PRKCQ Promotes Oncogenic Growth and Anoikis Resistance of a Subset
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Gene Symbol Gene Description ACVR1B Activin a Receptor, Type IB
Table S1. Kinase clones included in human kinase cDNA library for yeast two-hybrid screening Gene Symbol Gene Description ACVR1B activin A receptor, type IB ADCK2 aarF domain containing kinase 2 ADCK4 aarF domain containing kinase 4 AGK multiple substrate lipid kinase;MULK AK1 adenylate kinase 1 AK3 adenylate kinase 3 like 1 AK3L1 adenylate kinase 3 ALDH18A1 aldehyde dehydrogenase 18 family, member A1;ALDH18A1 ALK anaplastic lymphoma kinase (Ki-1) ALPK1 alpha-kinase 1 ALPK2 alpha-kinase 2 AMHR2 anti-Mullerian hormone receptor, type II ARAF v-raf murine sarcoma 3611 viral oncogene homolog 1 ARSG arylsulfatase G;ARSG AURKB aurora kinase B AURKC aurora kinase C BCKDK branched chain alpha-ketoacid dehydrogenase kinase BMPR1A bone morphogenetic protein receptor, type IA BMPR2 bone morphogenetic protein receptor, type II (serine/threonine kinase) BRAF v-raf murine sarcoma viral oncogene homolog B1 BRD3 bromodomain containing 3 BRD4 bromodomain containing 4 BTK Bruton agammaglobulinemia tyrosine kinase BUB1 BUB1 budding uninhibited by benzimidazoles 1 homolog (yeast) BUB1B BUB1 budding uninhibited by benzimidazoles 1 homolog beta (yeast) C9orf98 chromosome 9 open reading frame 98;C9orf98 CABC1 chaperone, ABC1 activity of bc1 complex like (S. pombe) CALM1 calmodulin 1 (phosphorylase kinase, delta) CALM2 calmodulin 2 (phosphorylase kinase, delta) CALM3 calmodulin 3 (phosphorylase kinase, delta) CAMK1 calcium/calmodulin-dependent protein kinase I CAMK2A calcium/calmodulin-dependent protein kinase (CaM kinase) II alpha CAMK2B calcium/calmodulin-dependent -
The Drug Sensitivity and Resistance Testing (DSRT) Approach
A phenotypic screening and machine learning platform eciently identifies triple negative breast cancer-selective and readily druggable targets Prson Gautam 1 Alok Jaiswal 1 Tero Aittokallio 1, 2 Hassan Al Ali 3 Krister Wennerberg 1,4 Identifying eective oncogenic targets is challenged by the complexity of genetic alterations in 1Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Finland cancer and their poorly understood relation to cell function and survival. There is a need for meth- Current kinome coverage of kinase inhibitors in TNBC exhibit diverse kinase dependencies MFM-223 is selectively addicted to FGFR2 2Department of Mathematics and Statistics, University of Turku, Finland 3The Miami Project to Cure Paralysis, Peggy and Harold Katz Family Drug Discovery Center, A A Sylvester Comprehensive Cancer Center, and Department of Neurological Surgery and Medicine ods that rapidly and accurately identify “pharmacologically eective” targets without the require- clinical evaluation TN Kinases MFM-223 CAL-120 MDA-MB-231 TNBC TNBC TNBC TNBC TNBC TNBC HER2+ 100 University of Miami Miller School of Medicine, Miami, FL 33136, USA. non- HER2+ FGFR1 0.97 0.00 0.00 MFM-223 BL1 BL2 M MSL IM LAR ER+, PR+ 50 ment for priori knowledge of complex signaling networks. We developed an approach that uses ma- cancerous FGFR2 56.46 0.00 0.00 CAL-120 25 4 MDA-MB-231 Biotech Research & Innovation Centre (BRIC) and Novo Nordisk Foundation Center HCC1937 CAL-85-1 CAL-120 MDA-MB-231 DU4475 CAL-148 MCF-10A SK-BR-3 BT-474 FGFR3 25.10 0.00 0.00 0 chine learning to relate results from unbiased phenotypic screening of kinase inhibitors to their bio- for Stem Cell Biology (DanStem), University of Copenhagen, Denmark HCC1599 HDQ-P1 BT-549 MDA-MB-436 MFM-223 FGFR4 0.00 0.00 0.00 MAXIS*Bk Clinical status MDA-MB-468 CAL-51 Hs578T MDA-MB-453 score chemical activity data. -
