Abstract
PURPOSE: Neoadjuvant chemotherapy is a key component of curative treatment in advanced colorectal cancer (CRC). However, 30%-40% of patients show progression on treatment, underscoring the need for predictive tools to guide up-front treatment selection. Scalable and reproducible methods for patient stratification remain limited. MicroOrganoSpheres (MOS) are droplet-encapsulated 3D tumor models that allow for high-throughput functional drug testing. Here, we evaluate the potential of tumor-derived MOS to predict response to chemotherapy in patients with CRC. METHODS: MOS droplets were generated from 37 primary and/or metastatic tumor samples collected from 21 patients. MOS response to chemotherapy was quantified using AI-based imaging analysis and compared with clinical response (RECIST/disease-free survival [DFS]) and lesion-specific outcomes (pathologic response/percent tumor volume change). RESULTS: MOS chemoprediction assay showed high reproducibility (coefficients of variation ≤ 2.5%). MOS drug sensitivity recapitulated patient response with 83% accuracy in the full sample cohort and 100% accuracy when derived from primary tumors. Patients with sensitive MOS showed longer DFS. Individual MOS analysis revealed preservation of intratumor heterogeneity in vitro and enabled identification of drug-resistant clones. CONCLUSION: MOS technology offers a scalable and robust functional precision medicine platform with potential to guide clinical decision making in CRC. The platform accurately predicts patient response to chemotherapy and provides insights into intrapatient and intratumor heterogeneity.