Colorectal cancer is the third most common cancer in the world, with an annual incidence of 2 million cases. The success of first-line chemotherapy plays a crucial role in determining the disease outcome. Therefore, there is an increasing demand for precision medicine to predict drug responses and optimize chemotherapy in order to increase patient survival and reduce the related side effects. Patient-derived organoids have become a popular in vitro screening model for drug-response prediction for precision medicine. However, there is no established correlation between oxaliplatin and drug-response prediction. Here, we suggest that organoid culture conditions can increase resistance to oxaliplatin during drug screening, and we developed a modified medium condition to address this issue. Notably, while previous studies have shown that survivin is a mechanism for drug resistance, our study observed consistent survivin expression irrespective of the culture conditions and oxaliplatin treatment. However, clusterin induced apoptosis inhibition and cell survival, demonstrating a significant correlation with drug resistance. This study’s findings are expected to contribute to increasing the accuracy of drug-response prediction in patient-derived APC mutant colorectal cancer organoids, thereby providing reliable precision medicine and improving patient survival rates.

(1) Background: Recent advances in precision oncology research rely on indicating specific genetic alterations associated with treatment sensitivity. Developing ex vivo systems to identify cancer patients who will respond to a specific drug remains important. (2) Methods: cells from 12 patients with glioblastoma were isolated, cultured, and subjected to high-content screening. Multi-parameter analyses assessed the c-Met level, cell viability, apoptosis, cell motility, and migration. A drug repurposing screen and large-scale drug sensitivity screening data across 59 cancer cell lines and patient-derived cells were obtained from 125 glioblastoma samples. (3) Results: High-content analysis of patient-derived cells provided robust and accurate drug responses to c-Met-targeted agents. Only the cells of one glioblastoma patient (PDC6) showed elevated c-Met level and high susceptibility to the c-Met inhibitors. Multi-parameter image analysis also reflected a decreased c-Met expression and reduced cell growth and motility by a c-Met-targeting antibody. In addition, a drug repurposing screen identified Abemaciclib as a distinct CDK4/6 inhibitor with a potent c-Met-inhibitory function. Consistent with this, we present large-scale drug sensitivity screening data showing that the Abemaciclib response correlates with the response to c-Met inhibitors. (4) Conclusions: Our study provides a new insight into high-content screening platforms supporting drug sensitivity prediction and novel therapeutics screening.