AGC Kinases in Mtor Signaling, in Mike Hall and Fuyuhiko Tamanoi: the Enzymes, Vol
Provided for non-commercial research and educational use only. Not for reproduction, distribution or commercial use. This chapter was originally published in the book, The Enzymes, Vol .27, published by Elsevier, and the attached copy is provided by Elsevier for the author's benefit and for the benefit of the author's institution, for non-commercial research and educational use including without limitation use in instruction at your institution, sending it to specific colleagues who know you, and providing a copy to your institution’s administrator. All other uses, reproduction and distribution, including without limitation commercial reprints, selling or licensing copies or access, or posting on open internet sites, your personal or institution’s website or repository, are prohibited. For exceptions, permission may be sought for such use through Elsevier's permissions site at: http://www.elsevier.com/locate/permissionusematerial From: ESTELA JACINTO, AGC Kinases in mTOR Signaling, In Mike Hall and Fuyuhiko Tamanoi: The Enzymes, Vol. 27, Burlington: Academic Press, 2010, pp.101-128. ISBN: 978-0-12-381539-2, © Copyright 2010 Elsevier Inc, Academic Press. Author's personal copy 7 AGC Kinases in mTOR Signaling ESTELA JACINTO Department of Physiology and Biophysics UMDNJ-Robert Wood Johnson Medical School, Piscataway New Jersey, USA I. Abstract The mammalian target of rapamycin (mTOR), a protein kinase with homology to lipid kinases, orchestrates cellular responses to growth and stress signals. Various extracellular and intracellular inputs to mTOR are known. mTOR processes these inputs as part of two mTOR protein com- plexes, mTORC1 or mTORC2. Surprisingly, despite the many cellular functions that are linked to mTOR, there are very few direct mTOR substrates identified to date. -
Profiling Data
Compound Name DiscoveRx Gene Symbol Entrez Gene Percent Compound Symbol Control Concentration (nM) BSJ-03-123 AAK1 AAK1 94 1000 BSJ-03-123 ABL1(E255K)-phosphorylated ABL1 79 1000 BSJ-03-123 ABL1(F317I)-nonphosphorylated ABL1 89 1000 BSJ-03-123 ABL1(F317I)-phosphorylated ABL1 98 1000 BSJ-03-123 ABL1(F317L)-nonphosphorylated ABL1 86 1000 BSJ-03-123 ABL1(F317L)-phosphorylated ABL1 89 1000 BSJ-03-123 ABL1(H396P)-nonphosphorylated ABL1 76 1000 BSJ-03-123 ABL1(H396P)-phosphorylated ABL1 90 1000 BSJ-03-123 ABL1(M351T)-phosphorylated ABL1 100 1000 BSJ-03-123 ABL1(Q252H)-nonphosphorylated ABL1 56 1000 BSJ-03-123 ABL1(Q252H)-phosphorylated ABL1 97 1000 BSJ-03-123 ABL1(T315I)-nonphosphorylated ABL1 100 1000 BSJ-03-123 ABL1(T315I)-phosphorylated ABL1 85 1000 BSJ-03-123 ABL1(Y253F)-phosphorylated ABL1 100 1000 BSJ-03-123 ABL1-nonphosphorylated ABL1 60 1000 BSJ-03-123 ABL1-phosphorylated ABL1 79 1000 BSJ-03-123 ABL2 ABL2 89 1000 BSJ-03-123 ACVR1 ACVR1 100 1000 BSJ-03-123 ACVR1B ACVR1B 95 1000 BSJ-03-123 ACVR2A ACVR2A 100 1000 BSJ-03-123 ACVR2B ACVR2B 96 1000 BSJ-03-123 ACVRL1 ACVRL1 84 1000 BSJ-03-123 ADCK3 CABC1 90 1000 BSJ-03-123 ADCK4 ADCK4 91 1000 BSJ-03-123 AKT1 AKT1 100 1000 BSJ-03-123 AKT2 AKT2 98 1000 BSJ-03-123 AKT3 AKT3 100 1000 BSJ-03-123 ALK ALK 100 1000 BSJ-03-123 ALK(C1156Y) ALK 78 1000 BSJ-03-123 ALK(L1196M) ALK 100 1000 BSJ-03-123 AMPK-alpha1 PRKAA1 93 1000 BSJ-03-123 AMPK-alpha2 PRKAA2 100 1000 BSJ-03-123 ANKK1 ANKK1 89 1000 BSJ-03-123 ARK5 NUAK1 98 1000 BSJ-03-123 ASK1 MAP3K5 100 1000 BSJ-03-123 ASK2 MAP3K6 92 1000 BSJ-03-123 AURKA -
Profiling Data
