Project description:The goal of the study was perform the transcriptome profile of the human salivary gland cell line after exposure to MeHg for 24h using the microarray technique and posterior bioinformatics analysis.
Project description:The present study was aimed to identify aberrantly expressed lncRNAs involved in the progression of SjS and explore their potential functions. Labial salivary gland of 4 SjS patients and 4 healthy controls was collected. LncRNA expression profile in labial salivary gland was analyzed by LncRNA microarray.
Project description:Salivary glands that produce and secret saliva, which is essential for lubrication, digestion, immunity, and oral homeostasis, consist of diverse cells. The long-term maintenance of diverse salivary gland cells in organoids remains problematic. Here, we established long-term murine salivary gland organoids from 3 major salivary glands, including parotid gland (PG), submandibular gland (SMG), and sublingual gland (SLG). Murine salivary gland organoids expressed gland-specific genes and proteins of acinar, myoepithelial, and duct cells. Organoids were maintained in growth media (named GEM) and further underwent differentiation in differentiation media (named DAM). Our study will provide an experimental platform for the exploration of mechanisms involvled in tissue regeneration, development, or several salivary gland diseases.
Project description:We use mRNA-seq to transcriptionally profile larval salivary gland tissue from Drosophila third instar larvae. These data provide insights into tissue physiology and can be used to identify tissue specific transcripts.
Project description:Loss of Irf6 leads to disruption of branching morphogenesis and secretory acnii formation in salivary gland. To determine the differentially expressed genes in Irf6 mutant, embryonic salivary gland tissues were extracted at E14.5.
Project description:Ionizing radiation (IR) – induced salivary gland damage is a common adverse effect in radiotherapy for patients with head and neck cancers. Currently, there is no effective treatment for the resulting salivary gland hypofunction and xerostomia (dry mouth). Here we profiled the acute gene expression change in the mouse submandibular salivary gland, and defined its damage response patterns at the transcriptome level.
Project description:We use mRNA-seq to transcriptionally profile larval salivary gland tissue from Drosophila third instar larvae. These data provide insights into tissue physiology and can be used to identify tissue specific transcripts. Salivary glands were dissected from 200 wandering third instar larvae and the associated fat body was removed.Salivary glands were transferred to Graces unsupplemented medium on ice prior to RNA extraction with TRIzol reagent. mRNA-seq samples were prepared from 10 ug of total RNA and subject to Illumina based sequencing.
Project description:Salivary glands that produce and secret saliva, which is essential for lubrication, digestion, immunity, and oral homeostasis, consist of diverse cells. Maintenance of diverse salivary gland cells in organoids remains problematic. Here, we established human salivary gland organoids, which is composed of multiple cellular subsets, from 3 major salivary glands, including parotid gland (PG), submandibular gland (SMG), and sublingual gland (SLG). Human salivary gland organoids expressed gland-specific genes and proteins of acinar, myoepithelial, and duct cells. Organoids were maintained in growth media (named GEM) and further underwent differentiation in differentiation media (named DAM). Our study will provide an experimental platform for the exploration of mechanisms involvled in tissue regeneration, development, or several salivary gland diseases.
Project description:Tumors of the major and minor salivary gland encompass a diverse spectrum of diagnostically challenging neoplasms. Recent studies have identified several gene fusions and somatic mutations that are specific or highly enriched in certain salivary gland tumor entities and can assist histopathological diagnosis. Still, there is an unmet need to identify additional diagnostic biomarkers for entities lacking specific alterations. In this study, we collected a comprehensive cohort of 363 cases encompassing 20 different salivary gland tumor entities and explored the potential of DNA methylation to classify these tumors. We were able to show that most entities show specific epigenetic signatures and present a machine learning algorithm that can be used to classify diagnostically challenging cases.