Predictive Analysis in Immunotherapy: Scientists Discover Methods to Anticipate Treatment Results
In the fight against cancer, immunotherapy has risen as a promising treatment method. However, not every person or cancer type responds positively to this treatment. To address this challenge, researchers from Johns Hopkins University, Maryland, have identified a specific subset of tumor mutations that may predict a tumor's responsiveness to immunotherapy.
According to their findings, published in the journal Nature Medicine, a large number of mutations in cancer cells—known as tumor mutational burden (TMB)—may help the immune system identify and attack the tumor. Yet, not all these mutations contribute equally to the immune response.
The scientists have focused on persistently present mutations—referred to as "persistent mutations"—which do not vanish as the cancer evolves. These mutations keep the tumor visible to the immune system, making it more probable that the immune system will react effectively to immunotherapy.
"Persistent mutations are always there in cancer cells and these mutations may render the cancer cells continuously visible to the immune system," explains Dr. Valsamo Anagnostou, a senior author of the study and an associate professor of oncology at Johns Hopkins. "This persistence of mutations leads to the creation of neoantigens, and an ongoing immune response against the tumor. This response is further augmented in the context of immune checkpoint blockade, enabling the immune system to eliminate cancer cells harboring these persistent mutations over time, resulting in sustained immunologic tumor control and long survival."
The study's results indicate that "persistent mutation load" may help doctors more accurately select cancer patients for clinical trials of novel immunotherapies or predict outcomes from current standard-of-care immune checkpoint blockade.
Cancer genomics studies indicate that not all genetic mutations within a cancer tumor are equally helpful in predicting a response to immunotherapy. Instead, it's essential to focus on specific subsets of mutations that produce immunogenic neoantigens, rather than the total mutation count. Other factors—such as microsatellite instability (MSI) and certain cancer lineage-dependent co-mutation patterns—further refine the predictive accuracy of these specific mutations.
The researchers believe that their findings will help doctors make more precise predictions regarding a patient's response to immunotherapy, leading to better outcomes for those with a higher likelihood of success.
Reporting by [Your Name] for Medical News Today
- The science behind immunotherapy in the fight against cancer is advancing, with researchers focusing on persistent mutations that make cancer cells visibly targetable.
- Dr. Valsamo Anagnostou, a Johns Hopkins University associate professor, explains that these persistent mutations lead to the creation of neoantigens, inducing an ongoing immune response against the tumor.
- The findings suggest that the 'persistent mutation load' could assist doctors in more accurately selecting cancer patients for immunotherapy trials or predicting outcomes from current immune checkpoint blockade treatments.
