npj Precision Oncology (Dec 2023)

Single-organoid analysis reveals clinically relevant treatment-resistant and invasive subclones in pancreatic cancer

  • 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

DOI
https://doi.org/10.1038/s41698-023-00480-y
Journal volume & issue
Vol. 7, no. 1
pp. 1 – 14

Abstract

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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 shows 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, our in vitro organoid analysis indicated a 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.