Intervenant : Gaël Moquin-Beaudry, senior postdoc, Osteosarcoma team of unit UMR1360 – Oncogenesis, resistance and therapeutic targets of pediatric cancers. Invité par Macha Nikolski, Head of Computational Biology and Bioinformatics team, IBGC / CNRS, Head of Bordeaux Bioinformatics Center.
Titre: "Spatial omics: from unbiased analysis to translational insight"
Abstract: Spatial transcriptomics are powerful tools for discovery and validation in fundamental and translational research. They however present considerable technical and computational challenges due to their sparse, mixed and spatially distributed nature. We developed the CellsFromSpace methodology to help researchers exploit spatial transcriptomics data using a reference-free, multi-sample compatible framework. We used it to identify new clinically exploitable features in a cohort of 26 osteosarcoma samples from 19 patients: a 9-gene tumor associated theranostic signature to the infiltration and in situ differentiation of osteoclasts in lung metastases. Other case studies will showcase the flexibility and breadth of our biology-informed computational approach.
Biosketch: Gaël Moquin-Beaudry is a Montreal native PhD-trained experimental biologist who developed preclinical autologous humanized mouse models for immuno-oncology using iPSC differentiated cell lines and proto-oncogene lentiviral transduction (J Immunol 2019, Cell Rep Methods 2022). After completing his PhD, with in-depth knowledge of oncogenesis, stem cell biology, particularly MSCs, and immunology, he turned to computational biology in 2019. First working on single cell analysis of immune perturbations in Parkinson’s disease at Montreal’s CHUM research center (Brain 2025), he joined the Osteosarcoma team of Antonin Marchais and Nathalie Gaspar in Gustave Roussy in 2022 to work on spatial transcriptomics of osteosarcoma as a senior Postdoc (Nat Commun 2026) where he co-developed CellsFromSpace (Bioinf Adv 2024). Gaël is interested in the interface of immunity and disease, how it manifests in the spatial distribution of cells, which signals are responsible, and how it can be modeled, quantified and perturbed for therapeutic applications.