56P Rapid and accurate prediction of TKI treatment response in advanced EGFR-mutant non-small cell lung cancer using the CODRP platform

Patient-derived organoids (PDOs) have shown promise in modeling cancer therapy response, but their application in clinical decision-making is challenging. We aimed to address this challenge by developing a disposable nozzle-type cell spotter for efficient high-throughput screening (HTS) of cells from malignant pleural effusion. Our focus was on patients with advanced EGFR-mutated non-small cell lung cancer (NSCLC) using the Cell-based Organoid Drug Response Prediction (CODRP)-based precision oncology platform to assess the effectiveness of tyrosine kinase inhibitor (TKI) treatments. We collected cells from fourteen lung cancer patients and used the HTS cell spotter for analysis. The CODRP index, considering cancer cell proliferation rate and AUC values, was employed to evaluate EGFR-TKI drug sensitivity. We compared the results with those obtained using the conventional AUC index. The conventional AUC index did not effectively differentiate patients into sensitive and resistant groups for EGFR-TKI treatment. In contrast, the CODRP index-based drug sensitivity test consistently correlated with the clinical drug treatment response. Our findings demonstrate the reliability of the CODRP index in predicting EGFR-TKI efficacy within a clinically suitable timeline of 14 days. PDO-based HTS combined with the CODRP index offers a promising approach to predict and analyze the effectiveness of anticancer drugs for lung cancer patients. By incorporating multiple parameters and utilizing patient-derived models, this strategy contributes to the development of a precision medicine platform. The CODRP index-based drug sensitivity test provides a reliable and timely tool for guiding treatment decisions, enabling personalized oncology care for lung cancer patients.