Genechip data at the probe level.Bioinformatics. 2004; 20: 307-315Crossref PubMed Scopus (3864) Google Scholar Data quality was evaluated using affyPLM,30Bolstad B.M. Collin F. Brettschneider J. Simpson K. Cope L. Irizarry R.A. Speed T.P. Quality Assesment of Affymetrix Genechip Data. Springer, New York2005Google Scholar and three arrays (GSM2420027, GSM2420029, and GSM2420033) were excluded from this study based on normalized unscaled SEM plots (Supplemental Figure S1B). Spearman's ρ and P values were calculated using the relative quantity of miR-182 expression and the log2 (Robust Multiarray Average) expression values of each probe set for 21 patients using the cor.test function, specifying Spearman correlation, in the stats package of R version 3.3.331R Core TeamR: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria2017Google Scholar (Supplemental Table S1). Primary prostate epithelial cells were isolated from deidentified radical prostatectomy tissue specimens as previously described under UIC Office for the Protection of Research Subjects–approved Institutional Review Board 2011-1138.14Mihelich B.L. Khramtsova E.A. Arva N. Vaishnav A. Johnson D.N. Giangreco A.A. Martens-Uzunova E. Bagasra O. Kajdacsy-Balla A. Nonn L. Mir-183-96-182 cluster is overexpressed in prostate tissue and regulates zinc homeostasis in prostate cells.J Biol Chem. 2011; 286: 44503-44511Crossref PubMed Scopus (116) Google Scholar Cells were grown in PrEGM media (Lonza, Basel, Switzerland) and transfected with miR-182 pre-miRNAs (Thermo Fisher) or mock transfected using siPORT NeoFX (Life Technologies, Carlsbad, CA). After 24 hours, RNA was Trizol (Invitrogen) extracted. cDNAs were made using High-Capacity cDNA RT kit (Invitrogen). Primers are listed in Table 1. qPCR was run using SYBR green and QuantStudio 6 (Thermo Fisher). PCR settings were as follows: 95°C for 10 minutes (×1), 95°C for 15 seconds, 58°C for 30 seconds, and 72°C for 30 seconds (×40). Relative quantity was calculated by the −ΔΔCt method, using β2-microglobulin for normalization.Table 1Primers for Quantitative RT-PCR Validation of Predicted miR-182 Gene TargetsGenePrimersCD164FWD5′-TTAGCTTTCTCCCGAACGCC-3′RVS5′-GCAGCTGTTTCGACCTTCAC-3′ELL2FWD5′-ATGTGAAGCTCACCGAGACG-3′RVS5′-TTTGACAAGCCCGTGGAGTC-3′PRKAR1AFWD5′-ACACCCAGAGAGGGACAGAGAA-3′RVS5′-GAGCTCACATTCTCGAAGGCT-3′RNF152FWD5′-AGACTCGGTGACAGATACAGAAAT-3′RVS5′-TGCAGGTAATGGCAAGCTCA-3′NR3C1FWD5′-GTTGTTTATCTCGGCTGCGG-3′RVS5′-TCAGTGAATATCAACTCTGGCA-3′B2MFWD5′-CCTGAATTGCTATGTGTCTGGG-3′RVS5′-TGATGCTGCTTACATGTCTCGA-3′FWD, forward; RVS, reverse. Open table in a new tab FWD, forward; RVS, reverse. Gene Set Enrichment Analysis version 3.0 software is from the Broad Institute.32Subramanian A. Tamayo P. Mootha V.K. Mukherjee S. Ebert B.L. Gillette M.A. Paulovich A. Pomeroy S.L. Golub T.R. Lander E.S. Mesirov J.P. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.Proc Natl Acad Sci U S A. 2005; 102: 15545-15550Crossref PubMed Scopus (26549) Google Scholar The correlation coefficients for genes with multiple probe sets were averaged together. To mimic expression data input, the negative correlation coefficients were multiplied by −1 and input in triplicate as negative correlation samples and the positive correlation coefficients in triplicate as positive correlation samples. Because of the small sample size, gene set permutation was used to calculate statistics. The miR-182-5p targets were predicted from TargetScan version 7.1 with a cumulative-weighted context score <−0.5,33Grimson A. Farh K.K. Johnston W.K. Garrett-Engele P. Lim L.P. Bartel D.P. MicroRNA targeting specificity in mammals: determinants beyond seed pairing.Mol Cell. 2007; 27: 91-105Abstract Full Text Full Text PDF PubMed Scopus (3032) Google Scholar miRDB with a target score >0.85,34Wong N. Wang X. MiRDB: an online resource for MicroRNA target prediction and functional annotations.Nucleic Acids Res. 2015; 43: D146-D152Crossref PubMed Scopus (1295) Google Scholar and TarBase version 8 with a prediction score >0.85.35Karagkouni D. Paraskevopoulou M.D. Chatzopoulos S. Vlachos I.S. Tastsoglou S. Kanellos I. Papadimitriou D. Kavakiotis I. Maniou S. Skoufos G. Vergoulis T. Dalamagas T. Hatzigeorgiou A.G. DIANA-Tarbase V8: a decade-long collection of experimentally supported Mirna-Gene interactions.Nucleic Acids Res. 2018; 46: D239-D245Crossref PubMed Scopus (538) Google Scholar Other gene sets were downloaded from MSigDB version 6.1, including Kyoto Encyclopedia of Genes and Genomes version 6.1,36Kanehisa M. Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes.Nucleic Acids Res. 2000; 28: 27-30Crossref PubMed Scopus (17964) Google Scholar CHANDRAN_METASTASIS_TOP50_UP (ID M18970),37Chandran U.R. Ma C. Dhir R. Bisceglia M. Lyons-Weiler M. Liang W. Michalopoulos G. Becich M. Monzon F.A. Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.BMC Cancer. 2007; 7: 64Crossref PubMed Scopus (391) Google Scholar and WALLACE_PROSTATE_CANCER_RACE_UP (ID M10319).38Wallace T.A. Prueitt R.L. Yi M. Howe T.M. Gillespie J.W. Yfantis H.G. Stephens R.M. Caporaso N.E. Loffredo C.A. Ambs S. Tumor immunobiological differences in prostate cancer between African-American and European-American men.Cancer Res. 2008; 68: 927-936Crossref PubMed Scopus (381) Google Scholar The results shown are in part based on data generated by The Cancer Genome Atlas (TCGA) Research Network (http://cancergenome.nih.gov; last accessed May 2, 2018). TCGA prostate adenocarcinoma miRNA sequencing cou" @default.
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