How to know if a treatment against lung cancer is effective or not, through a biomarker

Adjusting the temporary application of a treatment to a patient is crucial for their recovery. Knowing if, for example, an immunotherapy treatment should be prolonged or shortened depending on whether or not it is being effective, is vital for the patient’s health, especially considering that fatigue, fever, chills, weakness, nausea, vomiting, dizziness, body aches, and high or low blood pressure are possible side effects of immunotherapy.

Selection of an effective treatment and proper assessment of clinical benefit are important to better manage cancer patients with prolonged survival and preserve quality of life. Cancer treatments are often effective, but they also have a significant impact on patients, in various settings.

A study carried out by researchers from the Polytechnic University of Madrid (UPM) and several of the Network Biomedical Research Centers in Spain has aimed to improve the ability to predict the lasting clinical benefit of immunotherapy.

Thanks to this study, a non-invasive biomarker has been identified to predict the lasting clinical benefit of immunotherapy, based on the integration of monitored clinical and radiomic data, during the first months of treatment with anti-PD-1/PD- monoclonal antibodies. L1, in patients with advanced non-small cell lung cancer.

According to María Jesús Ledesma, a researcher at the Polytechnic University of Madrid, as well as the Center for Biomedical Research in the Bioengineering, Biomaterials and Nanomedicine Network (CIBERBBN), and co-author of this study, the results obtained in this have represented a significant advance in the prediction and monitoring of the response to immunotherapy using multimodal artificial intelligence, based on non-invasive data from the start of treatment.

On the other hand, Benito Farina, from the research team, highlights that “thanks to this research, the life and health of patients with advanced lung cancer could be improved by determining in time, and objectively, the efficacy of the treatment, avoiding toxicities, costs and facilitating the application of alternative treatments”.

The new research has made it possible to identify a non-invasive biomarker to predict the lasting clinical benefit of immunotherapy against lung cancer. (Image: UPM)

The identification of non-invasive predictive biomarkers of response to immunotherapy is crucial to avoid premature treatment interruptions or ineffective prolongations. A biomarker is sometimes used to determine the body’s response to a treatment for a disease or condition.

Immunotherapy makes it possible to help the immune system of patients to do its job against tumor cells, through the administration of drugs that allow deactivating the evasion mechanisms that cancer cells develop. It is done like this, for curative or preventive purposes.

Immunotherapy has become one of the reference treatments for advanced non-small cell lung cancer, with promising response rates, a disease that continues to occur with high frequency. The prediction of the efficacy of the response to treatment before and during treatment remains critical for the personalized management of patients.

The Center for Biomedical Research in a Network of Respiratory Diseases (CIBERES), the Center for Biomedical Research in a Cancer Network (CIBERONC), and the Fundación Jiménez Díaz and Clínica Universidad de Navarra hospitals, all of these in Spain, have also collaborated in the new study. entities.

The study is titled “Integration of longitudinal deep-radiomics and clinical data improves the prediction of durable benefits to anti-PD-1/PD-L1 immunotherapy in advanced NSCLC patients”. And it has been published in the Journal of Translational Medicine. (Source: UPM)