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
  • 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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