France, Marseille 
Dr. Nelson Dusetti is a senior translational oncology researcher and internationally recognized expert in pancreatic cancer biology, based in Marseille, France. His work focuses on tumor heterogeneity and the development of transcriptomic signatures to guide precision oncology. He has significantly contributed to biomarker discovery and treatment personalization in pancreatic ductal adenocarcinoma (PDAC), bridging molecular research with clinical application.
Current Position
- Research Director, INSERM
- Head, Translational and Therapeutic Targets Research in Pancreatic Cancer Team, Cancer
- Research Center of Marseille (CRCM)
- Chair, TRANSLATE-IT Program, CRCM
- Scientific Director (Former CSO), Predicting Med
Education
- PhD in Molecular Biology, Universidad de Buenos Aires
- Habilitation (HDR) in Molecular Biology, Aix-Marseille Université
Clinical & Research Focus
- Pancreatic ductal adenocarcinoma (PDAC)
- Tumor heterogeneity and molecular stratification
- Transcriptomic signatures and biomarker discovery
- Precision oncology and treatment response prediction
- Development of patient-derived tumor models
Scientific & Translational Impact
- Pioneer in transcriptomic-based prediction of chemotherapy sensitivity in pancreatic cancer
- Developed molecular gradients (PAMG) to predict clinical outcomes in PDAC
- Led the creation of AI-assisted transcriptomic tools for personalized treatment strategies
- Bridged academic research with clinical implementation through translational programs
Innovation & Industry Contribution
- Co-founder of Predicting Med
- Developed molecular diagnostic tools to support clinical decision-making in oncology
- Active in translating omics-based discoveries into real-world clinical applications
Academic Profile
- Extensive publication record in high-impact oncology and translational research journals
- Key contributions to:Transcriptomic prediction of gemcitabine sensitivity
- AI-assisted biomarker development
- Molecular classification of pancreatic cancer
All information is sourced from publicly available materials.