Cancer researcher receives grant to study how deep learning can improve immunotherapy
Willy Hugo, PhD, a melanoma scientist at the UCLA Jonsson Comprehensive Cancer Center, has received a $75,000 grant from the Margaret E. Early Medical Research Trust to help understand the underlying mechanism of response to immune checkpoint inhibitors, a type of immunotherapy drug.
Hugo, who is adjunct assistant professor of dermatology in the David Geffen School of Medicine at UCLA, is using this funding to design a machine learning method to help identify the spatial pattern of the intratumoral immune cells to better understand biological insights, which can potentially be used to predict the response or resistance to immune checkpoint inhibitors.
Immune-checkpoint inhibitors have helped revolutionize cancer therapy, extending the lives of people with advanced cancers that have little to no treatment options. These drugs work by blocking the interaction between PD-1 and PD-L1, enabling the immune system to better attack the cancer. However, there are still many people who do not respond to the therapy. Multiple studies had proposed supportive and inhibitory roles for different type of immune cells in the microenvironment and this study attempts to perform unbiased learning from hundreds of tumor samples to identify the cell populations, which drives response to immune checkpoint inhibitors
“While checkpoint inhibitors have been effective in treating multiple advanced cancers, only around half of patients who are treated with this type of therapy actually see a benefit,” Hugo said. “Moreover, the tumors of some those patients who did not respond to the therapy show a similar amount of immune cell infiltrations, raising the question of why these cells were not activated by the therapy. I’m hoping this project will give us more insight into how to make this type of therapy more effective for more people.”