Treatment outcomes prediction methods in immunotherapy: Scientists reveal key factors
Every year, scientists develop innovative treatments to combat cancer, one of the newest being immunotherapy. However, this treatment does not work for every individual or cancer type, leading researchers to seek answers concerning why some tumors respond to immunotherapy.
Recently, scientists from Johns Hopkins University identified a specific subset of mutations in cancer tumors that pointed to the tumor's potential responsiveness to immunotherapy. These persistent mutations, as they have been coined, remain in cancer cells and keep the tumor visible to the immune system, thus enhancing the effectiveness of immunotherapy.
Doctors have been using the total number of mutations in a tumor, known as tumor mutation burden, to try and predict how well a tumor will react to immunotherapy. However, this study suggests that examining persistent mutations might provide a more accurate way to identify tumors that are more likely to respond to immunotherapy.
The researchers believe their findings will enable doctors to more accurately select patients for immunotherapy and better predict outcomes from the treatment. Their work was published in the journal Nature Medicine.
Immunotherapy works by using the body's immune system to fight the disease. Normally, cancer cells develop mutations that allow them to evade the immune system. Immunotherapy boosts the immune system, making it easier for it to find and destroy cancer cells.
Immunotherapy is currently a treatment option for breast cancer, melanoma, leukemia, and non-small cell lung cancer. Researchers are exploring its potential as a treatment for other types of cancer, including prostate, brain, and ovarian cancer.
According to the study, persistent mutations might be determined by mutations in DNA repair genes, such as MSH2, MLH1, and ATM. A high mutational burden and the presence of tumor-specific antigens can also increase a tumor's susceptibility to immunotherapy. These mutations contribute to a tumor microenvironment that is more conducive to immune recognition and activation, enhancing the likelihood of a positive response to immunotherapeutic interventions.
In an interview with Medical News Today, Dr. Kim Margolin, a medical oncologist, highlighted the significance of this research, stating that the study goes beyond the simple concept of tumor mutation burden and defines persistent mutations in a new light. She suggests that persistent mutations and mutation-associated neo-antigens are likely the most important determinants of an effective anticancer immune response, which is stimulated and amplified by immunotherapeutic agents.
Margolin also believes that in the near future, high-throughput, next-generation sequencing techniques will be employed to study patients' mutational spectrum, thus potentially enabling doctors to categorize patients by their likelihood of response to immunotherapy or their likelihood of benefit from other treatments. This could pave the way for personalized medicine in cancer treatment.
- The scientists from Johns Hopkins University have identified a specific subset of mutations in cancer tumors, called persistent mutations, which may indicate the tumor's potential responsiveness to immunotherapy.
- The researchers believe that examining persistent mutations might provide a more accurate way to identify tumors that are more likely to respond to immunotherapy, enabling doctors to more accurately select patients for the treatment.
- According to the study, persistent mutations may be determined by mutations in DNA repair genes such as MSH2, MLH1, and ATM, and a high mutational burden and the presence of tumor-specific antigens can also increase a tumor's susceptibility to immunotherapy.
- In the future, high-throughput, next-generation sequencing techniques may be employed to study patients' mutational spectrum, potentially enabling doctors to categorize patients by their likelihood of response to immunotherapy or their likelihood of benefit from other treatments, paving the way for personalized medicine in cancer treatment.
