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Uncovering the hidden threat: single-organoid analysis reveals clinically relevant treatment-resistant and invasive subclones in pancreatic cancer

Authors :
Maxim Le Compte
Edgar Cardenas De La Hoz
Sofía Peeters
Felicia Rodrigues Fortes
Christophe Hermans
Andreas Domen
Evelien Smits
Filip Lardon
Timon Vandamme
Abraham Lin
Steve Vanlanduit
Geert Roeyen
Steven Van Laere
Hans Prenen
Marc Peeters
Christophe Deben
Publication Year :
2023
Publisher :
Cold Spring Harbor Laboratory, 2023.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal diseases, characterized by a treatment-resistant and invasive nature. In-line with these inherent aggressive characteristics, only a subset of patients show a clinical response to the standard of care therapies, thereby highlighting the need for a more personalized treatment approach. In this study, we comprehensively unraveled the intra-patient response heterogeneity and intrinsic aggressive nature of PDAC on bulk and single-organoid resolution. We leveraged a fully characterized PDAC organoid panel (N=8) and matched our artificial intelligence-driven, live-cell organoid image analysis with retrospective clinical patient response. In-line with the clinical outcomes, we identified patient-specific sensitivities to the standard of care therapies (gemcitabine-paclitaxel and FOLFIRINOX) using a growth rate-based and normalized drug response metric. Moreover, the single-organoid analysis was able to detect resistant as well as invasive PDAC organoid clones, which was orchestrates on a patient, therapy, drug, concentration and time-specific level. Furthermore, ourin vitroorganoid analysis indicated a strong correlation with the matched patient progression-free survival (PFS) compared to the current, conventional drug response readouts. This work not only provides valuable insights on the response complexity in PDAC, but it also highlights the potential applications (extendable to other tumor types) and clinical translatability of our approach in drug discovery and the emerging era of personalized medicine.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........773131cd98b72c4ad27e15cd6bc1cc03
Full Text :
https://doi.org/10.1101/2023.02.27.530080