A team of researchers at Baylor College of Medicine, ed the University of Pittsburgh Cancer Institute, RainDance Technologies, Inc., and Mayo Clinic College of Medicine and Science has developed a novel computational approach to unravel the complexity of breast cancer tumors. The strategy allows researchers to identify the different types of cells in the tumor and to unveil how the interactions between cancer and normal cells may shape the fate of the tumor. The results appear in Cell Reports.
“We have developed a computational method that allows us to better understand what goes on inside a tumor,” said first author Vitor Onuchic, who is a graduate student in the Program in Structural and Computational Biology and Molecular Biophysics at Baylor in the Bioinformatics Research Laboratory. “We can infer the cell type composition of breast tumors, detecting both normal and cancerous cell types. We can also detect changes in the epigenomic and transcriptomic profiles of individual cell types, which indicate what parts of the genome – the genetic makeup of the cell – become activated or inactivated within each cell type, as the cancer progresses.”
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