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Mir-29A Is Repressed by MYC in Pancreatic Cancer and Its Restoration Drives Tumor-Suppressive Effects Via Downregulation of LOXL2 Shatovisha Dey1, Jason J

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Mir-29A Is Repressed by MYC in Pancreatic Cancer and Its Restoration Drives Tumor-Suppressive Effects Via Downregulation of LOXL2 Shatovisha Dey1, Jason J Published OnlineFirst October 29, 2019; DOI: 10.1158/1541-7786.MCR-19-0594 MOLECULAR CANCER RESEARCH | RNA BIOLOGY miR-29a Is Repressed by MYC in Pancreatic Cancer and Its Restoration Drives Tumor-Suppressive Effects via Downregulation of LOXL2 Shatovisha Dey1, Jason J. Kwon1, Sheng Liu1, Gabriel A. Hodge1, Solaema Taleb1, Teresa A. Zimmers2,3, Jun Wan1,2, and Janaiah Kota1,2 ABSTRACT ◥ Pancreatic ductal adenocarcinoma (PDAC) is an intractable Implications: This study unravels a novel functional role of miR-29a cancer with a dismal prognosis. miR-29a is commonly downregu- in PDAC pathogenesis and identifies an MYC–miR-29a–LOXL2 axis lated in PDAC; however, mechanisms for its loss and role still remain in regulation of the disease progression, implicating miR-29a as a unclear. Here, we show that in PDAC, repression of miR-29a is potential therapeutic target for PDAC. directly mediated by MYC via promoter activity. RNA sequencing analysis, integrated with miRNA target prediction, identified global Visual Overview: http://mcr.aacrjournals.org/content/molcanres/ miR-29a downstream targets in PDAC. Target enrichment coupled 18/2/311/F1.large.jpg. with gene ontology and survival correlation analyses identified the top five miR-29a–downregulated target genes (LOXL2, MYBL2, CLDN1, HGK,andNRAS) that are known to promote tumorigenic mechanisms. Functional validation confirmed that upregulation of miR-29a is sufficient to ablate translational expression of these five genes in PDAC. We show that the most promising target among the identified genes, LOXL2, is repressed by miR-29a via 30-untranslated region binding. Pancreatic tissues from a PDAC murine model and patient biopsies showed overall high LOXL2 expression with inverse correlations with miR-29a levels. Collectively, our data delineate an antitumorigenic, regulatory role of miR-29a and a novel MYC–miR- 29a–LOXL2 regulatory axis in PDAC pathogenesis, indicating the potential of the molecule in therapeutic opportunities. Introduction the knowledge is yet to yield effective targeted therapies. Further- Pancreatic ductal adenocarcinoma (PDAC) is one of the most more, there was no success with targeting Kras (9, 10) or finding deadly forms of human malignancies. Being the fourth most lethal potent Kras inhibitors (11). Thus, there is a crucial need for cancer in the United States, PDAC accounts for 7% of all estimated investigating the molecular mechanisms of PDAC to identify de cancer-related deaths (1). With an overall 5-year survival rate of novo targets for the disease aimed at developing effective thera- less than 5% worldwide (2), the trend for PDAC is projected to peutic strategies to prolong life expectancies of patients with worsen over the next decade, rendering PDAC the second-leading PDAC. cause of cancer-related deaths by 2030 (3). Because of lack of miRNAs play pivotal roles in regulating a broad array of biological efficient biomarkers, PDAC remains undetected till an advanced, processes related to cancer pathogenesis (12). Particularly, studies have metastatic stage when the cancer is aggressive and resistant to shown tumor-suppressor miRNAs to be repressed in a wide variety of current forms of therapeutic modalities (4). Therapeutic failure for cancer types, which in turn derepress proto-oncogenic factors pro- PDAC can be attributed to the unique heterogeneous, immune- moting cancer phenotypes (12). In our previous reports, we demon- suppressive tumor microenvironment, which interferes with drug strated the pathologic role of miR-29a in PDAC tumor–stromal efficacy and cytotoxic T-cell infiltration in the cells (4, 5). Over 90% biology (13, 14). We found miR-29a to remain downregulated in of PDAC cases exhibit driver oncogenic Kras mutations with pancreatic cancer cells (PCC) and associated fibroblasts (13, 14). initiation of precursor, pancreatic intraepithelial neoplasia (PanIN) However, the mechanisms of miR-29a downregulation and its down- lesions, which lead to aggressive metastatic PDAC (6). Although stream effectors in PDAC are still unclear. This study delineates mutational spectrum of PDAC has been well characterized (6–8), the upstream regulation of miR-29a in PDAC and characterizes global 1Department of Medical and Molecular Genetics, Indiana University School of Corresponding Author: Janaiah Kota, Indiana University School of Medicine, Medicine, Indianapolis, Indiana. 2The Melvin and Bren Simon Cancer Center, 975 West Walnut Street, IB 244C, Indianapolis, IN 46202-5251. Phone: 317-278- IUSM, Indianapolis, Indiana. 