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NeuroscienceScientific Reports
Peer-reviewed journal article

A robust and comprehensive quality control of cerebral cortical organoids: methodology and validation

Héloïse CastiglioneiD, Lucie Madrange, Camille BaquerreiD, B. G. C. MaisonneuveiD, Thomas LemonnieriD, Jean‐Philippe Deslys, Frank YatesiD, Thibault HoneggeriD, Jessica RontardiD, Pierre-Antoine VigneroniD

Abstract

Cerebral organoids hold great promise for neuroscience research as complex in vitro models that mimic human brain development. However, they face significant challenges related to quality and reproducibility, leading to unreliability in both academic and industrial contexts. Discrepancies in morphology, size, cellular composition, and cytoarchitectural organization limit their application in biomedical studies, particularly in disease modeling, drug screening, and neurotoxicity testing, where consistent models are essential. Critically, current methods for organoid characterization often lack standardization and rely heavily on subjective assessments, restricting their broader applicability. In this study, we developed a comprehensive Quality Control (QC) framework for 60-days cortical organoids. Five key criteria: morphology, size and growth profile, cellular composition, cytoarchitectural organization, and cytotoxicity, are evaluated using a standardized scoring system. We implemented a hierarchical approach, beginning with non-invasive assessments to exclude low-quality organoids (Initial Scoring), while reserving in-depth analyses for those that passed the initial evaluation (Final Scoring). To validate this framework, we exposed 60-day cortical organoids to graded doses of hydrogen peroxide (H2O2), inducing a spectrum of quality outcomes. The QC system demonstrated its robustness and reproducibility by accurately discriminating organoid quality based on objective and quantifiable metrics. This standardized and user-friendly framework for quality assessment not only minimizes observer bias but also enhances the reliability and comparability of cerebral organoid studies. Additionally, its scalability makes it suitable for industrial applications and adaptable to other organoid types, offering a valuable tool for advancing both fundamental and preclinical research.

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