Radiogenomic Biomarker and Multiomic Data Integration to Predict Radiation Response in Lung Cancer
Chemotherapy and radiation remain the standard treatments for locally advanced lung cancer. Radiation therapy accounts for nearly half of cancer cures, but our understanding of how individual patients will respond to radiation is limited. In radiation oncology, dosing and combination therapy choices are made with few options for personalization based on predicted patient response. Our goal is to collect and analyze various types of data collected from lung cancer patients over the course of receiving standard treatments. We are interested in understanding how cells react to therapy, specifically from a transcriptomic and radiomic lens. We will use modern genomic and radiomic techniques to measure the dynamic responses of non-small cell lung cancer tumors to understand how these tumors change during therapy. Such knowledge will generate broad impact on precision care for lung cancer patients through developing radiogenomic biomarkers that predict therapeutic response and inform clinical decision making.
