Batch Effect Correction in a Functional Colorectal Cancer Organoid Clinical Correlation Study

Abstract

Batch effects are recognized as major sources of technical confounding in high-throughput assays. However, their impact on organoid studies receives little attention in the literature. As organoids gain prominence as a class of emerging new approach methodologies (NAMs), consideration of batch variation will become increasingly important to ensure data reproducibility and accurate interpretation in pre-clinical and clinical studies. In this manuscript, we provide a practical description of our work in detecting, characterizing, and correcting batch effects in a prior published retrospective clinical colorectal cancer organoid drug-response study. We outline the workflow we employed, including exploratory diagnostics, experimental drift detection, and statistical adjustment. We detail the methods employed to evaluate batch effects, monitor longitudinal drift, and select approaches to remove technical artifacts, preserve biological signal and test for robustness. Our experience demonstrates that in even modestly sized studies, results can be adversely affected by insufficient consideration and attempts at ameliorating batch effects. By documenting the challenges we encountered and the solutions implemented within our study, we hope that we can provide a seminal practical reference for organoid researchers and enable increased discussion and adoption of robust batch-compensation practices in the organoid field, ensuring that the topic is more routinely addressed, improved, and eventually standardized.