Brock Receives NCI U01 Grant to Integrate Big Data in Cancer Treatment

January 20, 2021

In the 77 years since chemotherapy has been used to treat cancer, it has extended the lives of many patients. Yet some patients develop resistance to chemotherapy, and this remains a clinical challenge. Associate Professor Amy Brock’s work focuses on analyzing individual cancer cells within tumors to gain insights into the reasons some of them become resistant to chemotherapy, in an effort to find more effective treatment methods for more patients.

amy brock

Brock, who holds the Raymond F. Dawson Centennial Teaching Fellowship in Engineering, has received a five-year U01 grant from the National Cancer Institute with a goal of quantifying the dynamics of drug resistance from experimental data and integrating that information into mathematical models that can predict patient-specific treatments and schedules.

While efforts to analyze big data in cancer have helped researchers study the disease at the molecular and genomic scale, one aspect that makes this project unique is that it will combine different high-dimensional data types, including analyzing cell responses to treatment at different timepoints.

Brock and the research team, which includes Professor Tom Yankeelov of the Department of Biomedical Engineering and Oden Institute for Engineering and Computational Sciences and Associate Professor Carla Van Den Berg of the Livestrong Cancer Institutes and Department of Oncology in the Dell Medical School, will gain in-depth insight by first measuring individual cell gene expression changes in treatment and assembling these measurements into cell subpopulation trajectories.

Using an innovative barcoding technology developed by the Brock lab, researchers will build a compendium of gene expression, cell growth and survival data of these trajectories. This data will ultimately lead to the building of a cohesive framework that can be used to describe how sensitive and resistant subpopulations of tumor cells grow, die, and transition in response to treatment.