Immunotherapy Outcomes Prediction: Studying Strategies to Forecast Responses
Immunotherapy: A Game-Changer in the Fight Against Cancer
Every year, scientists delve deeper into discovering innovative treatments for cancer, and one of the latest additions to this arsenal is immunotherapy.
However, it's important to note that not every individual or cancer type may benefit from immunotherapy. Researchers are tirelessly trying to uncover the mysteries behind immunotherapy's effectiveness.
Recently, a team of researchers from Johns Hopkins University identified a specific set of mutations within cancer tumors that shed light on the tumor's response to immunotherapy.
Scientists believe these findings will help doctors better select candidates for immunotherapy, ultimately allowing them to predict the treatment's outcomes.
Their research, recently published in the journal Nature Medicine, provides important insights into the world of immunotherapy.
What is Immunotherapy?
Immunotherapy enlists the body's immune system to combat disease. Typically, cancer cells develop mutations that let them evade the immune system. Immunotherapy gives the immune system a boost, making it easier to spot and destroy cancer cells.
There are various forms of immunotherapy, including checkpoint inhibitors, CAR T-cell therapy, and tumor vaccines.
Immunotherapy currently serves as a treatment option for cancers like breast cancer, melanoma, leukemia, and non-small cell lung cancer. Researchers are examining the possibilities of using immunotherapy for other cancer types, such as prostate cancer, brain cancer, and ovarian cancer.
Unveiling the Secrets of Mutations
In their study, the Johns Hopkins researchers found that doctors currently estimate a tumor's responsiveness to immunotherapy using the total number of mutations, known as the tumor mutation burden (TMB).
"Tumor mutation burden is the number of alterations in the genetic material," explains Dr. Valsamo Anagnostou, a senior author of the study and an associate professor of oncology at Johns Hopkins. "A large number of mutations in cancer cells effectively distinguishes them from normal cells, making them more visible to the immune system."
Identifying Persistent Mutations
Through their research, Anagnostou's team identified a specific subset of mutations within the TMB they called "persistent mutations." These mutations are less likely to disappear as cancer evolves, keeping the cancer tumor visible to the immune system for a better response to immunotherapy.
"Persistent mutations are always present in cancer cells," says Anagnostou. "These mutations make the cancer cells continuously detectable by the immune system, leading to a stronger immune response augmented by immunotherapy."
These findings, she adds, may help clinicians more accurately select patients for immunotherapy clinical trials or predict the outcome of immunotherapy for cancer patients.
Paving the Way for the Future
Dr. Kim Margolin, a medical oncologist and medical director at Providence Saint John's Health Center in California, believes the study opens up exciting possibilities for cancer treatment.
"These findings highlight a new, promising approach for identifying cancer patients who are likely to respond well to immunotherapy," Margolin says. "As high-throughput sequencing techniques evolve, it may become possible to quickly categorize patients by their likelihood of responding to immunotherapy, ultimately leading to more personalized and effective cancer treatment options."
- Immunotherapy, a game-changer in the fight against cancer, relies on the immune system to combat disease, particularly in cancer cases where cells have developed mutations that let them evade the immune system.
- Recent research from Johns Hopkins University revealed a specific set of persistent mutations within cancer tumors, which could aid doctors in better selecting candidates for immunotherapy, ultimately allowing them to predict the treatment's outcomes.
- As high-throughput sequencing techniques advance, it may become possible to quickly categorize cancer patients by their likelihood of responding to immunotherapy, leading to more personalized and effective cancer treatment options in the future.
