Predictive Approaches in Immunotherapy: Scientists Discover Methods to Forecast Treatment Results
Every year, scientists are pushing boundaries in the fight against cancer, developing new treatment options. One of the latest contenders is immunotherapy. But not every person or every type of cancer responds well to this treatment. Researchers from Johns Hopkins University in Maryland may have found an answer as to why that is.
They've identified a specific subset of mutations in a cancer tumor that suggests how receptive it will be to immunotherapy. Their study was recently published in the journal Nature Medicine.
Immunotherapy uses the body's immune system to fight the disease. Typically, cancer cells develop mutations, allowing them to hide from the immune system. Immunotherapy offers a boost to the immune system, helping it find and destroy cancer cells.
There are different types of immunotherapy, including checkpoint inhibitors and CAR-T cell therapy. Currently, immunotherapy is being used in treatment for breast cancer, melanoma, leukemia, and non-small cell lung cancer. Researchers are looking at using this treatment for other types of cancer, such as prostate, brain, and ovarian.
Doctors currently use the number of mutations in a tumor, called Tumor Mutational Burden (TMB), to try and figure out how a tumor will respond to immunotherapy. However, some mutations allow cancer cells to remain hidden from the immune system, making it difficult for immunotherapy to work.
In this study, the researchers at Johns Hopkins identified a specific subset of mutations within the overall TMB, which they called "persistent mutations." These mutations remain in the cancer cells and allow the cancer to stay visible to the immune system, making it easier for immunotherapy to work.
Persistent mutations may help doctors more accurately select people for immunotherapy and better predict the outcome from the treatment. In the study, they found that the number of persistent mutations more optimally identifies tumors that are more likely to respond to immune checkpoint blockade compared to the overall tumor mutation burden.
This research is exciting as it may pave the way for the more targeted and effective use of immunotherapy in the future. In the near future, it may be possible to use high-throughput, next-generation sequencing techniques to study a patient's mutational spectrum and categorize them by their likelihood of response to immunotherapy.
This work is still in its early stages, but it hints at a promising future for the use of immunotherapy in cancer treatment. As research continues, we may see more targeted and effective use of immunotherapy in the fight against cancer.
- The scientists at Johns Hopkins University identified a specific subset of mutations in a cancer tumor, which they called "persistent mutations," that could make immunotherapy more effective.
- These persistent mutations remain in cancer cells and keep them visible to the immune system, allowing immunotherapy to work more efficiently.
- The number of persistent mutations may help doctors more accurately select patients for immunotherapy and better predict the outcome of the treatment.
- This research could pave the way for the more targeted and effective use of immunotherapy in the future, potentially leading to higher TMB-specific responses to immune checkpoint blockade.