Compound Name DiscoveRx Gene Symbol Entrez Gene Percent Compound Symbol Control Concentration (nM) JNK-IN-8 AAK1 AAK1 69 1000 JNK-IN-8 ABL1(E255K)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317I)-nonphosphorylated ABL1 87 1000 JNK-IN-8 ABL1(F317I)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317L)-nonphosphorylated ABL1 65 1000 JNK-IN-8 ABL1(F317L)-phosphorylated ABL1 61 1000 JNK-IN-8 ABL1(H396P)-nonphosphorylated ABL1 42 1000 JNK-IN-8 ABL1(H396P)-phosphorylated ABL1 60 1000 JNK-IN-8 ABL1(M351T)-phosphorylated ABL1 81 1000 JNK-IN-8 ABL1(Q252H)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(Q252H)-phosphorylated ABL1 56 1000 JNK-IN-8 ABL1(T315I)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(T315I)-phosphorylated ABL1 92 1000 JNK-IN-8 ABL1(Y253F)-phosphorylated ABL1 71 1000 JNK-IN-8 ABL1-nonphosphorylated ABL1 97 1000 JNK-IN-8 ABL1-phosphorylated ABL1 100 1000 JNK-IN-8 ABL2 ABL2 97 1000 JNK-IN-8 ACVR1 ACVR1 100 1000 JNK-IN-8 ACVR1B ACVR1B 88 1000 JNK-IN-8 ACVR2A ACVR2A 100 1000 JNK-IN-8 ACVR2B ACVR2B 100 1000 JNK-IN-8 ACVRL1 ACVRL1 96 1000 JNK-IN-8 ADCK3 CABC1 100 1000 JNK-IN-8 ADCK4 ADCK4 93 1000 JNK-IN-8 AKT1 AKT1 100 1000 JNK-IN-8 AKT2 AKT2 100 1000 JNK-IN-8 AKT3 AKT3 100 1000 JNK-IN-8 ALK ALK 85 1000 JNK-IN-8 AMPK-alpha1 PRKAA1 100 1000 JNK-IN-8 AMPK-alpha2 PRKAA2 84 1000 JNK-IN-8 ANKK1 ANKK1 75 1000 JNK-IN-8 ARK5 NUAK1 100 1000 JNK-IN-8 ASK1 MAP3K5 100 1000 JNK-IN-8 ASK2 MAP3K6 93 1000 JNK-IN-8 AURKA AURKA 100 1000 JNK-IN-8 AURKA AURKA 84 1000 JNK-IN-8 AURKB AURKB 83 1000 JNK-IN-8 AURKB AURKB 96 1000 JNK-IN-8 AURKC AURKC 95 1000 JNK-IN-8 -
Key Genes Regulating Skeletal Muscle Development and Growth in Farm Animals
animals Review Key Genes Regulating Skeletal Muscle Development and Growth in Farm Animals Mohammadreza Mohammadabadi 1 , Farhad Bordbar 1,* , Just Jensen 2 , Min Du 3 and Wei Guo 4 1 Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman 77951, Iran; [email protected] 2 Center for Quantitative Genetics and Genomics, Aarhus University, 8210 Aarhus, Denmark; [email protected] 3 Washington Center for Muscle Biology, Department of Animal Sciences, Washington State University, Pullman, WA 99163, USA; [email protected] 4 Muscle Biology and Animal Biologics, Animal and Dairy Science, University of Wisconsin-Madison, Madison, WI 53558, USA; [email protected] * Correspondence: [email protected] Simple Summary: Skeletal muscle mass is an important economic trait, and muscle development and growth is a crucial factor to supply enough meat for human consumption. Thus, understanding (candidate) genes regulating skeletal muscle development is crucial for understanding molecular genetic regulation of muscle growth and can be benefit the meat industry toward the goal of in- creasing meat yields. During the past years, significant progress has been made for understanding these mechanisms, and thus, we decided to write a comprehensive review covering regulators and (candidate) genes crucial for muscle development and growth in farm animals. Detection of these genes and factors increases our understanding of muscle growth and development and is a great help for breeders to satisfy demands for meat production on a global scale. Citation: Mohammadabadi, M.; Abstract: Farm-animal species play crucial roles in satisfying demands for meat on a global scale, Bordbar, F.; Jensen, J.; Du, M.; Guo, W. -
Endometrial Gene Expression in the Early Luteal Phase Is Impacted By
