Measuring tumor mutation may predict treatment success

Measuring tumor mutation may predict treatment success

Since the US Food and Drug Administration (FDA) approved the first checkpoint inhibitor, ipilimumab (Yervoy) ®) in 2011 for the treatment of skin cancer, these immunotherapies have benefited patients with an increasing variety of cancers. Motivated by the potential of drugs, clinicians and researchers are exploring new ways to better predict when a treatment might be viable for more cancers and to show better outcomes in a higher percentage of patients. One such measure is what researchers call tumor mutation burden (TMB), which is based on the number of DNA mutations present within the tumor. Scientists are investigating ways to measure basal metabolic rate as a potential indicator of cancer 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 act against cancer,” says Ashish Sangal, MD, a medical oncologist at Phoenix Hospital.

Cancer develops when the DNA inside cells changes or mutates, preventing the cells from working properly. In many cases, these mutations can allow the defective cells to multiply and grow, forming tumors. Scientists believe that the higher the number of mutations in a tumor, or the higher the basal metabolic rate, the more likely one or more of these mutations will respond to immunotherapy.

“The more mutations, the better the answer. Therefore, the higher the number of mutations, the higher the chances of benefiting from the use of immunotherapy,” says Ashish Sangal, medical oncologist. Immunotherapy drugs are designed to interrupt the signals that allow cancer cells to spread. Hiding from the immune system. Cancer cells send tricky signals to protein receptors on the surface of immune cells, where they pass through what are called immune checkpoints. If not for these checkpoints, the immune system could attack healthy cells. Two main criteria are used to determine if a checkpoint inhibitor can work in a particular cancer:

  • PD L1 is a receptor often found in cancer cells that binds to the PD-1 receptor in immune cells. When the two receptors come into contact, the cancer cell can send a signal telling the immune cell that it is not a threat, causing the immune cell to leave and look for other threats. Checkpoint inhibitors interrupt this signal, allowing immune cells to better recognize and attack cancer cells.
  • Microsatellite instability (MSI) is a genetic mutation that makes it difficult for a cell’s DNA to repair itself, which can lead to the type of uncontrolled cell growth that causes many tumors to form and grow. Research has shown that tumors with a high MSI may respond better to checkpoint inhibitors. Last year, the US Food and Drug Administration (FDA) took the crucial step by approving the cancer drug pembrolizumab (Keytruda). ® ) for the treatment of cancers with a high content of MSI. The first approval of a treatment for cancer was based not on the primary location of the tumor in the body, but on a specific genetic feature found in the cancer’s DNA.

So if clinicians already have two ways to measure the potential of a checkpoint inhibitor, why would they need another? Researchers believe that some cancers that are not currently treated with checkpoint inhibitors may have an elevated BMR. Also, activated immune cells do not always know what to attack. The immune response is triggered when immune cells detect molecules called antigens. Researchers believe that cancer cells in tumors with a high basal metabolic rate may contain more new antigens, the receptors on cancer cells that can attract immune cells.

Researchers are conducting multiple clinical trials to determine how TMB can be used to predict the effectiveness of checkpoint inhibitors and other cancer treatments. Scientists are also working to develop reliable ways to test how many mutations there are in cancer and what might be considered elevated versus BMR. “Going forward, we’re definitely getting to a point where these three things (PD-L1, MSI, tumor mutation load) will be used to help determine how to use immunotherapies and what types of cancers can answer or not,” says Dr. Sangal.

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