Recent Work & Current Methods in Endocrine microRNA Research

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• Brief review of microRNA basics: history, biogenesis, function • Recent developments of microRNA research in the field of endocrinology • Current methods for microRNA discovery and profiling • Case studies and application examples

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Endocrine microRNA Webinar Recent Work & Current Methods In Endocrinology microRNA Research Christoph Eicken , PhD Head of Technical Services – Microarrays 2012-09-11

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Agenda Recent Studies Current methods Q & A Case Studies miRNA Intro

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Transcriptomics microRNA Profiling Microarray Services microRNA Discovery Sequencing Services Seq- Array SM Method Proteomics Phosphopeptide Binding Microarray Service Protein- Protein Interaction Microarray Service Kinase Profiling Microarray Service 5 µ Paraflo ® Microfluidic Technology High Density – On Chip Parallel Synthesis Customizable – DNA, RNA, Peptides, and Analogs Quality Data – Microfluidics / Synthesis Chemistry

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A ll miRNAs are small non-coding RNAs, usually consisting of ∼20–22 nucleotides for animals and ∼20–24 nt for plants. All miRNA precursors have a well-predicted stem loop hairpin structure, and this fold-back hairpin structure has a low free energy Many miRNAs are evolutionarily conserved, some from worm to human in animals, or from ferns to core eudicots or monocots in plants Bind to complementary mRNA molecules and act as negative regulators of translation High copy number Expression is tissue (and developmental stage) specific microRNAs - What W e Know

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microRNAs - What W e Know Currently - 25,141 mature miRNAs across 193 plant, animal, and virus species ( miRBase 19 , Aug. 2012). Mechanism is far reaching and complex – each miRNA may control many genes and it is estimated that miRNAs regulate expression of up to 1/3 of all human genes. Operate by one of two hypothesized mechanisms : – Complete pairing mRNA is degraded - predominant in plants – Imperfect pairing translation is repressed but mRNA remains intact - predominant in animals

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1993 – Lin-4 was shown to encode two small RNA molecules (not protein) Small RNAs control developmental timing in C. elegans through negative regulation of lin-14 gene. Lee RC et al. 1993 The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75(5):843-54. [ article ] 1998 – RNAi is observed for the first time – leads to Nobel Prize (2006) Fire A, Mello CC et al. 1998 Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 1998; 391:806-811. [ article ] Challenge to the Central Dogma of Biology DNA > transcription > RNA > translation > protein 2000 – Let-7 was identified in humans and Drosophila . (Reinhart et al., Slack et al.) 2001 – Bartel , Tuschl , Ambros - Discover large class of small regulatory RNAs, name them microRNA (miRNA) Lau NC et al. 2001 An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans . Science 294(5543):858-62 . [ abstract ] Lagos-Quintana M et al. 2001 Identification of novel genes coding for small expressed RNAs . Science 294(5543):853-8 . [ abstract ] Lee RC et al. 2001 An extensive class of small RNAs in Caenorhabditis elegans . Science 294(5543):862-4. [ abstract ] 2002 – Identification of Drosha reveals complete microRNA biogenesis pathway pri-miRNAs > Drosha > pre- miRNAs (~70nt) > Dicer > mature miRNAs (~22nt) Lee Y et al. (2002) The nuclear RNase III Drosha initiates microRNA processing. Nature 425(6956):415-9. [ abstract ] Milestones

