Organoid morphology-guided classification for oral cancer reveals prognosis

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.