Toward Clinical Adoption of Spatial Omics and Computational Pathology in Oncology
Spatial omics technologies map molecular information within intact tissue architecture, revealing how cellular organization and interactions shape tumor biology, therapeutic responses, resistance, and relapse. Advances in artificial intelligence and computational pathology are bridging research discovery and clinical practice, enabling prognostic extraction from routine histology and cost-effective molecular inference. Nevertheless, barriers including high costs, protocol complexity, and lack of standardized workflows remain. We outline how these converging fields can deliver translational value in oncology and identify key enablers for clinical adoption.
Authors
- Nathan Noiry (ORCID: https://orcid.org/0000-0002-7898-8640)
- Pierre‐Emmanuel Bonté (ORCID: https://orcid.org/0000-0002-9732-5826)
- Yasmine Adimi (ORCID: https://orcid.org/0009-0008-0447-2036)
- Grégoire Gessain (ORCID: https://orcid.org/0000-0001-6800-0339)
- Mariana Quiroga Londoño (ORCID: https://orcid.org/0000-0003-2352-0773)
- Franck Augé (ORCID: https://orcid.org/0000-0002-5641-4152)
- Antonin Marchais (ORCID: https://orcid.org/0000-0003-0954-8294)
- Galina Boldina (ORCID: https://orcid.org/0000-0002-8829-022X)
- Marion Classe (ORCID: https://orcid.org/0000-0002-0802-6585)
- Luis Cano
- Florent Ginhoux
- Sabrina Carpentier
- Cécile Badoual
- Julien Vibert
- Gaël Moquin-Beaudry
Institutions
- Inserm (FR)
- Université Paris-Saclay (FR)
- Institut Gustave Roussy (FR)
- Sanofi (France) (FR)
- Biomarker Strategies (United States) (US)
- Servier (France) (FR)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2026-09-01
- DOI
- https://doi.org/10.1038/s41746-026-03157-5
- Primary Topic
- Cancer Genomics and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Sanofi
- Institut Gustave-Roussy
- Servier