Alexandre Puissant’s team – Molecular Mechanisms of Acute Myeloid Leukemia Development

We apply bioinformatics and biostatistical methodologies derived from artificial intelligence to syngeneic mouse models, combined with deep sequencing of serial patient samples (diagnosis/relapse), to refine the evolutionary trajectories of leukemic clones from initiation to treatment resistance. This allows us to identify adaptive dead-ends that transformed cells are forced to enter, which can be targeted for eradication.

We have developed the RAINBOW program, which leverages functional precision medicine biomarkers based on flow cytometry to improve patient care pathways and identify new therapeutic repositioning strategies or novel drug combinations. This multiparametric pharmacological screening approach, conducted under pseudo-niche conditions, assesses in the context of first-in-human clinical trials (relapsed or refractory patients) the surface antigen expression or preclinical activity of new compounds or combinations on clinically and genetically annotated primary patient samples, including within defined target populations.