Work

A serum-derived 3D tumor model platform for personalized prediction and monitoring of chemotherapeutic response in pancreatic ductal adenocarcinoma

Year: 2026

Type: article

Abstract: • PDAC is deadly due to late diagnosis, heterogeneity, and a dense stroma. • Current treatments lack predictive models for personalized therapy choice. • 3D spheroids from patient serum mimic tumor traits and stay viable for days. • TICK-based chemograms matched clinical outcomes in a 16-patient study. • Accuracy was highest when serum was taken shortly before treatment initiation. Pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal cancer, largely due to late diagnosis, tumor heterogeneity, and a dense, immunosuppressive stroma that limits therapeutic efficacy. While regimens like FOLFIRINOX and gemcitabine-based therapies offer some benefit, treatment selection remains empirical, with no reliable predictive models to guide personalized decisions. We adapted our previously validated serum-derived educated spheroid technology creating 3D spheroids using PDAC patient serum. These spheroids maintained structural integrity, viability, and consistent size over eight days, avoiding overgrowth. They also exhibited extracellular matrix deposition such as type I collagen, and expressed key genes involved in drug resistance and tumor progression including COL1A1, FN1, MMP2, CXCL1 , and CXCL2 . Using the Target-Independent Cell Killing (TICK) strategy, we established individualized chemograms to assess true therapeutic response helping clinicians in refining the optimal treatment protocol. In a 16-case study, our model achieved high concordance with clinical responses across gemcitabine, Gem-Pac, and FOLFIRINOX treatments supporting its utility in personalized care. Finally, we demonstrated that predictive accuracy was highest when patient serum was collected within a short window prior to treatment initiation. These findings support PDAC patient serum-educated spheroids as a rapid, non-invasive, and physiologically relevant tool for guiding personalized chemotherapy and monitoring treatment response in real time.

Source: Translational Oncology

DOI: 10.1016/j.tranon.2025.102659

Authors: Sara Cherradi, Salomé Roux, Marie Dupuy, Eric Assenat, Hong Tuan Duong

Institutions: Centre Hospitalier Universitaire de Montpellier, Hôpital Saint Eloi

Language: English

Topic: Pancreatic and Hepatic Oncology Research

Subfield: Oncology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,390