The development of immune checkpoint inhibitors (ICI), a type of cancer therapy that helps a patient’s own immune system fight cancer tumours has widely been considered one of the most significant achievements in cancer treatment in the last decade. While this treatment has been successful across many cancer types, there continues to be patients whose cancer does not respond well to the treatment.
A study published in Clinical Cancer Research
aims to shed light on why some patients respond better than others. Co-led by BC Cancer medical oncologist Dr. Janessa Laskin and Dr. Marco Marra’s team at Canada’s Michael Smith Genome Sciences Centre at BC Cancer, researchers are examining how they can better predict the patients who will be successful on ICI therapy before they start treatment.
“ICI therapy has become part of the treatment strategy for many cancer types and in all stages of cancer. Our data suggests that using more information, particularly from the cancer genome, might help predict which patients will be more sensitive to ICI therapy before they start,” says Dr. Laskin.
Knowing who may be successful and who may not before starting treatment is incredibly important. ICI therapy can have severe side-effects. Developing a method for predicting which patients will have achieve results with ICI treatment can help reduce the number of patients who receive the treatment without benefit.
In their study, researchers analyzed the genetic data of 98 patients enrolled in the Personalized OncoGenomics (POG) program
at BC Cancer. The patient data covered a wide range of cancer types, biopsy sites and treatment histories. The patients had either received ICI therapy prior to biopsy or received it after the biopsy. The latter were the primary focus of the study, which aimed to identify cellular signals, known as biomarkers, which could predict how the cells would respond to ICIs.
BC Cancer medical oncologist Dr. Janessa Laskin
The researchers successfully identified multiple biomarkers of ICI response. Tumour mutation burden—which represents the number of mutations in one million bases of tumour DNA sequence—was the strongest predictor of the length of time a patient remained on the therapy before their cancer progressed. The number of different types of immune cells was a better predictor of overall patient survival. The researchers found that combining multiple biomarkers provided the best predictive power, demonstrating that a holistic approach to evaluating cellular responses rather than testing biomarkers in isolation leads to a more accurate prediction of ICI response.
A phase II clinical trial is now underway to actively test the efficacy of the biomarkers. “In the next few years, we will use this holistic approach to select patients from the POG program to receive treatment with the ICI as part of the phase II trial. The outcome of this study could have a profound impact on how to choose cancer treatments,” says Laskin.