Antigen presentation and tumor immunogenicity in cancer immunotherapy response prediction

In the last decade a new kind of cancer therapy, called immunotherapy, has changed how doctors treat cancer patients. These therapies mean that previously incurable cancers, including some skin and lung cancers, can now sometimes be cured. Immunotherapy does this by activating the patient’s own immune system so that it will attack the cancer cells. But for this to work, the cancer cells, much like invading bacteria or viruses, need to be recognized as foreign. Cancer cells contain many DNA mutations that cause the cell to make mutated proteins it would not normally make. These proteins betray the cancer cells as foreign to the immune system. The extent to which cancer cells make mutated proteins – also called the ‘tumor mutational burden’ – can sometimes predict whether a patient will respond to immunotherapy. In general, patients with a high mutational burden respond well to immunotherapy, but overall fewer than one in five cancer patients are cured by this treatment. An important question is whether there are better ways of predicting if a cancer patient will respond to immunotherapy. Wang et al. have addressed this problem by adding a second variable to the prediction. Not only do cancer cells have to make mutated proteins, but these proteins also have to be ‘seen’ by immune cells. Cancer cells, like normal cells, have mechanisms to present protein fragments to immune cells. Wang et al. hypothesized that patients with a high mutational burden would not respond to immunotherapy if they were lacking the machinery required for presenting protein fragments. The experiments revealed that measuring both tumor mutational burden and the levels of the machinery that presents protein fragments resulted in better predictions of patients’ responses to immunotherapy than measuring tumor mutational burden alone. Additionally, this new way of predicting responses to immunotherapy was successful across many different cancer types. The combined measurement of these two variables could be applied in clinical practice as a way to predict cancer patients’ response to immunotherapy. This should allow doctors to determine which course of treatment will work best for a specific patient. The results also suggest that inducing tumor cells to produce more of the machinery that presents protein fragments to the immune system could increase their responsiveness to immunotherapy. In the future, predicting how well a patient will respond to immunotherapy could become even more accurate by incorporating additional variables.