Predicting patient outcome based on gene-expression biomarkers learned from colorectal cancer organoids and cell lines
Colorectal cancer is characterized by an extremely high mortality rate, mainly caused by the high metastatic potential of this type of cancer. To date chemotherapy remains the backbone of the treatment of metastatic colorectal cancer. Three main chemotherapeutic drugs used for treatment of metastatic colorectal cancer are 5-FU, oxaliplatin and irinotecan which is metabolized to an active compound SN-38. The main goal of this study was to find the genes connected to the resistance to the aforementioned drugs and to construct predictive gene expression-based classifier to separate responders and non-responders. In this study we used 7 established colorectal cancer organoids to conduct correlational analysis of the expression and drug resistance. We also included in the study publicly available datasets of colorectal cancer cell lines. The obtained results demonstrated that the expression of just a small group of genes consistently correlate with resistance to standard chemotherapeutic drugs in different datasets. Some of these genes have been previously connected to prognosis or response to anticancer drugs, but some of them were linked to the drug resistance for the first time. The classifier constructed on the expression levels of some of these genes allows to discriminate between patients with favorable and unfavorable 5-year OS prognosis and can be further validated in clinic to improve the results of the treatment. Overall design: Total mRNA profiles of 7 metastatic colorectal cancer organoids from 6 patients were measured to identify correlations of gene expression with sensetivity to standard of care drugs.