Deciphering the energetic code of cells for better anticancer therapies
The CNRS, INSERM, and Aix-Marseille University scientists at the Centre d'Immunologie de Marseille-Luminy, in association with colleagues from the University of California San Francisco and the Marseille Public University Hospital System (AP-HM), with support from Canceropôle Provence-Alpes-Côte d'Azur, have reported a procedure that may help personalize anticancer therapies. Their patented technique reveals the energy status of cells, an indicator of their activity. It is presented in Cell Metabolism.
Immunotherapies are a promising anticancer arsenal and work by mobilizing the immune system to recognize and destroy cancer cells. Currently, however, only a third of patients respond to immunotherapies: The tumor environment can be hostile to immune cells, depriving them of their source of energy, which diminishes treatment efficacy. The energy status of the various types of immune cells is a marker of their activity, and particularly of their pro- or antitumour action. To boost the effectiveness of immunotherapies, it is thus essential to have a simple method for characterizing the energy profiles of immune cells from tumor samples.
SCENITH is just such a method. Developed by scientists working in Marseille and San Francisco, it identifies energy sources on which the different cells in the tumor are dependent and, most importantly, the specific needs of immune cells in this hostile environment. It uses the level of protein synthesis, a process responsible for half of cellular energy consumption, as an indicator of a cell's energy status. The biopsy sample is separated into subsamples that are each treated with an inhibitor of a metabolic pathway through which cells produce energy. Levels of protein synthesis are then measured using a flow cytometer, which also makes it possible to differentiate types of cells in the sample and identify cell surface markers targeted by therapies. The SCENITH method thus identifies the energy status of each immune or cancer cell within the tumor, its energy sources, and the metabolic pathways it relies upon.
The scientists behind SCENITH have already begun working with clinical research teams to better understand how it might be used to predict patient treatment response. They seek further collaborations of this kind to determine profiles associated with different responses to immuno- and chemotherapy. SCENITH seeks to enable personalized treatment for each patient that exploits the strengths of the immune response and the weaknesses of the tumor.