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Semin Thromb Hemost 2008; 34(6): 532-538
DOI: 10.1055/s-0028-1103364
© Thieme Medical Publishers

Genomic and Proteomic Applications in Diagnosis of Platelet Disorders and Classification

Lisa Senzel1 , Dmitri V. Gnatenko2 , Wadie F. Bahou2
  • 1Department of Pathology, State University of New York, Stony Brook, New York
  • 2Department of Medicine, State University of New York, Stony Brook, New York
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Publication History

Publication Date:
28 November 2008 (online)

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ABSTRACT

The transcriptome is the mRNA pool found within a cell. Transcriptomic discovery approaches include microarray-based technologies as well as sequencing-based technologies. Transcriptomic experiments provide dynamic information about gene expression at the tissue level. The proteome is the pool of proteins expressed at a given time and circumstance. The word proteomics summarizes several technologies for visualization, quantitation, and identification of these proteins. Protein separation can be accomplished by two-dimensional electrophoresis, use of protein chips with an affinity matrix, or by a variety of advanced chromatographic methods. Mass spectrometry is used to identify the proteins in conjunction with protein sequence databases. Recent proteomic experiments in resting and activated platelets have identified novel signaling pathways and secreted proteins. Platelet transcriptomic studies in essential thrombocythemia, atherosclerotic disease, sickle cell disease, and an inherited platelet defect are reviewed. Transcript profiling has the potential to distinguish molecular signatures in normal and diseased platelets and to classify prothrombotic patient phenotypes to tailor their therapy.