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2004 – Microarrays are used to profile miRNA expression Several groups develop or modify existing gene expression microarrays for profiling miRNAs Babak et al. 2004 [ article ], Barad et al. 2004 [ article ], Liu et al. 2004 [ article ], Nelson et al. [ abstract ], 2004, Thomson et al. 2004 [ article ]. 2005 – Next-Gen Sequencing is used for small RNA discovery and analysis Green Lab - uses Solexa (now Illumina) sequencing to identify novel small RNAs in Arabidopsis plants Lu C et al. 2005 Elucidation of the small RNA component of the transcriptome. Science, 309: 1567–1569. [ abstract ] 2006 – miRBase goes online at Sanger Institute Depository for experimentally verified microRNAs: http://www.mirbase.org/ Griffiths-Jones S et al. 2006 miRBase: microRNA sequences, targets and gene nomenclature. NAR 34(Database Issue):D140-D144. [ article ] 2008 – Circulating miRNAs detected in body fluids miRNA signatures in serum and plasma provide cancer diagnosis / prognosis Serum - Chen X et al.(2008) Characterization of microRNAs in serum: A novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res 18:997–1006. [ article ] Plasma - Mitchell PS et al.(2008) Circulating microRNAs as stable blood-based markers for cancer detection. PNAS USA 105:10513–10518. [ article ] Milestones

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2003 - A role for miRNAs in energy metabolism is discovered Xu P et al. 2003 The Drosophila microRNA Mir-14 suppresses cell death and is required for normal fat metabolism. Curr 13: 790–795. [ article ] 2004 – miRNAs are shown to regulate endocrine functions: adipocyte differentiation, insulin secretion, and B-cell development Esau et al. 2004 MicroRNA-14 regulates adipocyte differentiation. Journal of Biological Chemistry 279:52361–52365. [ article ] Poy MN et al. 2004 A pancreatic islet-specific microRNA regulates insulin secretion. Nature 432(7014):226-30. [ abstract ] Chen CZ, Li L, Lodish HF, Bartel DP. 2004 MicroRNAs modulate hematopoietic lineage differentiation. Science 303:83– 6. [ abstract ] 2007 - miRNAs roles identified in tissues in which diabetes complications occur He A et al. 2007 Overexpression of micro ribonucleic acid 29, highly up-regulated in diabetic rats, leads to insulin resistance in 3T3-L1 adipocytes . Mol Endocrinol 21(11):2785-94. [ abstract ] Xiao J et al. 2007 MicroRNA miR-133 represses HERG K+ channel expression contributing to QT prolongation in diabetic hearts. J Biol Chem 282(17):12363-7. [ abstract ] 2008 - miRNA linked with hormone-dependent cancers Adams BD et al. 2007 The micro-ribonucleic acid (miRNA) miR-206 targets the human estrogen receptor-alpha ( ERalpha ) and represses ERalpha messenger RNA and protein expression in breast cancer cell lines. Mol Endocrinol 21(5):1132-47. [ article ] Lin SL et al. 2008 Loss of mir-146a function in hormone-refractory prostate cancer. RNA 14(3), 417-24. [ article ] Milestones - Endocrinology

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pri-miRNA = primary microRNA transcript pre- miRNA = precursor microRNA miRNA * = antisense microRNA (now -3p or -5p) miRISC = microRNA-induced silencing complex For latest information regarding miRNA nomenclature see the miRBase.org blog . miRNA Processing

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miRNA Biogenesis Pathway (A) Animal and (B) plant miRNA biogenesis. Mature miRNAs are indicated in red and miRNA* strands are in blue. Du T, Zamore PD. 2005 microPrimer : the Biogenesis and Function of microRNA. Development 132: 4645-4652. [ article ]

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miRNAs in miRBase 21,264 miRBase Entries - 193 plant, animal, and virus species miRBase: microRNA sequences, targets and gene nomenclature. Griffiths-Jones S et al. NAR 2006 34(Database Issue): D140-D144 [ article ]

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miRNAs in PubMed

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Latest from the Funding Agencies NIH To Fund Projects to ID miRNA Cancer Markers, Study Role of ncRNAs in HIV-Associated Disorders Last month NIH announced that it is seeking research grant applications for projects related to the identification of microRNAs and other non-coding RNAs as biomarkers in the early detection of cancer . The funding agency is specifically encouraging research projects to assess the utility of stable miRNAs and ncRNAs to predict progression to cancer, it said. “Building on both basic and biomarker research on microRNAs, this [research opportunity] will further promote research on all classes of ncRNAs and support the translation of stable miRNAs into cancer screening or diagnostic tests .”

