Comprehensive Gene expression meta-analysis and integrated bioinformatic approaches reveal shared signatures between thrombosis and myeloproliferative disorders

Sci Rep. 2016 Nov 28:6:37099. doi: 10.1038/srep37099.

Abstract

Thrombosis is a leading cause of morbidity and mortality in patients with myeloproliferative disorders (MPDs), particularly polycythemia vera (PV) and essential thrombocythemia (ET). Despite the attempts to establish a link between them, the shared biological mechanisms are yet to be characterized. An integrated gene expression meta-analysis of five independent publicly available microarray data of the three diseases was conducted to identify shared gene expression signatures and overlapping biological processes. Using INMEX bioinformatic tool, based on combined Effect Size (ES) approaches, we identified a total of 1,157 differentially expressed genes (DEGs) (697 overexpressed and 460 underexpressed genes) shared between the three diseases. EnrichR tool's rich library was used for comprehensive functional enrichment and pathway analysis which revealed "mRNA Splicing" and "SUMO E3 ligases SUMOylate target proteins" among the most enriched terms. Network based meta-analysis identified MYC and FN1 to be the most highly ranked hub genes. Our results reveal that the alterations in biomarkers of the coagulation cascade like F2R, PROS1, SELPLG and ITGB2 were common between the three diseases. Interestingly, the study has generated a novel database of candidate genetic markers, pathways and transcription factors shared between thrombosis and MPDs, which might aid in the development of prognostic therapeutic biomarkers.

Publication types

  • Meta-Analysis

MeSH terms

  • Biomarkers / metabolism
  • Databases, Genetic
  • Humans
  • Microarray Analysis
  • Myeloproliferative Disorders / complications
  • Myeloproliferative Disorders / genetics*
  • Polycythemia Vera / complications
  • Polycythemia Vera / genetics*
  • Thrombocythemia, Essential / complications
  • Thrombocythemia, Essential / genetics*
  • Transcriptome*

Substances

  • Biomarkers