Identification of biomarkers to guide the duration of immunotherapy treatment for melanoma patients

Melanoma is the deadliest form of skin cancer, and prior to 2010, outcomes were extremely poor for most patients with metastatic melanoma, where their cancer had spread to other parts of their body. Encouragingly, a class of treatments called immune checkpoint inhibitors (ICIs) dramatically improved survival for some patients, even leading to cures in some cases. However, some patients do not respond to ICI therapy and others experience severe side-effects. Researchers do not fully understand why some patients respond while others do not and they cannot accurately predict who will respond, which is necessary to most effectively provide this expensive and sometimes toxic therapy to those most likely to benefit. 

Standard-of-care ICI treatment for patients with metastatic melanoma is two years. Although clinical trials have shown that this duration improves patient survival, the two-year period was arbitrarily selected in early trials. Since subsequent trials did not test different treatment durations, it remains unclear whether two years is the optimal length of therapy. 

To address this question, the Canadian Cancer Trials Group (CCTG) initiated a phase III clinical trial called ME13 STOP-GAP. The main study aims to determine whether patients with metastatic melanoma have the same survival, better quality of life and fewer side effects if given treatment on an intermittent schedule (where treatment breaks are administered once the melanoma reaches maximum shrinkage until growth is detected again) compared to those given continuous treatment for two years. The trial is co-chaired by Dr. Tara Baetz (Kingston Health Sciences Centre) and Dr. Xinni Song (Ottawa Hospital Cancer Centre) and supported by funding from the Canadian Cancer Society. 

To build on this innovative trial, the Marathon of Hope Cancer Centres Network (MOHCCN) is funding a sub-study that will see the collection and testing of blood and melanoma samples from patients participating in the main trial. The team of scientists performing this sub-study is led by Dr. Ian Watson, an investigator at McGill University’s Rosalind and Morris Goodman Cancer Institute (GCI) and the Research Institute of the McGill University Health Centre (RI-MUHC), Dr. Janet Dancey, Director of the CCTG, and Drs. Baetz and Song and includes researchers from institutions across Québec, Ontario, and British Columbia. 

The team will use MOHCCN funding to generate whole-genome and transcriptome sequencing (WGTS) data and collect detailed clinical information, such as diagnosis, treatment and response details, from each patient. This data will be contributed to the MOHCCN Gold Cohort, which is on track to become Canada’s largest and most complete cancer case resource and which will help facilitate advancements in precision oncology. The sub-study also received funding from the Canadian Institutes of Health Research (CIHR) funding to generate additional data types, such as epigenetic profiling and characterization of immune cell populations in tumour and blood samples. 

“In this project,” says Dr. Watson, “we will bring together scientific experts using cutting-edge technologies with the goal of identifying markers found in blood or melanoma samples from patients. The discovery of these markers may lead to clinical tests to predict whether a patient will respond to ICI treatment or have a side effect or to identify patients that are able to stop treatment. This would have important implications in improving outcomes and reducing duration of therapy to help limit side effects and reduce costs to healthcare systems.” 

This project highlights the strengths and advantages of pan-Canadian collaborative efforts and patient-centred clinical trials. “Trials that test optimal treatment doses, schedules or duration are most often led by academic cooperatives,” explains Dr. Dancey. “Partnerships such as this one between the MOHCCN and the CCTG are incredibly important to improve precision medicine by identifying markers that predict treatment response. These markers can be used to personalize each patient’s treatment approach, potentially leading to shorter treatment durations, less toxicity and increased quality of life without affecting survival, thus providing time and experiences that patients value and improving their cancer care journeys.”