Study Shows Better Immunotherapy Outcomes in Tumors with More Mutations
A recent study published in Nature Genetics called “Tumor mutational load predicts survival after immunotherapy across multiple cancer types” revealed that tumors with more mutations had better results with immunotherapy treatment.
The study looked at data from 1,662 metastatic cancer patients who received checkpoint inhibitor therapy, and data from over 5,000 patients who were not treated with the therapy. Immune checkpoint inhibitors work by getting the body’s immune system to recognize cancerous cells as foreign so that it can attack them. Many of these therapies are being used regularly for non-small cell lung cancers, melanomas, renal cell cancers, bladder cancer, and head and neck squamous cell cancers. The drugs include Tecentriq (atezolizumab), Bavencio (avelumab), Imfinzi (durvalumab), Yervoy (ipilimumab), Opvido (nivolumab), and Keytruda (pembrolizumab).
The study showed that patients receiving checkpoint inhibitor therapy with the highest number of tumor mutations — also called tumor mutational burden (TMB) — experienced better overall survival compared to those with lower tumor mutations. The survival increase was not shown in patients with high TMB who did not receive checkpoint inhibitor therapy. This suggests that high TMB responds better to immunotherapy.
These results make sense in terms of how the immune system functions. It’s job is to determine which cells aren’t behaving correctly, such as malignant cells, and destroy them. Unfortunately, tumor cells usually find ways to evade this system. So the more mutations a tumor cell has, the easier it might be for the immune system to identify them as different than normal cells. Theoretically, this would allow them to be more eliminated, especially with the introduction of immunotherapy treatments.
Many patients have excellent results with immunotherapy, but sometimes, it can cause damage to the lungs and kidney. Researchers have thus been spending a lot of time figuring out how they can predict patient response. Although this study helps to give some more insight as to which patients have better responses, it still poses some challenges that need to be further examined. Specifically, it’s difficult to decide what exactly defines “high” TMB. This is because every cancer behaves differently. The distinction between “high” and “low” TMB was very different among cancer types.
Researchers will have to come up with some kind of cutoff for different types of tumors. But its also challenging to determine TMB in clinical settings. New technologies allow for either entire tumor genome sequencing or part of it. The different available methods oftentimes produce varying results. Scientists will have to conduct a lot more research before they can clearly predict the efficacy of different therapies for different patients, especially with immunotherapies.