KEYWORDS

Genomics - transcriptomics - proteomics - microarray - platelets

REFERENCES

  • 1 Denis M M, Tolley N D, Bunting M et al.. Escaping the nuclear confines: signal-dependent pre-mRNA splicing in anucleate platelets.  Cell. 2005;  122 379-391
    CrossrefPubMedGoogle Scholar
  • 2 Gnatenko D V, Perrotta P L, Bahou W F. Proteomic approaches to dissect platelet function: half the story.  Blood. 2006;  108 3983-3991
    CrossrefPubMedGoogle Scholar
  • 3 Senis Y A, Tomlinson M G, Garcia A et al.. A comprehensive proteomics and genomics analysis reveals novel transmembrane proteins in human platelets and mouse megakaryocytes including G6b-B, a novel immunoreceptor tyrosine-based inhibitory motif protein.  Mol Cell Proteomics. 2007;  6 548-564
    PubMedGoogle Scholar
  • 4 Gnatenko D V, Dunn J J, McCorkle S R, Weissmann D, Perrotta P L, Bahou W F. Transcript profiling of human platelets using microarray and serial analysis of gene expression.  Blood. 2003;  101 2285-2293
    CrossrefPubMedGoogle Scholar
  • 5 Rox J M, Bugert P, Muller J et al.. Gene expression analysis in platelets from a single donor: evaluation of a PCR-based amplification technique.  Clin Chem. 2004;  50 2271-2278
    CrossrefPubMedGoogle Scholar
  • 6 McRedmond J P, Park S D, Reilly D F et al.. Integration of proteomics and genomics in platelets: a profile of platelet proteins and platelet-specific genes.  Mol Cell Proteomics. 2004;  3 133-144
    PubMedGoogle Scholar
  • 7 Bugert P, Dugrillon A, Gunaydin A, Eichler H, Kluter H. Messenger RNA profiling of human platelets by microarray hybridization.  Thromb Haemost. 2003;  90 738-748
    PubMedGoogle Scholar
  • 8 Bugert P, Kluter H. Profiling of gene transcripts in human platelets: an update of the platelet transcriptome.  Platelets. 2006;  17 503-504
    CrossrefPubMedGoogle Scholar
  • 9 Frankhauser P, Grimmer Y, Bugert P, Deuschle M, Schmidt M, Schloss P. Characterization of the neuronal dopamine transporter DAT in human blood platelets.  Neurosci Lett. 2006;  399 197-201
    CrossrefPubMedGoogle Scholar
  • 10 Rainesalo S, Keranen T, Saransaari P, Honkaniemi J. GABA and glutamate transporters are expressed in human platelets.  Brain Res Mol Brain Res. 2005;  141 161-165
    CrossrefPubMedGoogle Scholar
  • 11 Macaulay I C, Tijssen M R, Thijssen-Timmer D C et al.. Comparative gene expression profiling of in vitro differentiated megakaryocytes and erythroblasts identifies novel activatory and inhibitory platelet membrane proteins.  Blood. 2007;  109 3260-3269
    CrossrefPubMedGoogle Scholar
  • 12 Tenedini E, Fagioli M E, Vianelli N et al.. Gene expression profiling of normal and malignant CD34-derived megakaryocytic cells.  Blood. 2004;  104 3126-3135
    CrossrefPubMedGoogle Scholar
  • 13 Gnatenko D V, Cupit L D, Huang E C, Dhundale A, Perrotta P L, Bahou W F. Platelets express steroidogenic 17beta-hydroxysteroid dehydrogenases. Distinct profiles predict the essential thrombocythemic phenotype.  Thromb Haemost. 2005;  94 412-421
    PubMedGoogle Scholar
  • 14 Gnatenko D V, Zhu W, Dhundale A, Bahou W F. Class prediction models of thrombocytosis using gene profiling.  , [abstract] Blood. 2007;  110 38a
    PubMedGoogle Scholar
  • 15 Golub T R, Slonim D K, Tamayo P et al.. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.  Science. 1999;  286 531-537
    CrossrefPubMedGoogle Scholar
  • 16 Sun L, Gorospe J R, Hoffman E P, Rao A K. Decreased platelet expression of myosin regulatory light chain polypeptide (MYL9) and other genes with platelet dysfunction and CBFA2/RUNX1 mutation: insights from platelet expression profiling.  J Thromb Haemost. 2007;  5 146-154
    CrossrefPubMedGoogle Scholar
  • 17 Raghavachari N, Xu X, Harris A et al.. Amplified expression profiling of platelet transcriptome reveals changes in arginine metabolic pathways in patients with sickle cell disease.  Circulation. 2007;  115 1551-1562
    CrossrefPubMedGoogle Scholar
  • 18 Healy A M, Pickard M D, Pradhan A D et al.. Platelet expression profiling and clinical validation of myeloid-related protein-14 as a novel determinant of cardiovascular events.  Circulation. 2006;  113 2278-2284
    CrossrefPubMedGoogle Scholar