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Why Study miRNAs in Endocrinology? There is an intricate reciprocal relationship between these two important regulatory systems. Many miRNAs regulate hormones and many miRNAs are in turn regulated by hormones. miRNAs have been shown to target many genes important for proper endocrine function and metabolism. Dysregulation of miRNAs can contribute to endocrine related diseases: Hormone-dependent Cancers, Obesity, Diabetes, Hyperglycemia, Lipodystrophy

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miRNAs in Endocrinology: Clinical Potential Molecular Diagnostics / Biomarkers – Identification of specific miRNAs or miRNA expression based signatures that can act as biomarkers for various diseases/pathologies. Biomarkers in body fluids: plasma, exosomes, & HDL particles Make accurate and detailed clinical diagnosis Potential to determine prognosis and predict treatment efficacy Monitor and assess the molecular effects of environmental and other toxicants (ex. endocrine disrupting compounds) Rosetta Genomics' miRview Lung Assay: Assay Shown to Accurately Differentiate Between the Four Main Types of Lung Cancer

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Drug Discovery / Therapeutics – Identification of miRNAs that play essential roles in disease to act as drugs or possible therapeutic targets. miRNAs as endocrine regulating drugs miRNAs as drug targets Study of miRNAs to understand response to infections, stress, other stimuli miRNAs in Endocrinology: Clinical Potential

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Rottiers V, Näär AM. (2012) MicroRNAs in metabolism and metabolic disorders. Nat Rev Mol Cell Biol13(4):239-50. [ abstract ] 2012 Review: MicroRNAs in metabolism and metabolic disorders miRNAs are key regulators of cholesterol and lipid homeostasis. miRNAs regulate insulin signaling and control of glucose homeostasis. miRNAs are linked to metabolic dysregulation in adipogenesis and obesity. Dysregulation of miRNA expression may contribute to metabolic syndrome. Circulating miRNAs have recently been identified in the blood, including as part of high-density lipoprotein. The link of abnormal miRNA expression to metabolic disorders has highlighted the therapeutic potential of antisense targeting of specific miRNAs. MicroRNAs are now known to play an essential part in regulation of metabolic homeostasis

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20 2012 Review: MicroRNAs in metabolism and metabolic disorders miRNA Target tissue(s) Function Target genes * Refs miR-103 and miR-107 Adipose, liver Insulin and glucose homeostasis, adipogenesis CAV1, DICER 81 , 82 , 85 miR-122 Liver Hepatic lipid metabolism SLC7A1 (also known as CAT1), ADAM17 20 , 139 , 140 miR-124a Pancreas Pancreatic islet development FOXA2, RAB27A 66 , 67 miR-143 Adipose, liver, pancreas Adipocyte differentiation, insulin resistance ERK5 (also known as BMK1 or MAPK7), OSBPL8 (also known as ORP8) 77 , 80 , 94 miR-223 Muscle Glucose uptake, insulin resistance SLC2A4 (also known as GLUT4) 75 miR-27a Adipose Adipogenesis (PPARG, CEBPA) ‡ 141 , 142 miR-29 Muscle, adipose, liver Glucose transport INSIG1, CAV2, SLC16A1 (also known as MCT1), PIK3R1 70 , 71 , 73 miR-33a and miR-33b Liver, macrophage Cholesterol, lipid and energy homeostasis ABCA1, NPC1, CPT1A, HADHB, CROT, IRS2, SIRT6, PRKAA1 (also known as AMPKA1) 31 , 32 , 33 , 34 , 35 , 36 , 39 miR-335 Pancreas, liver, adipose Insulin production, fatty acid and triglyceride biosynthesis STXBP1 76 , 79 miR-34a Liver, pancreas Lipid metabolism, B cell exocytosis SIRT1, VAMP2, ACSL1 88 , 113 , 143 miR-375 Pancreas Insulin secretion, pancreatic islet development MTPN, USP1, JAK2, ADIPOR2, PDPK1 62 , 63 , 64 miR-378 and miR-378 * Adipose Adipocyte differentiation, lipid synthesis ESRRG, GABPA, (ribosomal genes) ‡ 144 , 145 , 146 miR-9 Pancreas Insulin secretion ONECUT2, SIRT1 68 , 69 miR-130 Adipose Adipogenesis PPARG 147 let-7 Muscle, adipose Insulin sensitivity IGF1R, INSR, IRS2, HMGA2 91 , 148

