Immunotherapy Outcomes Prediction: Scientists Disclose Strategies for Anticipating Treatment Success
Each year, scientists delve into developing novel methods to combat cancer, and one of the latest treatment options is immunotherapy. While promising, immunotherapy does not work for everyone or all types of cancer. Researchers at Johns Hopkins University in Maryland have identified a specific subset of mutations in cancer tumors that may indicate whether a tumor will be responsive to immunotherapy treatment.
The researchers believe their findings will help doctors more accurately select patients for immunotherapy and better predict treatment outcomes. Their study was recently published in the journal Nature Medicine.
Immunotherapy utilizes the body's immune system to fight off disease. When cancer cells develop mutations, they often evade detection by the immune system. Immunotherapy provides a boost to the immune system to help it find and destroy cancer cells more effectively.
Immunotherapy is currently a treatment option for breast cancer, melanoma, leukemia, and non-small cell lung cancer. Researchers are exploring using immunotherapy for other types of cancer, including prostate, brain, and ovarian.
Previously, doctors used the total number of mutations in a tumor, called tumor mutation burden (TMB), to try and determine how the tumor would respond to immunotherapy. However, the researchers in this study identified a specific subset of mutations within the overall TMB, which they called "persistent mutations." These persistent mutations allow the cancer tumor to remain visible to the immune system, improving the response to immunotherapy treatment.
"Persistent mutations are always present in cancer cells and these mutations may render the cancer cells continuously visible to the immune system," said Dr. Valsamo Anagnostou, a senior author of the study and an associate professor of oncology at Johns Hopkins. "This response is amplified in the context of immune checkpoint blockade, and the immune system continues to eliminate cancer cells harboring these persistent mutations over time, resulting in sustained immunologic tumor control and long survival."
These findings may help doctors more accurately select patients for immunotherapy and predict treatment outcomes. In the future, it may be possible to use high-throughput, next-generation sequencing techniques to study patients' mutational spectrum and categorize them by their likelihood of response to immunotherapy.
Certain mutations and genomic alterations are particularly relevant for immunotherapy response, such as mismatch repair gene mutations, ATM mutations, FGFR pathway alterations, and biomarkers for immunogenic cell death. These mutations result in a high neoantigen load, which is strongly associated with better immunogenicity and increased responsiveness to immune checkpoint inhibitors.
However, tumors with low neoantigen availability or loss of heterozygosity in HLA genes are more likely to be resistant to immunotherapy. Overall, persistent mutations in DNA repair genes, such as MSH2, MLH1, PMS2, and MSH6, are the most reliable indicators of likely immunotherapy response.
- The study published in Nature Medicine by researchers at Johns Hopkins University reveals a specific set of persistent mutations in cancer tumors could indicate responsiveness to immunotherapy treatment, potentially aiding doctors in patient selection and outcome prediction.
2.Immunotherapy treatment may become more effective for various types of cancer, such as prostate, brain, and ovarian, as scientists explore its application beyond breast cancer, melanoma, leukemia, and non-small cell lung cancer.
3.Mismatch repair gene mutations, ATM mutations, FGFR pathway alterations, and biomarkers for immunogenic cell death are examples of relevant mutations for immunotherapy response, leading to a high neoantigen load and increased responsiveness to immune checkpoint inhibitors, whereas tumors with low neoantigen availability or loss of heterozygosity in HLA genes tend to be resistant to immunotherapy.
