A team of investigators led by researchers at Georgetown Lombardi Comprehensive Cancer Center has found that the tumor mutation load (TML) in a patient’s cancer biopsy varied by age and the type of cancer, along with several other factors. The findings include 14 types of solid tumors and over 8,000 tissue samples, offering one of the most comprehensive analyses of TML to date.
TML is a measurement of the number of mutations in DNA. Mutated DNA can be subsequently translated to harmful changes in proteins. Mutated proteins often appear foreign to the immune system and can therefore activate a robust immune response that can be boosted by immunotherapeutic agents.
“One of our more interesting findings was the fact that mutation load increased with age in many cancers,” says the study’s principal investigator, Mohamed E. Salem, MD, a former assistant professor of medicine at Georgetown Lombardi. “Older age correlated closely with TML in most of the cancers we examined, but in some cancers, such as bladder cancer, there was no correlation by age, which also makes for an important observation in a difficult-to-treat type of cancer.”
Salem is interested in quantifying a cell’s TML because if it is high, then immunotherapy could be an effective cancer treatment. Immunotherapies work by “taking the brakes off ” the immune system, allowing immune-fighting cells to go after cancer cells. A cancer cell with more mutations may make it appear more alien to the immune-fighting cells, and therefore a more attractive object to attack. Tumor mutation load also could be used as a marker to determine which types of cancer and which patients could most benefit from immunotherapy.
“We found that, as expected, melanoma had the highest TML, as we know clinically that this type of cancer responds best to immunotherapy,” says Salem. “Indeed, the mean TML for melanoma was nearly double that of the next highest mean, non-small cell lung cancer. In addition, we see that high TML often occurs in tumors lacking well-known cancer-related genes, like BRAF or NRAS genes in melanoma and EGFR or ALK genes in non-small cell lung cancer. This suggests that immune checkpoint inhibitors may be particularly effective in patients who are not candidates for common targeted therapies in these types of cancer,” he adds.
“The next step is to validate and correlate TML levels with outcomes in patients who have received immunotherapy. We’ll look to see if patients had high TML levels before they started therapy and then determine if those with the highest levels had the best clinical outcome, which is what we might expect. If validation studies prove helpful, they could be very useful in designing clinical trials for many types of cancer,” Salem concludes.
