Abstract for presentation at 11th International Congress of Human Genetics

Characterizing Rearrangements in Glioma using Genomic Tilepath Microarrays

  • Nicole Johnson, Duke University Center for Human Genetics, United States
  • Dr Jessica Connelly, Duke University Center for Human Genetics, United States
  • Josh Virgadamo, Duke University Center for Human Genetics, United States
  • Dr Roger McLendon, Duke University Comprehensive Cancer Center, United States
  • Dr Jeffery Vance, Duke University Center for Human Genetics, United States
  • Dr Darrell Bigner, Duke University Comprehensive Cancer Center, United States
  • Simon Gregory, Duke University Center for Human Genetics, United States
  • Gliomas account for 60% of the estimated 17,000 primary brain tumors diagnosed in the United States each year. These malignant tumors include astrocytoma, oligodendroglioma and glioblastoma, and are commonly located in the central nervous system. Gliomas have a broad histopathology, are variably sensitive to treatment and, therefore, have unpredictable progression and survival times. We have used genomic microarrays, consisting of tilepath coverage of the entire human genome, to identify genomic alterations which contribute to the pathology of glioma. We conducted high resolution comparative genomic hybridization (hrCGH) microarray analysis of 76 grades II and III oligodendroglioma, 36 glioblastoma, and 13 astrocytomas to elucidate these mechanisms. Chromosome aberrations were correlated with stage and progression within and between glioma sub-types. Gene expression data was collected on a subset of oligodendroglioma patients and these data was compared with hrCGH profiles according to patient clinical outcomes. Genes that showed differential expression were correlated with regions of genomic amplification or deletion. Here we present our findings of common loss of 1p and 19q associated with OD, the accumulation of genomic rearrangements allied with stage progression, and the hrCGH profiles of patient clinical outcomes for short and long prognosis for progression free survival. Our method of data convergence will provide a powerful tool for identifying candidate genes that are implicated in glioma pathogenesis and will provide an insight into the poorly understood molecular mechanisms underlying glioma formation and development.

    Conference Organiser - ICMS Pty Ltd