Tumor mutation measurement may help predict treatment success

Motivated by the potential of immunotherapy, doctors and researchers are exploring new ways to better forecast when they may be a viable treatment for more cancers and show better outcomes in a larger percentage of patients.

Since the U.S. Food and Drug Administration (FDA) approved the first checkpoint inhibitor drug ipilimumab (Yervoy®) in 2011 to treat melanoma, these immunotherapies have benefited patients with an increasing variety of cancers. Motivated by the drugs’ potential, doctors and researchers are exploring new ways to better forecast when they may be a viable treatment for more cancers and show better outcomes in a larger percentage of patients. One of these measuring sticks is what researchers call tumor mutation burden (TMB), which is based on the number of DNA mutations found inside a tumor. Scientists are researching ways to measure TMB as a potential prognosticator to a cancer’s response to checkpoint inhibitors. “Tumor mutation burden is a good way to identify tumors that may respond to immunotherapy in a way that allows the immune system to work against cancer,” says Ashish Sangal, MD a Medical Oncologist at our Phoenix hospital.

Cancer develops when the DNA inside cells changes or mutates, preventing cells from working properly. In many cases, these mutations may allow defective cells to multiply and grow, forming a tumors. Scientists believe the more mutations a tumor has, or the higher its TMB, the more likely one or more of those mutations will respond to immunotherapy. 

“ The more mutations, the better the response may be. So, the higher the number of mutations, the better the chances of having a benefit from using immunotherapy,” says Ashish Sangal, MD, Medical Oncologist Immunotherapy drugs are designed to disrupt the signals that allow cancer cells to hide from the immune system. Cancer cells send deceptive signals to protein receptors, located on the immune cells’ surface, as they pass the so-called immune checkpoints. If not for these checkpoints, the immune system may attack healthy cells. Two primary benchmarks are used to determine if a checkpoint inhibitor may work on a given cancer:

  • PD L1 is a receptor often found on cancer cells that binds with the PD-1 receptor on immune cells. When the two receptors touch, the cancer cell may send a signal that tells the immune cell it is not a threat, prompting the immune cell to let it go and move on to look for other threats. Checkpoint inhibitors disrupt that signal, allowing the immune cells to better recognize and attack the cancer cells.
  • Microsatellite instability (MSI) is a gene mutation that makes it difficult for the DNA in a cell to repair itself, which may lead to the type of unchecked cell growth that causes many tumors to form and grow. Research has shown that tumors with high MSI may respond better to checkpoint inhibitors. The FDA last year took the breakthrough step of approving the cancer drug pembrolizumab (Keytruda®) to treat cancers with high MSI. It was the first approval of a cancer therapy based not on the tumor's primary location in the body but on a specific genetic feature found in the cancer’s DNA.

So, if doctors already have two ways to measure checkpoint inhibitors’ potential, why do they need another? Researchers theorize that some cancers that are not currently being treated with checkpoint inhibitors may have high TMB. Also, activated immune cells don’t always know what to attack. An immune response is triggered when immune cells detect molecules called antigens. Researchers suspect that cancer cells in tumors with high TMB may have more neoantigens—receptors found on cancer cells that may attract immune cells.

Researchers are conducting multiple clinical trials to determine how TMB may be used to forecast the effectiveness of checkpoint inhibitors and other cancer treatments. Scientists are also working to develop reliable ways of testing the number of mutations found in a cancer and what qualifies as high TMB vs. low TMB. “Moving forward,” Dr. Sangal says, “we are definitely coming to a point where these three things—PD-L1, MSI and tumor mutation burden—will be used to help determine how to use immunotherapies and which cancers may respond or not respond.”