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Identification of genomic aberrations in hemangioblastoma by droplet digital PCR and SNP microarray highlights novel candidate genes and pathways for pathogenesis

  • Ruty Mehrian-Shai
  • , Michal Yalon
  • , Itai Moshe
  • , Iris Barshack
  • , Dvorah Nass
  • , Jasmine Jacob
  • , Chen Dor
  • , Juergen K.V. Reichardt
  • , Shlomi Constantini
  • , Amos Toren
  • Tel Aviv University
  • Sheba Medical Center at Tel Hashomer
  • James Cook University Queensland
  • Tel Aviv Sourasky Medical Center

Research output: Contribution to journal › Article › peer-review

24 Scopus citations

Abstract

Background: The genetic mechanisms underlying hemangioblastoma development are still largely unknown. We used high-resolution single nucleotide polymorphism microarrays and droplet digital PCR analysis to detect copy number variations (CNVs) in total of 45 hemangioblastoma tumors. Results: We identified 94 CNVs with a median of 18 CNVs per sample. The most frequently gained regions were on chromosomes 1 (p36.32) and 7 (p11.2). These regions contain the EGFR and PRDM16 genes. Recurrent losses were located at chromosome 12 (q24.13), which includes the gene PTPN11. Conclusions: Our findings provide the first high-resolution genome-wide view of chromosomal changes in hemangioblastoma and identify 23 candidate genes: EGFR, PRDM16, PTPN11, HOXD11, HOXD13, FLT3, PTCH, FGFR1, FOXP1, GPC3, HOXC13, HOXC11, MKL1, CHEK2, IRF4, GPHN, IKZF1, RB1, HOXA9, and micro RNA, such as hsa-mir-196a-2 for hemangioblastoma pathogenesis. Furthermore, our data implicate that cell proliferation and angiogenesis promoting pathways may be involved in the molecular pathogenesis of hemangioblastoma.

Original languageEnglish
Article number56
JournalBMC Genomics
Volume17
Issue number1
DOIs
StatePublished - 14 Jan 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 Mehrian-Shai et al.

Funding

This research was funded by The Sheba Medical Research fund. We thank Sarah South, PhD, University of Utah, for insightful remarks on Affymetrix CGH analysis.

Funders
Sheba Medical Research fund

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • CGH
    • Cancer
    • Digital PCR
    • Hemangioblastoma

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