학술논문

Platform combining statistical modeling and patient-derived organoids to facilitate personalized treatment of colorectal carcinoma.
Document Type
Article
Source
Journal of Experimental & Clinical Cancer Research (17569966). 4/3/2023, Vol. 42 Issue 1, p1-17. 17p.
Subject
*COLORECTAL cancer
*STATISTICAL models
*ORGANOIDS
*LINEAR orderings
*RNA sequencing
Language
ISSN
1756-9966
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. [ABSTRACT FROM AUTHOR]