Human Reproduction, Vol.27, No.11 pp. 3259–3272, 2012 Advanced Access publication on August 28, 2012 doi:10.1093/humrep/des279 ORIGINAL ARTICLE Reproductive biology Endometrial gene expression in the early luteal phase is impacted by mode of triggering final oocyte maturation in recFSH stimulated and GnRH antagonist co-treated IVF cycles P. Humaidan1,*, I. Van Vaerenbergh2, C. Bourgain2, B. Alsbjerg3, Downloaded from C. Blockeel4, F. Schuit5, L. Van Lommel5, P. Devroey4, and H. Fatemi4 1The Fertility Clinic, Department D, Odense University Hospital, OHU, Entrance 55, Odense C 5000, Denmark 2Reproductive Immunology and Implantation Unit, Dutch-speaking Free University of Brussels, Brussels, Belgium 3The Fertility Clinic, Skive Regional Hospital, Skive, Denmark 4Centre for Reproductive Medicine, Dutch-speaking Free University of Brussels, Brussels, Belgium 5Gene Expression Unit, KU Leuven, Leuven, Belgium http://humrep.oxfordjournals.org/ *Correspondence address. Tel: +45-20-34-26-87; E-mail: [email protected] Submitted on March 9, 2012; resubmitted on June 3, 2012; accepted on June 22, 2012 study question: Do differences in endometrial gene expression exist after ovarian stimulation with four different regimens of triggering final oocyte maturation and luteal phase support in the same patient? summary answer: Significant differences in the expression of genes involved in receptivity and early implantation were seen between by greta verheyen on June 5, 2013 the four protocols. what is known already: GnRH agonist triggering -
Distinct Regulation of Cardiac Fibroblast Proliferation and Transdifferentiation by Classical and Novel Protein Kinase C Isoform
Molecular Pharmacology Fast Forward. Published on November 25, 2020 as DOI: 10.1124/molpharm.120.000094 This article has not been copyedited and formatted. The final version may differ from this version. Distinct regulation of cardiac fibroblast proliferation and transdifferentiation by classical and novel protein kinase C isoforms: possible implications for new antifibrotic therapies S. Tuuli Karhu, Heikki Ruskoaho, Virpi Talman* Affiliations Downloaded from STK, HR, and VT: Drug Research Program and Division of Pharmacology and Pharmacotherapy, Faculty of Pharmacy, University of Helsinki, Finland molpharm.aspetjournals.org *Corresponding author at ASPET Journals on September 30, 2021 1 Molecular Pharmacology Fast Forward. Published on November 25, 2020 as DOI: 10.1124/molpharm.120.000094 This article has not been copyedited and formatted. The final version may differ from this version. Running title: PKC agonists inhibit cardiac fibroblast activation Corresponding author: Virpi Talman Division of Pharmacology and Pharmacotherapy Faculty of Pharmacy University of Helsinki P.O. Box 56 (Viikinkaari 5E) FI-00014 Helsinki, FINLAND Downloaded from Tel: +358504480768 Email: [email protected] molpharm.aspetjournals.org Number of text pages: 35 Number of tables: 0 Number of figures: 4 at ASPET Journals on September 30, 2021 Number of references: 55 Number of words in the Abstract: 249 Number of words in the Introduction: 728 Number of words in the Discussion: 1459 Abbreviations: α-SMA, α-smooth muscle actin; aPKC, atypical protein kinase C isoform; BrdU, 5-bromo-2’-deoxyuridine; CF, cardiac fibroblast; cPKC, classical protein kinase C isoform; DDR2, discoidin domain receptor 2; ECM, extracellular matrix; ERK, extracellular signal-regulated kinase; HCA, high-content analysis; LDH, lactate dehydrogenase; MTT, 3- (4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide; nPKC, novel protein kinase C isoform; PKC, protein kinase C 2 Molecular Pharmacology Fast Forward. -
Protein Kinase C As a Paradigm Alexandra C
