Developing multi-modal biomarkers to predict response to specific immunotherapies

In recent years, immunotherapies have emerged as a promising class of cancer drugs that harnesses the power of the immune system to fight cancer. But despite their life-saving potential, their effectiveness is limited: only 20 to 30 per cent of people with cancer benefit from them and some experience severe side effects without any therapeutic benefit.

In this context, being able to predict who will benefit from a specific immunotherapy and who won’t is a crucial step towards personalizing cancer treatments in ways that improve survival and quality of life for cancer patients. 

The "Canadian framework to improve predictive models for immunotherapy interventions (CAN-PREDICT-IT)," is a new project led by clinician-scientists from British Columbia, Ontario and Quebec. Funded through the Network’s Pan-Canadian Project Program, this initiative seeks to collect and analyze multiple data points from cancer patients, including clinical and genomic data, to search for biomarkers that could help predict what patients are more likely to benefit from specific immunotherapy treatments.

“By leveraging the power of our collaborators throughout the Network we will be able to collect a large amount of data from patients, including whole genome and transcriptome sequencing, multiplexed immunohistochemistry (IHC), radiological imaging and high-quality well-annotated clinical data,” says Dr. Philippe Bedard, a clinician-investigator at the Princess Margaret Cancer Centre in Toronto, who co-leads of the team. “This massive data set will allow us to use tools like artificial intelligence to identify biomarkers that could indicate which patients are most likely to benefit from specific immunotherapies.”

The Canadian Cancer Trials Group (CCTG) is one of the main partners in this project is an academic cooperative oncology group that designs and conducts clinical trials testing cancer therapy, supportive care and prevention interventions. By collaborating with CCTG and its portfolio of clinical trials, researchers will be able to recruit patients to the project from CCTG trials, and importantly, will also be able to use the results from the study to eventually match patients to specific clinical trials of a treatment that may benefit them.

“We are excited about this partnership and the doors it opens to increase access for patients to receive clinical-laboratory quality genomic and transcriptomic sequencing and reports that may be used in making treatment decisions,” says Dr. Janet Dancey, CCTG Director. “We are also excited to use the knowledge created through this initiative as it may lead to patients being offered clinical trials testing potentially life-prolonging immunotherapies from which they are more likely to benefit .”

In addition to furthering the team’s research aims, all data collected through this study will also be part of the MOHCCN Gold Cohort. This resource, which seeks to be the largest and most complete cancer case resource in Canada, will be used by researchers across the country, now and into the future, to continue making discoveries to improve precision medicine for cancer in Canada and beyond.

Project title: Canadian framework to improve predictive models for immunotherapy interventions (CAN-PREDICT-IT) 

Principal Investigators:

• Philippe Bedard (Princess Margaret Cancer Centre) - lead
• Janessa Laskin (BC Cancer)
• Janet Dancey (Canadian Cancer Trials Group)
• George Zogopoulos (Research Institute of the McGill University Health Centre)