DESCRIPTION :
Liquid biopsy has established itself as a powerful tool for the early detection of cancer and the diagnosis, prognosis and treatment monitoring in a wide range of cancer types [1]. The BIAbooster technology from Adelis allows precise quantification of the size of cell free DNA fragments from plasma samples, establishing size distributions over a wide range of base pairs (part of the fragmentome). In the SChISM (Size Cfdna Immunotherapies Signature Monitoring, N = 334 patients) study led by Pr S. Salas (APHM and COMPO), we have demonstrated that features derived from these distributions were predictive of response to immunotherapy as univariable biomarkers [2, 3] or integrated within multivariable machine learning predictive models.
One of the main interest of such non-invasive biomarkers is for monitoring the response during treatment. We have developed a first mechanistic model of the longitudinal data collected during SChiSM that demonstrated added value for prediction of progression [4].
Objectives
1. At Adelis, develop advanced signal processing methods to improve the information extracted from the cfDNA fragment size distributions
2. Develop mechanistic models of the dynamics of the cfDNA size distributions, coupled with tumor and immune variables
3. Implement a clinical decision tool for adaptive therapeutic decision
Methodology
* Optimization of scalar or functional metrics derived from the cfDNA size distributions
* Mathematical modeling of the system dynamics, first using ordinary differential equations, then with size-structured partial differential equations
* Statistical modeling of the inter-individual variability through mixed-effects modeling
* Joint modeling for association with time-to-event outcomes (progression-free or overall survival)
References:
1. Computational modeling for circulating cell-free DNA in clinical oncology
L. Nguyen-Phuong, S. Salas, S. Benzekry
JCO Clinical Cancer Informatics, 2025, 9
2. The SChISM study: Cell-free DNA size profiles as predictors of progression in advanced carcinoma treated with immune-checkpoint inhibitors
Linh Nguyen Phuong, Frederic Fina, Laurent Greillier, Pascale Tomasini, Jean-Laurent Deville, Romain Zakrasjek, Lucie Della-Negra, Audrey Boutonnet, Frédéric Ginot, Jean-Charles Garcia, Sébastien Benzekry, Sébastien Salas
under review, 2025
3. Long cell-free DNA fragments predict early-progression in patients with advanced or metastatic cancer treated with immune-checkpoint inhibition.
Sébastien Salas, Linh Nguyen Phuong, Jean-Charles Garcia, Laurent Greillier, Caroline Gaudy-Marqueste, Jean-Laurent Deville, Audrey Boutonnet, Frédéric Ginot, Frédéric Fina, Sébastien Benzekry
ASCO, 2024
4. Mechanistic Modeling of Joint Circulating Cell-free DNA Concentration-Tumor Size Kinetics under Immune-Checkpoint Inhibitors in Advanced Cancer
Linh Nguyen Phuong, Frederic Fina, Romain Zakrajsek, Lucie Della-Negra, Pascale Tomasini, Jean-Laurent Deville, Laurent Greillier, Caroline Gaudy-Marqueste, Audrey Boutonnet, Frédéric Ginot, Jean-Charles Garcia, Sébastien Salas, Sébastien Benzekry
PAGE 2025
Principales activités
Main activities :
* Statistical data analysis
* Signal processing
* Mathematical modeling
* Statistical modeling (nonlinear mixed-effects modeling)
* Machine learning
* Programming
* Reporting: writing scientific papers, oral communications
Additional activities :
* Review the literature
* Test and enhance the codebase
* Presentation to a non-technical audience
* Conceive apps for biomedical users (e.g. Shiny apps)
Code d'emploi : Infirmier Praticien en Oncologie (h/f)
Domaine professionnel actuel : Infirmiers Spécialisés
Niveau de formation : Bac+8
Temps partiel / Temps plein : Plein temps
Type de contrat : Contrat à durée indéterminée (CDI)
Compétences : Analyse des Données, Simulation Informatique, Programmation Informatique, Python (Langage de Programmation), Machine Learning, Traitement de Signal, Scripting, Technologies Informatiques, Sens de la Communication, Génie Biomédical, Travaux Cliniques, Elaboration des Prévisions, Immunothérapie, Étude Longitudinale, Mathématiques, Modélisation Mathématique, Oncologie, Équations Différentielles Ordinaires (CALCUL Différentiel), Équation Différentielle Partielle, Modélisation Prédictive, Analyses Prédictives, Etudes et Statistiques, Dynamique des Systèmes, Capacités de Démonstration, Métrique, Littérature
Courriel :
Sebastien.Benzekry@inria.fr
Téléphone :
0139635511
Type d'annonceur : Employeur direct