  • 19 Krishnan U, Goodall A H, Bugert P. Letter by Krishnan et al regarding article, “Platelet expression profiling and clinical validation of myeloid-related protein-14 as a novel determinant of cardiovascular events.  Circulation. 2007;  115 e186
    CrossrefPubMedGoogle Scholar
  • 20 Morrow D A, Wang Y, Croce K et al.. Myeloid-related protein 8/14 and the risk of cardiovascular death or myocardial infarction after an acute coronary syndrome in the Pravastatin or Atorvastatin Evaluation and Infection Therapy: Thrombolysis in Myocardial Infarction (PROVE IT-TIMI 22) trial.  Am Heart J. 2008;  155 49-55
    CrossrefPubMedGoogle Scholar
  • 21 Peck D, Crawford E D, Ross K N, Stegmaier K, Golub T R, Lamb J. A method for high-throughput gene expression signature analysis.  Genome Biol. 2006;  7 R61
    CrossrefPubMedGoogle Scholar
  • 22 Eisenstein M. Microarrays: quality control.  Nature. 2006;  442 1067-1070
    PubMedGoogle Scholar
  • 23 Strauss E. Arrays of hope.  Cell. 2006;  127 657-659
    CrossrefPubMedGoogle Scholar
  • 24 Maguire P B, Foy M, Fitzgerald D J. Using proteomics to identify potential therapeutic targets in platelets.  Biochem Soc Trans. 2005;  33 409-412
    CrossrefPubMedGoogle Scholar
  • 25 de Hoog C L, Mann M. Proteomics.  Annu Rev Genomics Hum Genet. 2004;  5 267-293
    CrossrefPubMedGoogle Scholar
  • 26 Delahunty C M, Yates III J R. MudPIT: multidimensional protein identification technology.  Biotechniques. 2007;  43 563, 565, 567
    PubMedGoogle Scholar
  • 27 Kocher T, Superti-Furga G. Mass spectrometry-based functional proteomics: from molecular machines to protein networks.  Nat Methods. 2007;  4 807-815
    CrossrefPubMedGoogle Scholar
  • 28 Garcia A. Proteome analysis of signaling cascades in human platelets.  Blood Cells Mol Dis. 2006;  36 152-156
    CrossrefPubMedGoogle Scholar
  • 29 Macaulay I C, Carr P, Gusnanto A, Ouwehand W H, Fitzgerald D, Watkins N A. Platelet genomics and proteomics in human health and disease.  J Clin Invest. 2005;  115 3370-3377
    CrossrefPubMedGoogle Scholar
  • 30 Dittrich M, Birschmann I, Stuhlfelder C et al.. Understanding platelets. Lessons from proteomics, genomics and promises from network analysis.  Thromb Haemost. 2005;  94 916-925
    PubMedGoogle Scholar
  • 31 Maynard D M, Heijnen H F, Horne M K, White J G, Gahl W A. Proteomic analysis of platelet alpha-granules using mass spectrometry.  J Thromb Haemost. 2007;  5 1945-1955
    CrossrefPubMedGoogle Scholar
  • 32 Hernandez-Ruiz L, Valverde F, Jimenez-Nunez M D et al.. Organellar proteomics of human platelet dense granules reveals that 14–3-3zeta is a granule protein related to atherosclerosis.  J Proteome Res. 2007;  6 4449-4457
    CrossrefPubMedGoogle Scholar
  • 33 Greening D W, Glenister K M, Kapp E A et al.. Comparison of human platelet membrane-cytoskeletal proteins with the plasma proteome: Towards understanding the platelet-plasma nexus.  Proteomics Clin Appl. 2008;  2 63-77
    CrossrefPubMedGoogle Scholar
  • 34 Moebius J, Zahedi R P, Lewandrowski U, Berger C, Walter U, Sickmann A. The human platelet membrane proteome reveals several new potential membrane proteins.  Mol Cell Proteomics. 2005;  4 1754-1761
    PubMedGoogle Scholar
  • 35 Smalley D M, Root K E, Cho H, Ross M M, Ley K. Proteomic discovery of 21 proteins expressed in human plasma-derived but not platelet-derived microparticles.  Thromb Haemost. 2007;  97 67-80
    PubMedGoogle Scholar
  • 36 Garcia B A, Smalley D M, Cho H, Shabanowitz J, Ley K, Hunt D F. The platelet microparticle proteome.  J Proteome Res. 2005;  4 1516-1521
    CrossrefPubMedGoogle Scholar
  • 37 Coppinger J A, Cagney G, Toomey S et al.. Characterization of the proteins released from activated platelets leads to localization of novel platelet proteins in human atherosclerotic lesions.  Blood. 2004;  103 2096-2104
    CrossrefPubMedGoogle Scholar
  • 38 Martens L, Van D P, Van D J et al.. The human platelet proteome mapped by peptide-centric proteomics: a functional protein profile.  Proteomics. 2005;  5 3193-3204
    CrossrefPubMedGoogle Scholar
  • 39 Nanda N, Bao M, Lin H et al.. Platelet endothelial aggregation receptor 1 (PEAR1), a novel epidermal growth factor repeat-containing transmembrane receptor, participates in platelet contact-induced activation.  J Biol Chem. 2005;  280 24680-24689
