ABSTRACT
Mast cells (MCs) are tissue-resident innate immune cells that express the high-affinity receptor for immunoglobulin E and are responsible for host defense and an array of diseases related to immune system. We aimed in this study to characterize the pathways and gene signatures of human cord blood-derived MCs (hCBMCs) in comparison to cells originating from CD34- progenitors using next-generation knowledge discovery methods. CD34+ cells were isolated from human umbilical cord blood using magnetic activated cell sorting and differentiated into MCs with rhIL-6 and rhSCF supplementation for 6-8 weeks. The purity of hCBMCs was analyzed by flow cytometry exhibiting the surface markers CD117+CD34-CD45-CD23-FcεR1αdim. Total RNA from hCBMCs and CD34- cells were isolated and hybridized using microarray. Differentially expressed genes were analyzed using iPathway Guide and Pre-Ranked Gene Set Enrichment Analysis. Next-generation knowledge discovery platforms revealed MC-specific gene signatures and molecular pathways enriched in hCBMCs and pertain the immunological response repertoire.
Subject(s)
Fetal Blood , Mast Cells , Humans , Knowledge Discovery , Antigens, CD34/genetics , Cell Differentiation/geneticsABSTRACT
Gestational diabetes mellitus (GDM) affects one in four Saudi women and is associated with high risks of cardiovascular diseases in both the mother and foetus. It is believed that endothelial cells (ECs) dysfunction initiates these diabetic complications. In this study, differences in the transcriptome profiles, cell cycle distribution, and mitochondrial superoxide (MTS) between human umbilical vein endothelial cells (HUVECs) from GDM patients and those from healthy (control) subjects were analysed. Transcriptome profiles were generated using high-density expression microarray. The selected four altered genes were validated using qRT-PCR. MTS and cell cycle were analysed by flow cytometry. A total of 84 altered genes were identified, comprising 52 upregulated and 32 downregulated genes in GDM.HUVECs. Our selection of the four interested altered genes (TGFB2, KITLG, NEK7, and IGFBP5) was based on the functional network analysis, which revealed that these altered genes are belonging to the highest enrichment score associated with cellular function and proliferation; all of which may contribute to ECs dysfunction. The cell cycle revealed an increased percentage of cells in the G2/M phase in GDM.HUVECs, indicating cell cycle arrest. In addition, we found that GDM.HUVECs had increased MTS generation. In conclusion, GDM induces persistent impairment of the biological functions of foetal ECs, as evidenced by analyses of transcriptome profiles, cell cycle, and MTS even after ECs culture in vitro for several passages under normal glucose conditions.
Subject(s)
Cell Cycle/physiology , Diabetes, Gestational/physiopathology , Human Umbilical Vein Endothelial Cells/physiology , Mitochondria/metabolism , Superoxides/metabolism , Transcriptome/physiology , Adult , Cells, Cultured , Female , Fetal Diseases/etiology , Gene Expression , Humans , Pregnancy , Saudi ArabiaABSTRACT
BACKGROUND: Follicular variant of papillary thyroid carcinoma (FVPTC) and follicular adenoma (FA) are histologically closely related tumors and differential diagnosis remains challenging. RNA expression profiling is an established method to unravel molecular mechanisms underlying the histopathology of diseases. METHODS: BRAF mutational status was established by direct sequencing the hotspot region of exon 15 in six FVPTCs and seven FAs. Whole-transcript arrays were employed to generate expression profiles in six FVPTCs, seven FAs and seven normal thyroid tissue samples. The threshold of significance for differential expression on the gene and exon level was a p-value with a false discovery rate (FDR) < 0.05 and a fold change cutoff > 2. Two dimensional average linkage hierarchical clustering was generated using differentially expressed genes. Network, pathway, and alternative splicing utilities were employed to interpret significance of expression data on the gene and exon level. RESULTS: Expression profiling in FVPTCs and FAs, all of which