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MicroRNA profiling: approaches and considerations Colin C. Pritchard, Heather H. Cheng & Muneesh Tewari Nature Reviews Genetics 13, 358-369 (May 2012 ) .[ abstract ] MicroRNA Profiling Review:

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Seq-Array SM ACGT101-miR Stem-Loop Specific Detection & Profiling Northern Blotting In situ hybridization Real-time PCR Microarray analysis Next-gen Sequencing Target Determination Bioinformatics – TargetScan , PicTar , PITA Gene / proteome expression analysis Pull-down assays 5′ RACE analyses Degradome Sequencing Functional Analysis Lucifierase Assays Gene knockout/overexpression models miRNA inhibition - antagomirs miRNA mimicry Degradsome Seq Digital Gene Expression Pathway Network miRNA Identification Genetic screening Direct cloning, sequencing Computational strategy – MIRCheck , findMiRNA , MIRscan , MiRAlign Tiling Microarrays Next-gen Sequencing Pathway Analysis Bioinformatics – miRFocus , mirPath , MMIA microRNA Research Tools

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miRNA microarray qRT -PCR custom miRNA microarray Next Gen Sequencing Discovery Profiling Quantitation Validation 3 Major Steps & Technologies } Seq-Array SM

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Sample Preparation Cell Line Tissue Blood Serum Plasma FFPE Block Algea Plant Material Fatty Tissue (Viscous Samples) Total RNA (1-4 µg) Norgen Biotek Ambion Qiagen S elect a kit designed to retain small RNA Select kit based on your sample type Use the same kit for entire experiment miRVana Kit miRNeasy Kit Total RNA Extraction Kit Urine

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You can check the UV spectrum of your sample with a spectrophotometer. ↑ 1.0 ↑ 1.8 260nm 230nm 260nm 280nm Bioanalyzer or 1-1.5% agarose gel 28S rRNA band at 4.5kb - ~2X intensity 18S rRNA band at 1.9kb. For Average Cell Line or Tissue sample – RIN number must be ↑ 7 For other sample types such as Blood or Plant – RIN number does not apply Excessive smearing on the gel indicates degraded RNA. Customer Sample Quality Control

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Customer Sample Quality Control microRNA Microarray Expression Profiling Good Poor Good Poor Good Poor Failure in recovery of RNA <200 nt (including microRNA) 1.5% Formaldehyde Agarose Gel Agilent BioAnalyzer Gel Image Urea-PAGE Gel Images © Norgen Biotek

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Biological Replicates – Still Very Important For experiments performed with a small number of biological replicates, significant results may be due to biological diversity between individuals and may not be reproducible - it is impossible to know whether expression patterns are specific to the individuals in the study or are a characteristic of the test condition. There is no statistical significance for a difference observed between 2 samples. There is no magic to RNA-Seq. These ideas are widely accepted for DNA microarray experiments, where a large number of biological replicates are now required to justify scientific conclusions . Hansen KD, Wu Z, Irizarry RA, Leek JT.  2011 Sequencing technology does not eliminate biological variability. Nat Biotechnol 29:572–573. [ abstract ] Reg. Experimental Design Sample Replicates for Expression Studies

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Key Advantages of RNA-Seq Provides a comprehensive view of the transcriptome. All transcripts can be analyzed (mRNA, ncRNA, snoRNA, lncRNA , miRNA, ...). Not necessarily dependent on any prior sequence knowledge. Increased dynamic range and tunable sensitivity . Can detect structural variations such as gene fusions and alternative splicing events. A truly digital solution (absolute abundance vs relative abundance). Microarray vs RNA Sequencing Key Advantages of Microarray Robust, reliable method, proven over decades of use High through-put method – 100s of samples analyzed per month Streamlined handling – can be easily automated Straightforward data analysis Short turn-around time – 5 days Lower cost

