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.


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.

MeSH terms

  • Colorectal Neoplasms* / drug therapy
  • Colorectal Neoplasms* / genetics
  • Colorectal Neoplasms* / pathology
  • Humans
  • Lapatinib
  • Liver Neoplasms* / drug therapy
  • Liver Neoplasms* / genetics
  • Liver Neoplasms* / pathology
  • Organoids
  • Precision Medicine / methods


  • Lapatinib