Biochem. J. (2003) 370, 361–371 (Printed in Great Britain) 361 REVIEW ARTICLE Regulation of the ABC kinases by phosphorylation: protein kinase C as a paradigm Alexandra C. NEWTON1 Department of Pharmacology, University of California at San Diego, La Jolla, CA 92093-0640, U.S.A. Phosphorylation plays a central role in regulating the activation down-regulation of PKC as a paradigm for how these sites and signalling lifetime of protein kinases A, B (also known as control the function of the ABC kinases. Akt) and C. These kinases share three conserved phosphorylation motifs: the activation loop segment, the turn motif and the Key words: phosphoinositide 3-kinase, phosphoinositide-depen- hydrophobic motif. This review focuses on how phosphorylation dent kinase-1 (PDK-1), phosphorylation motif, protein kinase A at each of these sites regulates the maturation, signalling and (PKA), protein kinase B (PKB)\Akt, protein kinase C (PKC). INTRODUCTION by phosphorylation as a paradigm for control of ABC kinase function by phosphorylation. Almost half a century ago Krebs, Graves and Fischer reported b that the first discovered protein kinase, phosphorylase kinase, ARCHITECTURE OF ABC KINASES was, itself, activated by phosphorylation [1]. Two decades later, Fischer and colleagues showed that the kinase that phosphory- Protein kinases A, B\Akt and C have in common a conserved lates phosphorylase kinase, later named protein kinase A (PKA), kinase core whose function is regulated allosterically by a was also phosphorylated [2]. Reversible control by phosphory- corresponding regulatory moiety (Figure 1). In the case of PKA, lation\dephosphorylation is now firmly established as a fun- the regulatory moiety is a separate polypeptide, whereas the damental mechanism for regulating the function of most of the regulatory determinants are on the same polypeptide as the 500 or so members of the mammalian protein kinase superfamily. -
Protein Kinase C As a Therapeutic Target in Non-Small Cell Lung Cancer
International Journal of Molecular Sciences Review Protein Kinase C as a Therapeutic Target in Non-Small Cell Lung Cancer Mohammad Mojtaba Sadeghi 1,2, Mohamed F. Salama 2,3,4 and Yusuf A. Hannun 1,2,3,* 1 Department of Biochemistry, Molecular and Cellular Biology, Stony Brook University, Stony Brook, NY 11794, USA; [email protected] 2 Stony Brook Cancer Center, Stony Brook University Hospital, Stony Brook, NY 11794, USA; [email protected] 3 Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA 4 Department of Biochemistry, Faculty of Veterinary Medicine, Mansoura University, Mansoura 35516, Dakahlia Governorate, Egypt * Correspondence: [email protected] Abstract: Driver-directed therapeutics have revolutionized cancer treatment, presenting similar or better efficacy compared to traditional chemotherapy and substantially improving quality of life. Despite significant advances, targeted therapy is greatly limited by resistance acquisition, which emerges in nearly all patients receiving treatment. As a result, identifying the molecular modulators of resistance is of great interest. Recent work has implicated protein kinase C (PKC) isozymes as mediators of drug resistance in non-small cell lung cancer (NSCLC). Importantly, previous findings on PKC have implicated this family of enzymes in both tumor-promotive and tumor-suppressive biology in various tissues. Here, we review the biological role of PKC isozymes in NSCLC through extensive analysis of cell-line-based studies to better understand the rationale for PKC inhibition. Citation: Sadeghi, M.M.; Salama, PKC isoforms α, ", η, ι, ζ upregulation has been reported in lung cancer, and overexpression correlates M.F.; Hannun, Y.A. Protein Kinase C with worse prognosis in NSCLC patients. -
Expression Profile Analysis of Two Antisense Lncrnas to Improve Prognosis Prediction of Colorectal Adenocarcinoma
