We are a computational cancer biology lab with a research focus on the analysis of cancer genomics data to improve our understanding of cancer biology. We have a specialized research interest in understanding disease progression of brain tumors, particularly glioblastoma and glioma. We mostly use high throughput sequencing and computational analysis in our research.
2016: AAAS Martin and Rose Wachtel Cancer Research Award
2015: Finalist, Robert M. Chamberlain Distinguished Mentor Award.
2014: Adult Basic Science Award, Society for Neuro-Oncology Meeting 2014
2013: Pediatric Brain Tumor Foundation, Peter Steck Memorial Award
2011: Wilson S. Stone Memorial Award at MD Anderson's Symposia on Cancer Research
The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.
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Cancer cells hijack a mechanism that enables stem cells and germ cells to continue dividing, by reactivating telomerase. A research team led by JAX Professor Roel Verhaak reports on the discovery that, in about 35 percent of cancers, TERT promoter methylation is the key to cancer cells' success in maintaining telomeres and surviving.
New research is providing a better understanding of the processes underlying cell-to-cell differences within glioblastoma tumors — a crucial finding because these differences contribute to therapy resistance.