Researchers Discover Strategies to Forecast Immunotherapy Success
Every year, scientists develop innovative treatment options to combat cancer. One of the latest options is immunotherapy, which leverages the body's immune system to fight the disease. However, it's not a magic bullet for everyone or every type of cancer, leaving researchers on a perpetual hunt for answers.
Recently, researchers from Johns Hopkins University in Maryland have identified a subgroup of cancer tumor mutations that seem to indicate how receptive a tumor might be to immunotherapy. These findings could help doctors more accurately select patients for the treatment and potentially predict outcomes. Their research has been published in the journal Nature Medicine.
What's immunotherapy all about?
Simply put, immunotherapy harnesses the body's immune system to destroy cancer cells. Cancer cells often develop mutations, allowing them to go unnoticed by the immune system. However, immunotherapy provides a boost, making it easier for the immune system to find and squash the cancer cells.
There are several types of immunotherapy, including immune checkpoint inhibitors, adoptive T-cell therapy, and cancer vaccines.
Currently, immunotherapy is a treatment option for breast cancer, melanoma, leukemia, and non-small cell lung cancer. Researchers are also exploring its potential in treating other types of cancer, such as prostate cancer, brain cancer, and ovarian cancer.
Mutation research
Previously, doctors have used the total number of mutations in a tumor – known as the tumor mutation burden (TMB) – to gauge the tumor's responsiveness to immunotherapy.
However, researchers from Johns Hopkins University identified a specific subset of these cancer mutations, which they called "persistent mutations." These mutations tend to stay put as the cancer evolves, keeping the cancer tumor visible to the body's immune system and improving immunotherapy's effectiveness.
"Persistent mutations are always there in cancer cells and these mutations may render the cancer cells consistently visible to the immune system, provoking an immune response that is augmented in the context of immune checkpoint blockade," explained the study's senior author, Dr. Valsamo Anagnostou, associate professor of oncology at Johns Hopkins, director of the thoracic oncology biorepository, and co-leader of the John Hopkins Molecular Tumor Board and the Lung Cancer Precision Medicine Center of Excellence.
She added that the number of persistent mutations better predicts the likelihood of a tumor responding to immune checkpoint blockade compared to TMB.
A look into the future
These findings could revolutionize how doctors select patients for immunotherapy and predict its effectiveness. "In the not-too-distant future, it will be possible to use high-throughput, next-generation sequencing techniques to study patients' mutational spectrum and to categorize patients by their likelihood of response to immunotherapy, which is crucial for advanced cancer," said Dr. Kim Margolin, a medical oncologist and medical director of the Saint John's Cancer Institute Melanoma Program at Providence Saint John's Health Center in California.
Ultimately, this research could move beyond prognostic indicators to become predictive factors that can interact with therapy and disease, even influencing the choice of treatment sites.
- The evidence from Johns Hopkins University suggests that the presence of 'persistent mutations' in certain cancer tumors may enhance the effectiveness of immunotherapy, making it a more promising treatment option for patients.
- In the future, high-throughput, next-generation sequencing techniques could be used to identify 'persistent mutations' in patients, enabling doctors to more accurately select and predict the response of patients to immunotherapy, particularly for advanced cases of cancer.
- By understanding 'persistent mutations' and their implications for cancer treatment, the field of medical-health-and-wellness may witness a significant shift, where treatment options can be tailored to individual patients based on their specific genetic makeup or health-conditions; this could potentially improve the overall success rate of immunotherapy for various types of cancer, such as breast cancer, melanoma, leukemia, non-small cell lung cancer, and even emerging candidates like prostate cancer, brain cancer, and ovarian cancer.
