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Scientific article
Open access
English

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

Publication date2023-04-03
First online date2023-04-03
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.

eng
Keywords
  • Drug‑drug interaction
  • Drug resistance
  • Multidrug combination
  • Organoid
  • Phenotypic screen
  • Synergy
  • Targeted RNAseq
Funding
Citation (ISO format)
RAMZY, George Mourad et al. Platform combining statistical modeling and patient-derived organoids to facilitate personalized treatment of colorectal carcinoma. In: Journal of experimental & clinical cancer research, 2023, vol. 42, n° 1, p. 79. doi: 10.1186/s13046-023-02650-z
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Identifiers
ISSN of the journal1756-9966
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Technical informations

Creation04/04/2023 2:22:12 PM
First validation05/09/2023 6:59:30 AM
Update time05/09/2023 6:59:30 AM
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