Magali Richard

Magali Richard

I am a CNRS researcher in bioinformatics, with a background in molecular biology, genetics, and computational biology. My research focuses on tumor heterogeneity, method development, and cancer biology, and I also promote collaborative science by organizing data challenges.

Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma

To allow rapid PDAC molecular subtyping and study PDAC heterogeneity, we develop PACpAInt, a multi-step deep learning model. PACpAInt correctly predicts tumor subtypes at the whole slide level on surgical and biopsies specimens and independently predicts survival. PACpAInt highlights the presence of a minor aggressive Basal contingent that negatively impacts survival in 39% of RNA-defined classical cases.

Recommended citation: Saillard, C., Delecourt, F., Schmauch, B. et al. Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma. Nat Commun 14, 3459 (2023). https://doi-org.ins2i.bib.cnrs.fr/10.1038/s41467-023-39026-y
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