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Poster Année : 2023

Quantitative cell-free DNA markers for prediction of early progression in patients undergoing immunotherapy

Résumé

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 much earlier than the first imaging evaluation, thanks to liquid biopsies. Five cancer types were 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, as concentration, first and second peak of the cfDNA size distribution, and specific size ranges of cfDNA fragments. The principal purpose is to early predict response to immunotherapy by searching for a longitudinal signature in the concentration and sizes in cfDNA. The study aims to develop mechanistic model of cfDNA joint kinetics with other longitudinal markers and tumor size imaging. Such models embedded within a statistical framework will then be calibrated on our population data. Machine learning models will be used to predict some outcomes as radiologically confirmed progression at the first imaging evaluation, progression-free survival or the overall survival, thanks to these dynamic parameters and other variables available at baseline and in order to predict response to immunotherapy. Thus, typical classification models as logistic regression, or survival models as proportional hazard Cox regression model will be tested to analyze feature at baseline, and models consisting of a dynamic system of differential equations will help us to describe the evolution of the quantitative profile of cfDNA over time.
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Dates et versions

hal-04388821 , version 1 (11-01-2024)

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  • HAL Id : hal-04388821 , version 1

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Linh Nguyen Phuong, Laurent Greillier, Caroline Gaudy, Jean-Laurent Deville, Jean-Charles Garcia, et al.. Quantitative cell-free DNA markers for prediction of early progression in patients undergoing immunotherapy. Summer School AI4Health, Jul 2023, Paris, France. ⟨hal-04388821⟩
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