Algorithm to be highlighted during ASCO Annual Meeting accurately predicted Anti-PD-L1 response in 90% of cases
- Roswell Park, OmniSeq collaborated to predict response to Anti-PD-L1 treatment
- Team developed and tested an algorithm based on a 54-gene signature
- Custom algorithm accurately correlated with treatment response in 90% of cases
BUFFALO, N.Y. — The class of immunotherapies known as checkpoint inhibitors have proven to be a highly effective and advantageous treatment option for many cancer patients, but they don’t work well for everyone, and oncologists have no reliable way to determine in advance which patients are likely to respond to these drugs. Looking to identify a genetic profile to predict how patients will respond to checkpoint inhibition, also known as anti PD-L1 therapy, researchers from Roswell Park Comprehensive Cancer Center and OmniSeq collaborated to sequence the tumors of patients who had completed treatment with checkpoint inhibitors. They will report the results of this analysis at the American Society of Clinical Oncology (ASCO) 53rd Annual Meeting in Chicago.
“While some patients will respond well to checkpoint inhibitors, many will see their tumors progress quickly, so giving them these treatments actually could hurt more than it helps. The task of developing a predictive tool to help oncologists determine which patients will and will not respond to anti-PD-L1 therapy is a matter of high priority,” says Carl Morrison, MD, DVM, Executive Director of the Center for Personalized Medicine at Roswell Park and founder and Chief Scientific Officer of OmniSeq.
The research team discovered a set of 54 immune-related genes using expression data from whole transcriptome RNA-sequencing in 300 tumor specimens. They then designed a sequencing test to measure both gene expression and tumor mutational burden from a population of 167 Roswell Park patients previously treated with approved checkpoint inhibitors, with complete treatment and response data available for 87 patients. From these measurements and data, the team created and tested an algorithm designed to predict clinical response to checkpoint inhibition. Their algorithm, which incorporated expression data for those 54 genes along with a patient’s mutational burden, accurately reflected therapeutic response for 90% of patients. By comparison, an analysis based on positive PD-L1 immunohistochemistry results or high mutational burden status alone correctly predicted response in only 30% of cases.
“Our results show that this two-pronged algorithm — expression analysis for the 54-gene signature we identified, on top of mutational burden — may prove to be a highly accurate tool for predicting treatment response,” notes Dr. Morrison. “We’re excited by these striking findings and look forward to validating our results in a larger study.”
The poster, “Algorithmic prediction of response to checkpoint inhibitors,” is ASCO 2017 abstract 11565 and will be presented Saturday, June 3, from 1:15 p.m. to 4:45 p.m. CDT in McCormick Place, Hall A, as part of the Tumor Biology session.
The poster will be presented by Shipra Gandhi, a Clinical Fellow in the Department of Medicine at Roswell Park.
The mission of Roswell Park Comprehensive Cancer Center is to understand, prevent and cure cancer. Founded in 1898, Roswell Park is one of the first cancer centers in the country to be named a National Cancer Institute-designated comprehensive cancer center and remains the only facility with this designation in Upstate New York. The Institute is a member of the prestigious National Comprehensive Cancer Network, an alliance of the nation’s leading cancer centers; maintains affiliate sites; and is a partner in national and international collaborative programs. For more information, visit www.roswellpark.org, call 1-877-ASK-Roswell Park (1-866-559-4838) or email AskRoswell@Roswellpark.org. Follow Roswell Park on Facebook and Twitter.
Annie Deck-Miller, Senior Media Relations Manager