    CrossrefPubMedGoogle Scholar
  • 40 Garcia A, Prabhakar S, Hughan S et al.. Differential proteome analysis of TRAP-activated platelets: involvement of DOK-2 and phosphorylation of RGS proteins.  Blood. 2004;  103 2088-2095
    CrossrefPubMedGoogle Scholar
  • 41 Marcus K, Immler D, Sternberger J, Meyer H E. Identification of platelet proteins separated by two-dimensional gel electrophoresis and analyzed by matrix assisted laser desorption/ionization-time of flight-mass spectrometry and detection of tyrosine-phosphorylated proteins.  Electrophoresis. 2000;  21 2622-2636
    CrossrefPubMedGoogle Scholar
  • 42 O'Neill E E, Brock C J, von Kriegsheim A F et al.. Towards complete analysis of the platelet proteome.  Proteomics. 2002;  2 288-305
    CrossrefPubMedGoogle Scholar
  • 43 Bugert P, Ficht M, Kluter H. Towards the identification of novel platelet receptors: Comparing RNA and proteome approaches.  Transfus Med Hemother. 2006;  33 236-243
    CrossrefPubMedGoogle Scholar
  • 44 Hillmann A G, Harmon S, Park S D, O'brien J, Shields D C, Kenny D. Comparative RNA expression analyses from small-scale, single-donor platelet samples.  J Thromb Haemost. 2006;  4 349-356
    CrossrefPubMedGoogle Scholar
  • 45 Guerrier L, Claverol S, Fortis F et al.. Exploring the platelet proteome via combinatorial, hexapeptide ligand libraries.  J Proteome Res. 2007;  6 4290-4303
    CrossrefPubMedGoogle Scholar
  • 46 Yee D L, Sun C W, Bergeron A L et al.. Aggregometry detects platelet hyperreactivity in healthy individuals.  Blood. 2005;  106 2723-2729
    CrossrefPubMedGoogle Scholar
  • 47 Tang Y, Xu H, Du X et al.. Gene expression in blood changes rapidly in neutrophils and monocytes after ischemic stroke in humans: a microarray study.  J Cereb Blood Flow Metab. 2006;  26 1089-1102
    CrossrefPubMedGoogle Scholar
  • 48 Moore D F, Li H, Jeffries N et al.. Using peripheral blood mononuclear cells to determine a gene expression profile of acute ischemic stroke: a pilot investigation.  Circulation. 2005;  111 212-221
    CrossrefPubMedGoogle Scholar
  • 49 Ma J, Liew C C. Gene profiling identifies secreted protein transcripts from peripheral blood cells in coronary artery disease.  J Mol Cell Cardiol. 2003;  35 993-998
    CrossrefPubMedGoogle Scholar
  • 50 Tabibiazar R, Wagner R A, Ashley E A et al.. Signature patterns of gene expression in mouse atherosclerosis and their correlation to human coronary disease.  Physiol Genomics. 2005;  22 213-226
    PubMedGoogle Scholar
  • 51 Seo D, Wang T, Dressman H et al.. Gene expression phenotypes of atherosclerosis.  Arterioscler Thromb Vasc Biol. 2004;  24 1922-1927
    CrossrefPubMedGoogle Scholar
  • 52 Karra R, Vemullapalli S, Dong C et al.. Molecular evidence for arterial repair in atherosclerosis.  Proc Natl Acad Sci U S A. 2005;  102 16789-16794
    CrossrefPubMedGoogle Scholar
  • 53 Potti A, Bild A, Dressman H K, Lewis D A, Nevins J R, Ortel T L. Gene-expression patterns predict phenotypes of immune-mediated thrombosis.  Blood. 2006;  107 1391-1396
    CrossrefPubMedGoogle Scholar
  • 54 Pellagatti A, Vetrie D, Langford C F et al.. Gene expression profiling in polycythemia vera using cDNA microarray technology.  Cancer Res. 2003;  63 3940-3944
    PubMedGoogle Scholar
  • 55 Goerttler P S, Kreutz C, Donauer J et al.. Gene expression profiling in polycythaemia vera: overexpression of transcription factor NF-E2.  Br J Haematol. 2005;  129 138-150
    CrossrefPubMedGoogle Scholar
  • 56 Kralovics R, Teo S S, Buser A S et al.. Altered gene expression in myeloproliferative disorders correlates with activation of signaling by the V617F mutation of Jak2.  Blood. 2005;  106 3374-3376
    CrossrefPubMedGoogle Scholar
  • 57 Hyman T, Huizing M, Blumberg P M, Falik-Zaccai T C, Anikster Y, Gahl W A. Use of a cDNA microarray to determine molecular mechanisms involved in grey platelet syndrome.  Br J Haematol. 2003;  122 142-149
    CrossrefPubMedGoogle Scholar

Lisa SenzelM.D. Ph.D. 

Department of Pathology, State University of New York, Stony Brook, University Hospital

Level 3, Rm 532, Stony Brook, NY 11794-7300

Email: lsenzel@notes.cc.sunysb.edu

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