Immunotherapy cancer treatments that focus on the cell programmed death (PD) pathway and ligands (L) have given oncologists new options for standard-of-care therapies in many patients. However, figuring out which patients might respond to these treatments is quite difficult, and using the PD-L1 biomarker has shown to have many limitations. For instance, results can vary depending on where tumor tissue is located. Researchers are thus dedicating their resources to find additional biomarkers that will help them to figure out who are the best candidates for immune checkpoint inhibitors.
Jarushka Naidoo, a medical oncologist at the Kimmel Comprehensive Cancer Center, Johns Hopkins University in Baltimore, is one of those researchers. At the recent annual meeting of the National Comprehensive Cancer Network, Naidoo showed results that included at least 10 possible biomarkers. She described the field as a “very crowded space.”
But even though researchers have discovered a large amount of biomarkers, only PD-L1 is currently being studied. This is because the testing process for biomarker testing is quite complicated. The NCCN guidelines for biomarker testing are a “rapidly evolving space,” said Naidoo.
The three broad categories currently used in immunotherapy. The first category reveals whether the tumor is inflamed, like OD-L1. The second show how immunogenic the tumor is, or how likely it is to create an immune response. This is called tumor mutational burden (TMB). The third shows features of the “host environment” which is the most recent of the three categories. This might include elements outside of the tumor, like the gut microbiome, which could predict whether a patient will respond to immunotherapy.
Naidoo said that TMB has been the most clinically developed, but it is still not in full use. “TMB is where PD-L1 was a couple of years ago in terms of the need to harmonize the different methods, the different cut-off values,” she said. “There is still work to be done in TMB.”
Her presentation also included 10 other biomarkers that are currently being studied, and she suggested that the future of biomarkers will likely be in the form of combinations. In other words, researchers will begin to study which biomarkers work well together. The ongoing studies will require a lot of funds to keep going, as the technology required to test them is advanced and expensive. But Naidoo ended her presentation on a positive note by stating that the more the biomarkers are tested, the less expensive the testing will become.