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Microfluidic Array Platform μ Paraflo ® Microfluidics Chip 10 µl total volume 4000 features 270 pl / reaction chamber uniform flow rate

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miRBase Version # of pre-cursor sequences (all species) Version 19 Aug 2012 2003 2011 Flexibility Allows miRBase Synchronicity

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Comprehensive Microarray Services Sample QC Sample preparation Hybridization reactions Advanced data analysis High level customer support Customer Total RNA Small RNA Isolation Labeling Customer Sequences Chip Design Chip Synthesis Chip QC Hybridization Signal Amplification Image Acquisition Customer Analysis Report Data Extraction Data Analysis Sample QC miRBase microRNA Microarray Expression Profiling

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Control / Treated Biological repeats t-Test p < 0.05 p < 0.01 Control Treated Multi-array normalization and clustering analysis Array assay Differentiated miRNAs of Biological & Statistical Significance - Multiple Chips microRNA Microarray Expression Profiling

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Repeats microRNA Microarray Expression Profiling

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Advanced Data Analysis Package Includes: The original and processed chip images An array layout file A raw intensity data file in Excel A fully analyzed data file in Excel A Data Summary containing a catalog of data files, images Images of representative regions of corresponding arrays Descriptions of specific features of the arrays A list of up and down regulated transcripts that are called based on a statistical analysis. microRNA Microarray Expression Profiling

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Key Advantages of RNA-Seq Provides a comprehensive view of the transcriptome. All transcripts can be analyzed (mRNA, ncRNA, snoRNA, lncRNA , miRNA, ...). Not necessarily dependent on any prior sequence knowledge. Increased dynamic range and tunable sensitivity . Can detect structural variations such as gene fusions and alternative splicing events. A truly digital solution (absolute abundance vs relative abundance). Microarray vs RNA Sequencing Key Advantages of Microarray Robust, reliable method, proven over decades of use High through-put method – 100s of samples analyzed per month Streamlined handling – can be easily automated Straightforward data analysis Short turn-around time – 5 days Lower cost

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Small RNA Sequencing and Data Analysis LC Sciences - Comprehensive RNA Sequencing Services Sample QC Sample preparation Library preparation High-throughput sequencing Advanced bioinformatics analysis High level customer support

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Sequencing Run Instrument: Illumina Genome Analyzer GAIIx Length of Reads: 35 bases Number of Reads: ~20-30 Million Data Output: ~0.7-1.0 Gb Bar-coding (Indexing) Samples: We recommend 3 per lane, Max 4 per lane The total number of reads does not change with bar-coding Sacrifice sequencing depth for lower cost Total Reads / Lane Number of Samples / Lane Reads/ Sample 30 M 1 30 M 30 M 2 15 M 30 M 3 10 M 30 M 4 7.5 M 30 M 5 6 M 30 M 6 5 M Small RNA Sequencing and Data Analysis

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Data Flow Mappable reads Raw reads Reads mapped to mammalian mirs in miRBase Reads un-mapped to mammalian mirs in miRBase mirs mapped to species genome mirs un-mapped to species genome Reads mapped to species genome Reads un-mapped to species genome Reads un-mapped to mRNA, Rfam, and repbase Reads mapped to mRNA, Rfam, and repbase Reads mapped to species genome Reads un-mapped to species genome Group 4 no hit others Group 1 Group 2 Group 3 Known species miRNAs Known miRNAs candidate species miRNAs Candidate species miRNAs genome inconsistent with miRBase Potentially novel miRNAs ACGT101-miR v3.5 Software Small RNA Sequencing and Data Analysis

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19,842,938 reads are mappable ADT, Junk, & Seq Filter 11,426,638 reads are mapped to miRBase or are miRNA candidates 2,400,521 reads mapped to mRNA, Rfam and repbase 6,015,779 reads - no hit 10,713,874 reads are filtered out 30,556,812 raw reads from sequencer Grp 1 - 8,007,998 Grp 2 - 14,067 Grp 3 - 64,086 Grp 4 - 3,340,487 64.9% 19.7% 15.1% 0.3% 57.6% 30.3% 12.1% 70.1% 29.2% 0.1% 0.6% Data Flow Small RNA Sequencing and Data Analysis

