Immunotherapy Outcome Predictions: Scientists Discover Strategies for Prognostication
Every year, scientists are developing innovative treatment options to combat cancer, and one such groundbreaking approach is immunotherapy. However, it's crucial to note that this treatment does not work for every individual or cancer type. Researchers at Johns Hopkins University have made a significant breakthrough in identifying a specific group of cancer tumor mutations that can indicate a tumor's receptiveness to immunotherapy.
These experts have discovered that a specific subset of mutations within a cancer tumor, which they call "persistent mutations," can help determine a tumor's response to immunotherapy. These mutations are less likely to disappear as the cancer evolves, keeping the tumor visible to the immune system. This increases the likelihood of a successful response to immunotherapy, thereby improving the chances of long-term survival.
The researchers believe that their findings will help medical professionals more accurately select patients for immunotherapy and predict the treatment's outcome. Their study, recently published in the journal Nature Medicine, could potentially revolutionize the way cancer treatment decisions are made.
Immunotherapy works by boosting the body's immune system, allowing it to more easily detect and destroy cancer cells. There are several types of immunotherapy, including checkpoint inhibitors, CAR T-cell therapies, and cancer vaccines. Currently, immunotherapy is a recommended treatment for certain cancer types, such as breast cancer, melanoma, leukemia, and non-small cell lung cancer. Researchers are also exploring its potential benefits for other types of cancer, like prostate, brain, and ovarian cancer.
Prior to this study, doctors had mainly relied on the total number of mutations in a tumor – called the tumor mutation burden (TMB) – to help determine a tumor's reactiveness to immunotherapy. However, using persistent mutations as a marker may provide more accurate predictions and better prognostic values.
According to Dr. Valsamo Anagnostou, a senior author of the study and an associate professor of oncology at Johns Hopkins, the number of persistent mutations more optimally identifies tumors that are more likely to respond to immune checkpoint blockade compared to the overall TMB. This could help clinicians more accurately select patients for clinical trials of novel immunotherapies or predict a patient's clinical outcome with standard-of-care immune checkpoint blockade.
When asked about the study's implications for cancer patients, Dr. Kim Margolin, a medical oncologist and medical director of the Saint John's Cancer Institute Melanoma Program at Providence Saint John's Health Center in California, noted that it demonstrated significant advancements in the understanding of persistent mutations' role in immune responses to cancer. She expects that, in the near future, high-throughput, next-generation sequencing techniques will be used to study patients' mutational spectrum, potentially helping to categorize patients by their likelihood of response to immunotherapy.
- The study published in the journal Nature Medicine has suggested that the number of persistent mutations in a cancer tumor could be a more accurate marker for determining a tumor's response to immunotherapy, as compared to the traditional tumor mutation burden (TMB) method.
- In the future, high-throughput, next-generation sequencing techniques might be employed to study patients' mutational spectrum, potentially enabling clinicians to categorize patients based on their likelihood of response to immunotherapy.
- This research at Johns Hopkins University could potentially revolutionize the way cancer treatment decisions are made, as it offers a more precise approach for selecting patients for immunotherapy and predicting the treatment's outcome, improving the chances of long-term survival for certain medical-conditions like cancer.
