BBDS Scientists Led the Development of Computational Pipeline to Help Predict Cancer Therapy Response

Berkeley Lab scientists led the development of an algorithm and a computational pipeline that analyzes large sets of tumor images. Their work will help scientists learn more about the genetic and molecular mechanisms that control tumor signatures. It will also shed light on whether tumor subtype can predict the effectiveness of therapies. The research was led by Hang Chang, Ju Han, Leandro Loss, and Bahram Parvin of the Life Sciences Division, as well as scientists from several other institutions. The scientists validated their pipeline by applying it to 377 whole-slide images from patients who have an aggressive brain cancer. (Read more)