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Length Distribution of Mappable Reads Small RNA Sequencing and Data Analysis

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Can explain discrepancies array data vs qRT-PCR validation IsomiRs Small RNA Sequencing and Data Analysis

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Molecular Diagnostics / Biomarkers in Body Fluids – Plasma The first demonstration that miRNAs are present in circulating HDL, indicating that disease-associated miRNAs may traffic in lipoprotein particles and convey regulatory information to distant target tissues. Vickers KC, Palmisano BT, Shoucri BM, Shamburek RD, Remaley AT. (2011) MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins . Nat Cell Biol 13(4):423-33.[ article ] Evidence that high-density lipoprotein (HDL) transports endogenous miRNAs and delivers them to recipient cells with functional targeting capabilities. The human HDL–miRNA profile of normal subjects is significantly different from that of familial hypercholesterolemia subjects. Notably, HDL–miRNA from atherosclerotic subjects induced differential gene expression, with significant loss of conserved mRNA targets in cultured hepatocytes . a) Hierarchical clustering heatmap of human HDL–miRNAs from normal (n=6) and familial hypercholesterolemia (FH; n=5) subjects. Blue to red, colour range gradient of mean abundance (−3 to 3). (b) StarGlyph distribution of each miRNA observed on HDL. Log values of the mean RQV. Red, normal; blue, familial hypercholesterolemia HDL.

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Biomarkers – Molecular Diagnostics – Diagnosis Meng S, Cao JT, Zhang B, Zhou Q, Shen CX, Wang CQ. (2012) Downregulation of microRNA-126 in endothelial progenitor cells from diabetes patients, impairs their functional properties, via target gene Spred-1 . J Mol Cell Cardiol 53(1):64-72. [ abstract ] Using miRNA microarray, found the first evidence that miR-126 is downregulated in endothelial progenitor cells (EPCs) from diabetic patients, and impairs EPCs-mediated function via its target, Spred-1, and it is partially mediated through Ras/ERK/VEGF and PI3K/Akt/eNOS signal pathway. If miR-126 is uniquely modified by diabetic vascular injury, it may be capable of adding to the predictive value of conventional risk factors and miR-126 in EPCs. miR-126 as a potential biomarker for diabetes mellitus-associated vascular complications Fig 1 - A) Early EPC isolation from PMBCs. B) FACS analysis showed that 88% cells were both positive for CD31 and CD34. C) Differentially expressed miRNAs in diabetic endothelial progenitor cells. D) The EPCs were cultured for a week.

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Biomarkers – Molecular Diagnostics Study of miRNA expression profiles to assess the molecular effects of EDCs and other toxicants Tilghman SL et al . (2012) Endocrine disruptor regulation of microRNA expression in breast carcinoma cells . PLoS One 7(3):e32754. [ article ] Several environmental agents termed “endocrine disrupting compounds” (EDCs) have been reported to bind and activate the estrogen receptor-α (ER). miRNA microarray results suggest that in addition to E2, the EDCs BPA and DDT affect endogenous levels of estrogen-regulated onco-miR-21 in estrogen-responsive MCF-7 breast cancer cells, supporting the possibility that environmental compounds with estrogenic activity have the potential to play an important role in breast carcinogenesis. Defining the molecular mechanisms underlying EDC-induced miRNA changes and the subsequent cellular consequences may provide insight into the role of EDCs in human disease, including breast cancer. miRNA microarray heatmaps of MCF-7 cells treated with vehicle, estrogen, BPA, or DDT

