Wide-Field Optical Redox Imaging with Leading-Edge Detection Enables Assessment of Treatment Response and Heterogeneity in Patient-Derived Cancer Organoids.

UNLABELLED: Patient-derived cancer organoids (PDCO) are a valuable model to recapitulate human disease in culture, with important implications for drug development. However, current methods for rapidly and reproducibly assessing PDCOs are limited. Label-free imaging methods are a promising tool to measure organoid-level heterogeneity and rapidly screen drug responses in PDCOs. This study aimed to assess and predict PDCO response to treatments based on mutational profiles using label-free wide-field optical redox imaging (WF ORI). WF ORI provided organoid-level measurements of treatment response without labels or additional reagents by measuring the autofluorescence intensity of the metabolic coenzymes NAD(P)H and FAD, and the optical redox ratio, defined as the fluorescence intensity of [NAD(P)H/NAD(P)H + FAD], was used to measure the oxidation-reduction state of PDCOs. Development of leading-edge analysis tools helped maximize the sensitivity and reproducibility of treatment response measurements using WF ORI in colorectal cancer PDCOs. Leading-edge analysis improved sensitivity to redox changes in treated PDCOs. Additionally, WF ORI resolved FOLFOX (5-fluorouracil + oxaliplatin) treatment effects across all PDCOs better than two-photon ORI, with an approximately threefold increase in effect size. WF ORI distinguished metabolic differences based on driver mutations in colorectal cancer PDCOs, differentiating between KRAS + PIK3CA double-mutant PDCOs and wild-type PDCOs with 80% accuracy and identified treatment-resistant mutations in mixed PDCO cultures. Overall, WF ORI enables rapid, sensitive, and reproducible measurements of treatment response and heterogeneity in colorectal PDCOs that will affect patient management, clinical trials, and preclinical drug development.

SIGNIFICANCE: Label-free wide-field optical redox imaging is an accessible tool for monitoring changes in metabolism in patient-derived cancer organoids to reproducibly assess treatment response and heterogeneity in clinically relevant treatment studies.