Mechanistic modeling of the longitudinal tumor and biological markers combined with quantitative cell-free DNA

Early prediction of resistance to immunotherapy is a major challenge in oncology. The ongoing SChISM (Size Cell-fre DNA (cfDNA) Immunotherapies Signature Monitoring) clinical study proposes an innovative approach based on patented cfDNA quantification methods, providing concentration and size profile fluctuations of plasmatic circulating DNA for early therapeutic management of immune checkpoint inhibitors treated patients. The main interest is that such measures can be performed in a less invasive, less expansive way, and especially much earlier than the first imaging evaluation, thanks to liquid biopsies. Five cancer types are investigated: melanoma, head and neck, renal, bladder and lung cancers, with a total of 260 patients at the end of the study, described by their clinical and classical biological data, and cfDNA features, such as concentration, first and second peak of the cfDNA size distribution, and specific size ranges of cfDNA fragments. We developed a mechanistic model of cfDNA joint kinetics with other longitudinal markers and tumor size imaging to help describe and understand the time dynamics of the quantitative profiles of cfDNA over time. The model consists of a dynamical system of differential equations that estimates specifically the component corresponding to cfDNA production by tumor lesions. Subsequently, the model is embedded within a nonlinear mixed-effects statistical framework in order to quantify inter-patient variability, and calibrated on the data. Future perspective will use machine learning models to predict early progression, progression-free survival or overall survival, combining these dynamic parameters and other variables available at baseline