were negative for a BRAF mutation, revealed 55 transcripts that were significantly differentially expressed, 40 of which were upregulated and 15 downregulated in FVPTCs vs. FAs. Amongst the most significantly upregulated genes in FVPTCs were GABA B receptor, 2 (GABBR2), neuronal cell adhesion molecule (NRCAM), extracellular matrix protein 1 (ECM1), heparan sulfate 6-O-sulfotransferase 2 (HS6ST2), and retinoid X receptor, gamma (RXRG). The most significantly downregulated genes in FVPTCs included interaction protein for cytohesin exchange factors 1 (IPCEF1), G protein-coupled receptor 155 (GPR155), Purkinje cell protein 4 (PCP4), chondroitin sulfate N-acetylgalactosaminyltransferase 1 (CSGALNACT1), and glutamate receptor interacting protein 1 (GRIP1). Alternative splicing analysis detected 87 genes, 52 of which were also included in the list of 55 differentially expressed genes. Network analysis demonstrated multiple interactions for a number of differentially expressed molecules including vitamin D (1,25- dihydroxyvitamin D3) receptor (VDR), SMAD family member 9 (SMAD9), v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog (KIT), and RXRG. CONCLUSIONS: This is one of the first studies using whole-transcript expression arrays to compare expression profiles between FVPTCs and FAs. A set of differentially expressed genes has been identified that contains valuable candidate genes to differentiate both histopathologically related tumor types on the molecular level.
Subject(s)
Adenoma/genetics , Carcinoma/genetics , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , Oligonucleotide Array Sequence Analysis , Thyroid Gland/pathology , Thyroid Neoplasms/genetics , Carcinoma, Papillary , Cluster Analysis , Exons/genetics , Gene Regulatory Networks , Genes, Neoplasm , Humans , Principal Component Analysis , RNA Splicing/genetics , Thyroid Cancer, PapillaryABSTRACT
Hashimoto's thyroiditis (HT) is present in the background of around 30% of papillary thyroid carcinomas (PTCs). The genetic predisposition effect of this autoimmune condition is not thoroughly understood. We analyzed the microarray expression profiles of 13 HT, eight PTCs with (w/) coexisting HT, six PTCs without (w/o) coexisting HT, six micro PTCs (mPTCs), and three normal thyroid (TN) samples. Based on a false discovery rate (FDR)-adjusted p-value ≤ 0.05 and a fold change (FC) > 2, four comparison groups were defined, which were HT vs. TN; PTC w/ HT vs. TN; PTC w/o HT vs. TN; and mPTC vs. TN. A Venn diagram displayed 15 different intersecting and non-intersecting differentially expressed gene (DEG) sets, of which a set of 71 DEGs, shared between the two comparison groups HT vs. TN â© PTC w/ HT vs. TN, harbored the relatively largest number of genes related to immune and inflammatory functions; oxidative stress and reactive oxygen species (ROS); DNA damage and DNA repair; cell cycle; and apoptosis. The majority of the 71 DEGs were upregulated and the most upregulated DEGs included a number of immunoglobulin kappa variable genes, and other immune-related genes, e.g., CD86 molecule (CD86), interleukin 2 receptor gamma (IL2RG), and interferon, alpha-inducible protein 6 (IFI6). Upregulated genes preferentially associated with other gene ontologies (GO) were, e.g., STAT1, MMP9, TOP2A, and BRCA2. Biofunctional analysis revealed pathways related to immunogenic functions. Further data analysis focused on the set of non-intersecting 358 DEGs derived from the comparison group of HT vs. TN, and on the set of 950 DEGs from the intersection of all four comparison groups. In conclusion, this study indicates that, besides immune/inflammation-related genes, also genes associated with oxidative stress, ROS, DNA damage, DNA repair, cell cycle, and apoptosis are comparably more deregulated in a data set shared between HT and PTC w/ HT. These findings are compatible with the conception of a genetic sequence where chronic inflammatory response is accompanied by deregulation of genes and biofunctions associated with oncogenic transformation. The generated data set may serve as a source for identifying candidate genes and biomarkers that are practical for clinical application.