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  3. Platform combining statistical modeling and patient-derived organoids to facilitate personalized treatment of colorectal carcinoma

Platform combining statistical modeling and patient-derived organoids to facilitate personalized treatment of colorectal carcinoma

  • J Exp Clin Cancer Res. 2023 Apr 3;42(1):79. doi: 10.1186/s13046-023-02650-z.
George M Ramzy 1 2 3,  Maxim Norkin 4,  Thibaud Koessler 5,  Lionel Voirol 6,  Mathieu Tihy 7,  Dina Hany 1 2 3,  Thomas McKee 7,  Frédéric Ris 8,  Nicolas Buchs 8,  Mylène Docquier 9 10,  Christian Toso 11,  Laura Rubbia-Brandt 7,  Gaetan Bakalli 12,  Stéphane Guerrier 2 6,  Joerg Huelsken 4,  Patrycja Nowak-Sliwinska 13 14 15
Affiliations

Affiliations

  • 1 Molecular Pharmacology Group, School of Pharmaceutical Sciences, University of Geneva, Rue Michel-Servet 1, CMU, 1211, Geneva 4, Switzerland.
  • 2 Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1211, Geneva, Switzerland.
  • 3 Translational Research Center in Oncohaematology, 1211, Geneva, Switzerland.
  • 4 Swiss Institute for Experimental Cancer Research (ISREC), Ecole Polytechnique Fédérale de Lausanne-(EPFL-SV), 1015, Lausanne, Switzerland.
  • 5 Department of Oncology, Geneva University Hospitals, 1205, Geneva, Switzerland.
  • 6 Research Center for Statistics, Geneva School of Economics and Management, University of Geneva, 1205, Geneva, Switzerland.
  • 7 Division of Clinical Pathology, Diagnostic Department, University Hospitals of Geneva (HUG), 1205, Geneva, Switzerland.
  • 8 Translational Department of Digestive and Transplant Surgery, Geneva University Hospitals and Faculty of Medicine, 1205, Geneva, Switzerland.
  • 9 iGE3 Genomics Platform, University of Geneva, 1211, Geneva, Switzerland.
  • 10 Department of Genetics & Evolution, University of Geneva, 1211, Geneva, Switzerland.
  • 11 Department of Visceral Surgery, Geneva University Hospital, 1211, Geneva, Switzerland.
  • 12 EMLYON Business School, Artificial Intelligence in Management Institute, Ecully, France.
  • 13 Molecular Pharmacology Group, School of Pharmaceutical Sciences, University of Geneva, Rue Michel-Servet 1, CMU, 1211, Geneva 4, Switzerland. [email protected].
  • 14 Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1211, Geneva, Switzerland. [email protected].
  • 15 Translational Research Center in Oncohaematology, 1211, Geneva, Switzerland. [email protected].
PMID: 37013646 DOI: 10.1186/s13046-023-02650-z
Abstract

Background: We propose a new approach for designing personalized treatment for colorectal Cancer (CRC) patients, by combining ex vivo organoid efficacy testing with mathematical modeling of the results.

Methods: The validated phenotypic approach called Therapeutically Guided Multidrug Optimization (TGMO) was used to identify four low-dose synergistic optimized drug combinations (ODC) in 3D human CRC models of cells that are either sensitive or resistant to first-line CRC chemotherapy (FOLFOXIRI). Our findings were obtained using second order linear regression and adaptive lasso.

Results: The activity of all ODCs was validated on patient-derived organoids (PDO) from cases with either primary or metastatic CRC. The CRC material was molecularly characterized using whole-exome sequencing and RNAseq. In PDO from patients with liver metastases (stage IV) identified as CMS4/CRIS-A, our ODCs consisting of regorafenib [1 mM], vemurafenib [11 mM], palbociclib [1 mM] and lapatinib [0.5 mM] inhibited cell viability up to 88%, which significantly outperforms FOLFOXIRI administered at clinical doses. Furthermore, we identified patient-specific TGMO-based ODCs that outperform the efficacy of the current chemotherapy standard of care, FOLFOXIRI.

Conclusions: Our approach allows the optimization of patient-tailored synergistic multi-drug combinations within a clinically relevant timeframe.

Keywords

Drug resistance; Drug-drug interaction; Multidrug combination; Organoid; Phenotypic screen; Synergy; Targeted RNAseq.

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