An organoid library of salivary gland tumors reveals subtype-specific characteristics and biomarkers

Abstract

Abstract Background Salivary gland tumors (SGTs) include a large group of rare neoplasms in the head and neck region, and the heterogeneous and overlapping features among the subtypes frequently make diagnostic difficulties. There is an urgent need to understand the cellular mechanisms underlying the heterogeneity and overlap among the subtypes, and explore the subtype-specific diagnostic biomarkers. Methods The tumor tissue and the adjacent normal tissue from the 6 most common types of SGTs were processed for organoid culture which only maintained tumor epithelial cells. Organoids were histologically evaluated based on phenotype markers, followed by transcriptional profiling using RNA-sequencing. The transcriptomic similarities and differences among the subtypes were analyzed by subtype consensus clustering and hierarchical clustering. Furthermore, by comparative transcriptional analysis for these 6 types of SGTs and the matched organoids, the potential diagnostic biomarkers from tumor epithelium were identified, in which two selected biomarkers were evaluated by qPCR and confirmed by immunohistochemistry staining using a tissue microarray. Results We generated a biobank of patient-derived organoids (PDOs) with 6 subtypes of SGTs, including 21 benign and 24 malignant SGTs. The PDOs recapitulated the morphological and transcriptional characteristics of the parental tumors. The overlap in the cell types and the heterogenous growth patterns were observed in the different subtypes of organoids. Comparing the bulk tissues, the cluster analysis of the PDOs remarkably revealed the epithelial characteristics, and visualized the intrinsic relationship among these subtypes. Finally, the exclusive biomarkers for the 6 most common types of SGTs were uncovered by comparative analysis, and PTP4A1 was demonstrated as a useful diagnostic biomarker for mucoepidermoid carcinoma. Conclusions We established the first organoid biobank with multiple subtypes of SGTs. PDOs of SGTs recapitulate the morphological and transcriptional characteristics of the original tumors, which uncovers subtype-specific biomarkers and reveals the molecular distance among the subtype of SGTs.