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Drug Discovery / Therapeutics miRNAs as Endocrine Regulators Vascular endothelial growth factor (VEGF) is a dimeric glycoprotein that plays a crucial role in microvascular complications of diabetes, including diabetic nephropathy. Comparative miRNA expression profile arrays identified miR-93 as a signature miRNA in hyperglycemic conditions. Findings also indicate that miR-93 Represses High Glucose-induced Downstream Targets of VEGF in Podocytes. Dissecting molecular mechanisms by which miR-93 regulates VEGF both in normal and pathological conditions can lead to insights into preventing microvascular complications of diabetes. miRNA mimics and miRNA antisense constructs could hold promise for the design of a new generation of drugs for the treatment of patients with diabetic kidney disease. Long J, Wang Y, Wang W, Chang BH, Danesh FR. (2010) Identification of MicroRNA-93 as a novel regulator of vascular endothelial growth factor (VEGF) In hyperglycemic conditions . J Biol Chem 285(30), 23457-465. [ article ] miR-93 inhibits high glucose-induced downstream target genes of VEGF. A, podocytes were transfected with miR-93 mimics with or without VEGF cDNA lacking 3′-UTR. Cells were serum-starved and exposed to high glucose (HG) for 24 h, and α3 collagen (IV) (COL4A3) or fibronectin (FN1). B, mRNAs were assessed by reverse transcription-qPCR. Expression levels of mRNAs were normalized as described under “Experimental Procedures.” Data are shown as mean ± S.E. (error bars). miR-93 mimics can regulate vascular endothelial growth factor and repress high glucose conditions

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Drug Discovery / Therapeutics miRNAs as Drug Targets Nuclear factor (NF)- κB is strongly activated in human anaplastic thyroid carcinomas (ATCs). Researchers inactivated NF- κB in the ATC-derived FRO cell line and analyzed its miRNA profile in comparison with the parental counterpart by using a miRNA chip microarray. Results show that miR-146a transcription was controlled by NF- κB and demonstrate that NF- κB contributes to anaplastic thyroid cancer by up-regulating the expression of miR-146a. These functional studies suggest regulation of mir-146a expression might be exploited for therapeutic purposes. Pacifico F et al. (2010) Nuclear factor-{kappa}B contributes to anaplastic thyroid carcinomas through up-regulation of miR-146a . J Clin Endocrinol Metab 95(3):1421-30. [ article ] miR-146a inhibition in FRO cells determines the block of their oncogenic potential. (A) Colony formation assay of parental and transfected FRO cells. Colonies larger than 50 cells were scored after 2 wk of incubation at 37 C (B). Matrigel invasion assay of parental and transfected FRO (C) and BHT 101 (D) cells are shown. Quantitative analysis of matrigel FRO (E) and BHT 101 (F) invading cells. miR-146a inhibition in FRO cells determines the block of their malignant potential.

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Drug Discovery / Therapeutics miRNAs as Drug Targets Immature αβ T cells developing in the thymus are particularly sensitive to stress, with infections and/or exposure to lipopolysaccharide or glucocorticoids eliciting a rapid apoptotic program. Performed microRNA profiling of thymic microRNAs isolated from control or stressed thymic tissue obtained from mice and identified 18 microRNAs that are dysregulated >1.5-fold in response to lipopolysaccharide or the synthetic corticosteroid dexamethasone . Many of the differentially regulated microRNAs have known functions in thymopoiesis , indicating that their dysregulation will alter T cell repertoire selection and the formation of naïve T cells. This data has implications for clinical treatments involving anti-inflammatory steroids, ablation therapies, and provides mechanistic insights into the consequences of infections. Belkaya S, Silge RL, Hoover AR, Medeiros JJ, Eitson JL, et al. (2011) Dynamic Modulation of Thymic MicroRNAs in Response to Stress . PLoS ONE 6(11): e27580. [ article ] Representative microarray chip scans show differential expression of miRNAs in the thymus of control (PBS) and LPS-treated mice (t = 72 h). (A) Lymphocytes were isolated from control (PBS injected, t = 72 h), LPS, or Dex injected mice (t = 24, 48 and 72 h). The total lymphoid cellularity was determined. Thymically encoded microRNAs are stress responsive and modulate thymopoiesis .

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