3Department of Surgery, Indiana University School 2105; Fax: 317-274-2293; E-mail: [email protected] of Medicine, Indianapolis, Indiana. Mol Cancer Res 2020;18:311–23 Note: Supplementary data for this article are available at Molecular Cancer doi: 10.1158/1541-7786.MCR-19-0594 Research Online (http://mcr.aacrjournals.org/). Ó2019 American Association for Cancer Research. AACRJournals.org | 311 Downloaded from mcr.aacrjournals.org on September 27, 2021. © 2020 American Association for Cancer Research. Published OnlineFirst October 29, 2019; DOI: 10.1158/1541-7786.MCR-19-0594 Dey et al. miR-29a targetome in the disease. Here, we reveal for the first time the a Leica DM5000B microscope. Quantification of percent MYC nuclear association of miR-29a–LOXL2 axis is regulation of PDAC pathogenesis. localization was performed using ImageJ software. Data were charted and presented as the average quantification of four replicates for each cell line. Materials and Methods Accession number Chromatin immunoprecipitation The RNA-sequencing (RNA-seq) data reported in this study are Chromatin immunoprecipitation (ChIP) experiments were carried available at the Gene Expression Omnibus database under the acces- out as described previously (15, 16) with a few modifications as shown sion number GSE128663. in Supplementary Materials and Methods. Experimental mice Transfection of cultured cell lines LSL.G12D/þ LSL.R172H/þ Kras ; p53 (KP) mice were generated and crossed Exponentially growing PCCs were transfected using Dharmafect1 LSL.G12D/þ R172H/þ with Pdx1-Cre mice to obtain the Kras ; p53 ; Pdx1-Cre Reagent (T-2001-01, Dharmacon) and with control (CN-001000-01) (KPC) mice used in this study. All animal protocols were reviewed and or miR-29a mimic (C-300504-07), or the following siRNAs from approved by the Indiana University Animal Care and Use Committee. Dharmacon: siCTRL (D-001810-10-05), siMYC (L-003282-02- Regulatory guidelines set by Guide for the Care and Use of Laboratory 0005), siSMAD4 (L-003902-00-0005), siGLI3 (L-011043-00-0005), Animals of the National Institute of Health were followed for all animal siMYBL2 (L-010444-00-0005), siLOXL2 (L-008020-01-0005), housing, use, and euthanasia procedures. siCLDN1 (L-017369-00-0005), siHGK (L-003971-00-0002), and siN- RAS (L-003919-00-0005), from Qiagen: miRNA inhibitor control Patient tissue procurement (339126) or LNA miR-29a inhibitor (339121), following the manu- This study was reviewed and approved by the Indiana University facturer's protocol. Total protein or RNA was isolated 48 hours after Institutional Review Board (IU IRB # 1312935090R004). Patient transfection for Western blot or qPCR analyses. tissues were obtained as described previously (13). RNA-seq and bioinformatics Cell culture Panc-1 and MIA PaCa-2 cells were transfected with control or miR- Normal human pancreatic epithelial cell lines HPNE (CRL-023, 29a (n ¼ 3/group) following the protocol described above. Total RNA ATCC) and HPDE (T0018001, AddexBio), and PCC lines Panc-1 was extracted 48 hours after transfection using the RNeasy Plus Mini (CRL-1469, ATCC) and MIA PaCa-2 (CRL-1420, ATCC) were cul- Kit (74134, Qiagen), and the purity was assessed using a Nanodrop tured in DMEM (11965092, Life Technologies) supplemented with 2000. Purified RNA quality was determined by a Bioanalyzer, then 10% FBS. AsPC-1 (CRL-1682, ATCC) and BxPC-3 (CRL-1687, used to prepare libraries, and sequenced (pair end read 150 cycles) ATCC) PCC lines were grown in RPMI1640 medium (11875-093, using an Illumina HiSeq 2000. RNA-seq quality was examined using Gibco) supplemented with 10% FBS. Cells were grown in a humidified the FastQC tool. Library obtained from each replicate consisted of 26 5% CO2 incubator at 37 C. Cell lines were authenticated by morpho- to 36 million short sequence reads that were remapped back to the logic inspection and Mycoplasma testing. Experiments were per- reference genome (hg38) using STAR v2.5 (17), which yielded overall formed with cells of passage of <10. average read map ratios of 93.6% and 90% for Panc-1 and MIA PaCa-2 cell lines. Uniquely mapped sequencing reads were assigned to genes RNA extraction based on Gencode 25 using featureCounts (v1.6.2; ref. 18). After Total RNA was extracted from cultured cells or frozen pancreatic filtering out low expressed genes with read count per million < 0.5 tissues using TRIzol Reagent (Invitrogen). The concentration and in greater than two samples, gene expression profiles were normalized purity of the extracted RNAs were measured using a NanoDrop 2000 using trimmed mean of M values method, and differential expression Spectrophotometer (Thermo Fisher Scientific) and stored at À80C analysis was performed using edgeR (v3.20.8; refs. 19, 20). The for future use. differentially expressed genes (DEG) were determined by cutoff P < 0.05 after FDR adjustment and amplitude of fold change (FC) of gene Quantitative real-time PCR expression greater than 2 linear FC. RNA was reverse transcribed to generate cDNA using High- TargetScan (v7.1; ref. 21) was adopted to predict conserved miR-29a Capacity cDNA Reverse Transcription Kit (4368814, Thermo Fisher target genes. Hypergeometric model was used to calculate the overlap Scientific) with random primers or custom primer pool for miRNA between DEGs and miR-29a–predicted targets. Functional enrich- (Applied Biosystems). miRNA and LOXL2 expressions were measured ment analyses on the DEGs were performed using DAVID (v6.8) using TaqMan Assays. Other gene expressions were measured using database (https://david.ncifcrf.gov/). The miR-29a target gene levels in SYBR Green assays with primers shown in Supplementary Table S1.
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