Chemotherapy remains the primary treatment for pancreatic ductal adenocarcinoma (PDAC), a highly aggressive form of pancreatic cancer. However, treatment regimens are primarily based on patient performance and expected efficacy, underscoring the need for molecular predictors of chemotherapeutic efficacy to improve patient prognosis through personalized treatment.
To address this need, the Pancreatic Cancer Team at the Cancer Research Center of Marseille developed RNA-based signatures to predict the efficacy of all drugs used to treat PDAC. They utilized preclinical models such as primary cell cultures (PCC), patient-derived xenografts (PDX), and patient-derived organoids (PDO) to overcome limitations of individual models. The team combined all three models to produce unbiased predictive RNA-based signatures. This signatures were validated in different patient cohorts, showing significant associations with overall, disease-free, and progression-free survival.
The importance of thorough target validation in the initial stages of pharmaceutical development is also discussed in the presentation. Incomplete preclinical validation can lead to efficacy and toxicity setbacks, highlighting the need for tailor-made strategies for investigating target validation. Oncodesign-services offers innovative approaches, such as PDAC 2D and 3D cell models, CRISPR target modulation, and real-time proliferation, which hold great promise for advancing the field of drug discovery and personalized medicine in pancreatic cancer.
Join the featured speakers for an informative webinar on unlocking the synergy in preclinical models and the importance of target validation for the personalized treatment of pancreatic cancer.
Key learning objectives
Attendees will discover:
- RNA-based signatures can be used to predict the efficacy of all drugs used to treat PDAC and improve prognosis by tailoring treatments
- Using a combination of in vitro models (primary cell cultures and patient-derived organoids) and patient-derived xenografts can overcome individual model limitations and produce unbiased RNA-based signatures
- How personalized treatment based on molecular analysis and unbiased RNA-based signatures could lead to better patient outcomes and the development of more effective treatments for PDAC
- The utilization of methodologies such as PDAC 2D/3D cell models, CRISPR target modulation and real-time proliferation to improve target validation
About our speakers
Dr. Nelson Dusetti, Research Director at the Cancer Research Center of Marseille, INSERM U.1068
Nelson Dusetti is an oncology researcher with expertise in pancreatic cancer. He developed an innovative approach for predicting tumor response to chemotherapy using transcriptomic signatures validated in clinical studies. As Director of the Translational Research and Innovative Therapies department, he currently leads the Translational and Therapeutic Targets Research Pancreatic Cancer team. Dusetti co-founded Predicting Med, a startup aiming to commercialize molecular tests for chemotherapy response in pancreatic cancer. His research has significantly contributed to improving chemotherapy efficacy and developing predictive tools for chemo sensitivity in pancreatic cancer.
Dr. Nicolas Ancellin, Senior Program Director/Site Director, Strategic Projects, Oncodesign Services
Nicolas Ancellin is an experienced cell and molecular biologist specializing in drug discovery. He completed his post-doctoral fellowship at UCONN researching angiogenesis signaling before joining GlaxoSmithKline in 2002, where he successfully led multiple drug discovery projects and gained expertise in target identification and validation. Since joining Oncodesign in 2016, he has been instrumental in developing a LRRK2 kinase inhibitor, which is currently in Phase I clinical trials (run by OPM, sponsored by Servier). In his current role as the research site director and strategic project director at Oncodesign-services, Nicolas is actively involved in integrated drug discovery projects.