Investigators at the USTAR Center for Genetic Discovery are developing computational methods to track metastatic tumors as they accumulate mutations over the course of disease and treatment. Following the trajectories of tumors will allow physicians to prescribe targeted treatments at the right time to prevent disease relapse.
Cancer is difficult to beat because tumors adapt, allowing them to become resistant to treatment, metastasize, and ultimately become unstoppable. Yi Qiao, PhD, a director of research and science, created Subclone Seeker, a computer algorithm that can differentiate between normal and cancerous cells, as well as between mutational subclones obtained from a tumor biopsy.
In collaboration with clinicians at the Huntsman Cancer Institute, Qiao analyzed serial samples collected from women as their breast cancer changed over the course of their disease. The analyses allowed investigators to identify differences in individual cancer cells from the same patient, including pinpointing cells that were resistant or sensitive to treatment.
Investigation showed that treatment-resistant cells shared some common characteristics, and that knowledge could be used to identify targeted therapies to successfully kill the cells in the lab.
The USTAR Center for Genetic Discovery and Huntsman Cancer Institute are continuing to develop these technologies with a goal of bringing personalized cancer care to the clinic.