Predicting Which Patients Will Benefit From Immunotherapy

A mathematical model may help providers better understand which patients will benefit from certain immunotherapy.

A study published in Nature proposed a mathematical model developed by researchers at the Icahn School of Medicine at Mount Sinai that captures aspects of the tumor’s evolution and underlying interactions of the tumor with the immune system.

“This approach will hopefully lead to better mechanistic predictive modeling of response and future design of therapies that further take advantage of how the immune system recognizes tumors,” Benjamin Greenbaum, PhD, of The Tisch Cancer Institute at the Icahn School of Medicine at Mount Sinai, and the senior author, said in a statement.

The researchers used data from patients with melanoma and lung cancer who were being treated with immune checkpoint inhibitors, and tracked many properties within the immune response to the drugs. In particular, they tracked neoantigens, which have the potential to be prime immunotherapy targets.

The model was found to be more accurate in predicting how the tumor will respond to immunotherapy. According to researchers, the model also has the potential to find new therapeutic targets and help design vaccines for patients who do not typically respond to immunotherapy.

A companion study from researchers at Memorial Sloan Kettering (MSK) Cancer Center provided a better understanding of why some patients with pancreatic cancer survive longer than others.

“This research represents a big step forward in understanding why some tumors are more aggressive than others and being able to predict rationally which neoantigens will be the most effective at stimulating an immune response,” said Vinod P. Balachandran, MD, a member of the David M. Rubenstein Center for Pancreatic Cancer Research at MSK, and corresponding author of the companion study in Nature.

The research was part of the Stand Up To Cancer’s “Convergence” model funding, which sought to bring the benefits of immunotherapy to more patients.