Immunotherapy Outcomes Prediction: Scientists Discover Methods to Anticipate Responses
Every year, advancements are made in cancer treatments. One of the latest additions is immunotherapy, which utilizes the body's immune system to combat disease. However, it's crucial to note that not all cancer types or patients respond to immunotherapy. This has led researchers to investigate factors that could predict its effectiveness.
In a recent study published in Nature Medicine, scientists from Johns Hopkins University identified a subset of mutations in cancerous tumors that may indicate a tumor's receptiveness to immunotherapy. These specific mutations, termed "persistent mutations," are less likely to disappear as the cancer evolves, leaving the tumor visible to the immune system.
Doctors currently use the total number of mutations in a cancer cell, known as the tumor mutation burden (TMB), to estimate a tumor's response to immunotherapy. However, these findings suggest that the number and persistence of mutations are more accurate indicators of a tumor's suitability for immunotherapy than the overall TMB.
These persistent mutations are associated with a phenomenon called deficient mismatch repair (dMMR) and microsatellite instability-high (MSI-H), both of which are known to improve a tumor's visibility to the immune system. This, in turn, improves the response to immune checkpoint inhibitors (ICIs) and other immunotherapies.
By accurately identifying patients for immunotherapy and predicting outcomes, this study could help personalize treatment strategies and improve patient outcomes. Further research is needed to confirm these findings and fully understand the role of these persistent mutations in cancer treatment.
Immunotherapy involves boosting the body's immune system to better detect and destroy cancer cells. It is currently a viable treatment option for various types of cancer, including breast cancer, melanoma, leukemia, and non-small cell lung cancer. Researchers are exploring its application in other cancer types, such as prostate, brain, and ovarian cancer.
The study's findings may pave the way for more precise patient selection for immunotherapy and a better understanding of its effectiveness in the near future. High-throughput sequencing techniques may eventually enable doctors to categorize patients by their likelihood of response to immunotherapy, ultimately improving treatment outcomes.
- Scientists, in a recent study published in Nature Medicine, have discovered persistent mutations in cancerous tumors that could indicate a tumor's receptiveness to immunotherapy.
- These persistent mutations, such as deficient mismatch repair (dMMR) and microsatellite instability-high (MSI-H), make the tumor more visible to the immune system, thereby improving the response to immune checkpoint inhibitors (ICIs) and other immunotherapies.
- The accurate identification of patients for immunotherapy based on persistent mutations could help personalize treatment strategies, ultimately improving patient outcomes and enabling doctors to categorize patients by their likelihood of response to immunotherapy in the future.
