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.

The engineering strategy of artificial biointerfaces is vital for governing their performances in bioanalysis and diagnosis. Highly ordered arrangement of affinity ligands on the interface surface facilitates efficient interaction with target molecules, whereas biointerfaces aimed at drug delivery or rare cell isolation require sophisticated stimuli-response mechanisms. However, it is still challenging to facilely fabricate biointerfaces possessing the two features. Herein, we endow a biointerface with both reversibility and capability to orderly assemble affinity ligands by introducing boronic acid moieties alone. By boronate conjugation via glycosylation sites, avidin was well arranged at the surface of boronic acid-decorated carbon nitride nanosheets for the assembly of biotinylated aptamers. The ordered orientation of aptamers largely relieved their inactivation caused by inter-strand entanglement, facilitating significant increase in cell affinity for the isolation of circulating tumor cells (CTCs). The reversible boronate conjugation also facilitated mild release of CTCs by acid fructose with high cell viability. This engineered interface was capable of isolating CTCs from the peripheral blood of tumor-bearing mice and cancer patients. The successful utilization of the isolated CTCs in the downstream drug susceptibility test and mutation analysis demonstrated the clinical potential of this biointerface for the early diagnosis of cancers and precision medicine.

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 RT-PCR 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.