Nat Biomed Engine: Scientists have developed new mathematical methods that could help predict the effectiveness of immunotherapy in treating cancer

FEBRUARY 3, 2021 // -- In a recent study published in the international journal Nature Biomedical Engineering, scientists from Houston Methodist Church and others developed a new mathematical model that may help predict how specific types of cancer respond to immunotherapy, increasing the chances of successful treatment with a combination of multiple cancer immunotherapy drugs.
Immunotherapy activates the patient's own immune system to identify and attack cancer, leading to higher, more targeted cancer deaths and fewer side effects than chemotherapy, radiotherapy and other therapies;
Photo Source: CC0 Public Domain researchers say the mathematical models we have developed can use a mathematical equation system based on the laws of physics and chemistry to describe complex biological systems involved in immunotherapy and its associated body's immune response;
Zhihui Wang said: 'We have designed this approach to predict the intensity of the immune response using input measured only in the body of cancer patients, and this model establishes a framework for engineered individualized therapies, which have laid the foundation for the development of non-individual therapies.'
To test the model's ability to accurately and reliably describe specific immunotherapy treatments for cancer, the researchers studied 124 patients and obtained CT or MRI scan data on the patient's body tumor before, during, and after receiving immunosuppressant immunotherapy, and then used the model to analyze the data to obtain specific measures that could produce a therapeutic response.
researchers found that the two model-derived measures were able to quantify the presence and health of the immune system inside the tumor, while the mortality rate of cancer cells caused by immunotherapy-activated immune cell sniping could be combined into a single measurement highly related to the long-term tumor burden, providing the tumor The researchers then studied an additional 177 patients who received one of the common checkpoint inhibitors immunotherapy (anti-CTLA4 or anti-PD1/PDL1 immunotherapy) to confirm the results.
Finally, the researchers say the new mathematical model can be applied quickly in clinical settings without the need for new techniques, personnel or extensive training, and that researchers are currently working on ways to improve the accuracy and accuracy of model-based predictions using other clinical measures, such as data from blood samples or tumor tissue samples.
hope that more joint studies will be conducted later to achieve the clinical transition or transformation of this predictive model.
() Original source: Butner, J.D., Wang, Z., Elganainy, D. et al. A mathematical model for the quantification of a patient’s sensitivity to checkpoint inhibitors and long-term tumour burden. Nat Biomed Eng (2021). doi：10.1038/s41551-020-00662-0