Related Experiment Video
Updated: May 6, 2026

Multiparametric Tumor Organoid Drug Screening Using Widefield Live-Cell Imaging for Bulk and Single-Organoid Analysis
Published on: December 23, 2022
Organoid morphology-guided classification for oral cancer reveals prognosis
Mi Rim Lee1, Sumin Kang1, Jonghyun Lee2
1Molecular Imaging Branch, Division of Convergence Technology, Research Institute of National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang, Gyeonggi-do 10408, Republic of Korea; Department of Cancer Biomedical Science, National Cancer Center Graduate School of Cancer Science and Policy, 323 Ilsan-ro, Ilsandong-gu, Goyang, Gyeonggi-do 10408, Republic of Korea.
Abstract:
Oral cancer is an aggressive malignancy with a survival rate below 50% in advanced stages due to low mutation rates, lack of molecular subtypes, and limited treatment targets. This study presents a pioneering approach to classifying oral cancer subtypes based on the morphology of patient-derived organoids (PDOs) and proposes a therapeutic strategy. We establish 76 cancer and 81 normal PDOs. For cancer PDOs, both manual classification and AI-based scoring are utilized to categorize them into three distinct subtypes: normal-like, dense, and grape-like. These subtypes correlate with unique transcriptomic profiles, genetic mutations, and clinical outcomes, with patients harboring dense and grape-like organoids exhibiting poorer prognoses. Furthermore, drug response assessments of 14 single agents and cisplatin combination therapies identify a synergistic treatment approach for resistant subtypes. This study highlights the potential of integrating morphology-based classification with genomic and transcriptomic analyses to refine oral cancer subtyping and develop effective treatment strategies.