Shademan et al. Cancer Cell Int (2019) 19:278 https://doi.org/10.1186/s12935-019-1000-1 Cancer Cell International PRIMARY RESEARCH Open Access Expression profle analysis of two antisense lncRNAs to improve prognosis prediction of colorectal adenocarcinoma Milad Shademan1†, Azam Naseri Salanghuch1†, Khadijeh Zare1, Morteza Zahedi1, Mohammad Ali Foroughi2, Kambiz Akhavan Rezayat3,5, Hooman Mosannen Mozafari3,5, Kamran Ghafarzadegan6, Ladan Goshayeshi3,4* and Hesam Dehghani1,2,7* Abstract Background: Long noncoding RNAs (lncRNAs) are involved in diferent pathogenesis pathways including cancer pathogenesis. The adenoma-carcinoma pathway in colorectal cancer may involve the aberrant and variable gene expression of regulatory RNAs. This study was conducted to analyse the expression and prognosis prediction abil- ity of two natural antisense transcripts, protein kinase C theta antisense RNA 1 (PRKCQ-AS1), and special AT-rich sequence binding protein 1 antisense RNA 1 (SATB1-AS1) in colorectal low-grade adenoma, advanced adenoma, and adenocarcinomas. Methods: In this study, from two RNA-seq analyses of CCAT1-ko cells and colorectal carcinoma biopsies having diminished and increased levels of CCAT1 transcription, respectively, we nominated two antisense lncRNAs of PRKCQ- AS1 and SATB1-AS1. Samples from colorectal low-grade adenomas, advanced adenomas, adenocarcinomas, and adjacent tissue were subjected to RT-qPCR to determine the expression of PRKCQ-AS1, SATB1-AS1 along with colon cancer-associated transcript 1 (CCAT1) and cMYC. In addition, we used diferent bioinformatics analyses and webserv- ers (including GEPIA 2, TCGA, and CancerMine) to elucidate the prognosis prediction value, the expression correlation of sense–antisense pair of genes, and the expression profle of these antisense transcripts at the presence or absence of mutations in the driver genes, or the corresponding sense genes. -
HHS Public Access Author Manuscript
HHS Public Access Author manuscript Author Manuscript Author ManuscriptBreast Cancer Author Manuscript Res Treat Author Manuscript . Author manuscript; available in PMC 2016 June 01. Published in final edited form as: Breast Cancer Res Treat. 2015 June ; 151(2): 453–463. doi:10.1007/s10549-015-3401-8. Body mass index associated with genome-wide methylation in breast tissue Brionna Y. Hair1, Zongli Xu2, Erin L. Kirk1, Sophia Harlid2, Rupninder Sandhu3, Whitney R. Robinson1,3, Michael C. Wu4, Andrew F. Olshan1, Kathleen Conway1,3, Jack A. Taylor2, and Melissa A. Troester1 1 Department of Epidemiology, University of North Carolina at Chapel Hill, CB #7435, 2101 McGavran-Greenberg Hall, Chapel Hill, NC 27599-7435, USA 2 Epidemiology Branch, and Epigenomics and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences (NIH), Research Triangle Park, NC, USA 3 Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA 4 Fred Hutchinson Cancer Research Center, Seattle, WA, USA Abstract Gene expression studies indicate that body mass index (BMI) is associated with molecular pathways involved in inflammation, insulin-like growth factor activation, and other carcinogenic processes in breast tissue. The goal of this study was to determine whether BMI is associated with gene methylation in breast tissue and to identify pathways that are commonly methylated in association with high BMI. Epigenome-wide methylation profiles were determined using the Illumina HumanMethylation450 BeadChip array in the non-diseased breast tissue of 81 women undergoing breast surgery between 2009 and 2013 at the University of North Carolina Hospitals. Multivariable, robust linear regression was performed to identify methylation sites associated with BMI at a false discovery rate q value <0.05.