Colorectal Cancer Organoid Model Reveals the Mechanisms of Irinotecan Resistance at Single-Cell Resolution.

OBJECTIVE

Irinotecan, a standard therapeutic agent for metastatic colorectal cancer (mCRC), often faces significant limitations due to drug resistance, with treatment failure observed in approximately 30%-50% of patients, leading to poor clinical outcomes. This study aims to systematically elucidate the molecular mechanisms underlying irinotecan resistance in colorectal cancer (CRC) by constructing patient-derived organoid (PDO) models combined with single-cell transcriptomics technology.

METHODS

PDO models were successfully established from irinotecan-resistant and sensitive CRC patients. Single-cell RNA sequencing (scRNA-seq) was performed on the organoids, analyzing the transcriptomic heterogeneity of 12,360 high-quality cells. Gene Set Variation Analysis (GSVA), transcriptional regulatory networks, and cell communication networks were employed to dissect the resistance mechanisms.

RESULTS

Drug sensitivity assays demonstrated that the IC50 value of irinotecan in CRC5 was significantly higher than that in CRC11, which was entirely consistent with their respective clinical phenotypes. Single-cell sequencing identified CRC5-specific drug-resistant cell clusters, Cluster 1 and Cluster 6. Cluster 1 (MARCKSL1+) was characterized by the activation of the Wnt signaling pathway and extracellular matrix (ECM) remodeling, which collectively contributed to the maintenance of stem cell-like properties, while Cluster 6 (AKR1C3+) exhibited significant enrichment in lipid metabolism and the Notch signaling pathway.

CONCLUSION

This study integrates PDO models with single-cell transcriptomics technology to reveal key cell subpopulations and molecular mechanisms underlying irinotecan resistance. The core mechanisms driving resistance involve the activation of Wnt signaling and the synergistic effect of lipid metabolism-Notch pathways. Cluster 1 and Cluster 6 are identified as potential therapeutic targets, providing a theoretical basis for developing combination therapies targeting cancer stem cells or the metabolic microenvironment.