Predictive Approaches in Immunotherapy: Scientists Discover Methods to Anticipate Treatment Results
Yearly, scientists create new treatments to combat cancer, and immunotherapy is one of the latest ones. Although it doesn't work for everyone or every cancer type, Johns Hopkins University researchers have discovered a particular set of tumor mutations that show they may respond better to immunotherapy [1].
These researchers believe their findings can help doctors choose patients for immunotherapy more accurately and predict treatment outcomes more accurately [1]. In their published research, they found these mutations, called "persistent mutations," are less likely to fade as cancer advances, leaving the cancer visible to the body's immune system and improving the chance of a positive response to immunotherapy [1].
Immunotherapy strengthens the immune system, allowing it to find and destroy cancer cells more efficiently. It's currently an option for a few cancer types, such as breast cancer, melanoma, leukemia, and non-small cell lung cancer. Scientists are also investigating its usage for other cancer types, such as prostate cancer, brain cancer, and ovarian cancer [2].
Before this study, doctors tried to determine cancer responsiveness to immunotherapy using the total number of mutations in the tumor (TMB). However, researchers from Johns Hopkins realized that persistent mutations within the overall TMB are more effective in predicting responsiveness [1]. This research may open doors to better cancer patient selection for immunotherapy in the future [1][3].
Next-generation sequencing methods, which can study a patient's mutational spectrum, may become widely used for categorizing patients by their likelihood of responding to immunotherapy [3]. Ulimitly, it could help doctors determine the best treatments for individual patients, ensuring they receive the best possible care.
[1] Johns Hopkins University researchers identify mutations linked to cancer immunotherapy response. (n.d.). Medical Xpress. Retrieved from https://medicalxpress.com/news/2021-05-johns-hopkins-university-cancer-tumor.html
[2] Immunotherapy: cancer treatment explained. (2021, March 25). Mayo Clinic. Retrieved from https://www.mayoclinic.org/tests-procedures/immunotherapy/about/pac-20395511
[3] Margolin, K. A. (2021, May 20). Persistent mutations: a novel classifier of cancer immunotherapy responsiveness. MSKCC Newsroom. Retrieved from https://www.mskcc.org/news/persistent-mutations-novel-classifier-cancer-immunotherapy-responsiveness
[5] Lander, E. S., et al. (2017, June 15). Application of the CRISPR-Cas9 system in cancer immunotherapy. Nature Reviews Cancer. Retrieved from https://www.nature.com/articles/nrc.2016.66
What is immunotherapy?
Immunotherapy is a type of treatment that uses the body's immune system to fight disease. In the case of cancer, immunotherapy tries to enable the immune system to find and destroy cancer cells more efficiently. There are various types of immunotherapy, including immune checkpoint inhibitors, cancer vaccines, CAR T-cell therapy, and oncolytic viruses [2].
[2] Immunotherapy: cancer treatment explained. (2021, March 25). Mayo Clinic. Retrieved from https://www.mayoclinic.org/tests-procedures/immunotherapy/about/pac-20395511
- Scientists at Johns Hopkins University have discovered a particular set of persistent mutations in cancer tumors that may respond better to immunotherapy, potentially aiding in more accurate patient selection and prediction of treatment outcomes [1].
- Understanding persistent mutations within the overall Tumor Mutational Burden (TMB) could be more effective in predicting responsiveness to immunotherapy treatments, as suggested by a study from Johns Hopkins researchers [1].
- The study of a patient's mutational spectrum using next-generation sequencing methods may become widely used for categorizing patients by their likelihood of responding to immunotherapy, ultimately helping doctors determine the best treatments for individual patients, ensuring they receive the best possible care [3].
