image: A diagram outlining the experimental workflow for the UVA team's investigation of transcribed ultra conserved regions (TUCRs) in glioblastoma.
Credit: COURTESY OF ROGER ABOUNDER, UNIVERSITY OF VIRGINIA
Glioblastoma is an extremely aggressive type of brain cancer with a typically low survival rate. At the University of Virginia, two researchers are joining forces to study an unexplored part of the genome and its role in glioblastoma.
Stephen Turner, assistant dean for research in the School of Data Science, and Roger Abounder, professor of microbiology, immunology, and cancer biology, received funding for their project from a pilot grant program that supports collaborative efforts between data science and Cancer Center researchers.
“As many of you know, glioblastoma is a common, lethal central nervous system malignancy,” Turner said. “Even with maximal therapy — chemo, radiation, surgery — its median survival is just a little over a year.”
Turner and Abounder are working together to apply machine learning and functional genomics to better understand the function of transcribed ultra conserved regions (TUCR) in glioblastoma.
For decades, much of genomic research has focused on the protein-coding portion of the genome, Turner said, which represents only a small fraction of the overall genome. The vast, unexplored portion of the genome is the focus of their project.
While tens of thousands of publications exist on certain well-studied segments of the genome, Turner noted that TUCRs only have around 70 related publications, and prior to this project, none specifically examined their role in glioblastoma.
Turner presented the project, “ML and Functional Genomics to Understand Function of TUCRs in Glioblastoma,” at a Cancer-Data Science Research Symposium at UVA on Feb. 19.
“The appetite for cancer and data science collaboration at UVA is real,” Turner said to attendees, some of whom applied for the same pilot funding for their research projects.
“That was the whole point of the symposium: to surface the problems cancer researchers are wrestling with and match them up with data scientists who want in.”