Liver differentially expressed genes between microsomic and control inbred mice at birth
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE49876 | GEO | 2014/06/04
SECONDARY ACCESSION(S): PRJNA215225
REPOSITORIES: GEO
Similar Datasets
Project description:To understand the processes involved in the natural development of microsomic imbred mice, a whole genome microarray expression profiling of mouse liver was performed. Total RNA of liver from C57BL/6J microsomic mice of both sexes were extracted and compared with total RNA of liver from normal (control) mice of both sexes.
2014-06-04 | E-GEOD-49876 | biostudies-arrayexpress
Project description:Hepatocellular carcinoma (HCC) is a cancer with global impact and largely refractory to current treatments. Novel treatment options are therefore urgently needed. LncRNAs play important regulatory roles in HCCs and are emerging as promising therapeutic options against HCC. We identified TP53TG1 as a promising tumor suppressor LncRNA. To understand TP53TG1 target genes and the mechanisms, we performed mRNA expression profiling in TP53TG1-overexpressing Huh7 cells and negative control.
2021-06-14 | GSE166284 | GEO
Project description:Osteocytes represent the most abundant cellular component of mammalian bones with important functions in bone mass maintenance and remodeling. To elucidate the differential gene expression between osteoblasts and osteocytes we completed a comprehensive analysis of their gene profiles. Selective identification of these two mature populations was achieved by utilization of visual markers of bone lineage cells. We have utilized dual GFP reporter mice in which osteocytes are expressing GFP (topaz) directed by the DMP1 promoter, while osteoblasts are identified by expression of GFP (cyan) driven by 2.3 kb of the Col1a1 promoter. Histological analysis of 7-day-old neonatal calvaria confirmed the expression pattern of DMP1GFP in osteocytes and Col2.3 in osteoblasts and osteocytes. To isolate distinct populations of cells we utilized fluorescent activated cell sorting (FACS). Cell suspensions were subjected to RNA extraction, in vitro transcription and labeling of cDNA and gene expression was analyzed using the Illumina WG-6v1 BeadChip. Following normalization of raw data from four biological replicates, 3444 genes were called present in all three sorted cell populations: GFP negative, Col2.3cyan(+) (osteoblasts), and DMP1topaz(+) (preosteocytes and osteocytes). We present the genes that showed in excess of a 2-fold change for gene expression between DMP1topaz(+) and Col2.3cyan(+) cells. The selected genes were classified and grouped according to their associated gene ontology terms. Genes clustered to osteogenesis and skeletal development such as Bmp4, Bmp8a, Dmp1, Enpp1, Phex and Ank were highly expressed in DMP1topaz(+)cells. Most of the genes encoding extracellular matrix components and secreted proteins had lower expression in DMP1topaz(+) cells, while most of the genes encoding plasma membrane proteins were increased. Interestingly a large number of genes associated with muscle development and function and with neuronal phenotype were increased in DMP1topaz(+) cells, indicating some new aspects of osteocyte biology. Although a large number of genes differentially expressed in DMP1topaz(+) and Col2.3cyan(+) cells in our study have already been assigned to bone development and physiology, for most of them we still lack any substantial data. Therefore, isolation of osteocyte and osteoblast cell populations and their subsequent microarray analysis allowed us to identify a number or genes and pathways with potential roles in regulation of bone mass.
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Project description:BackgroundEvidence is accumulating to characterise the key differences between systemic sclerosis (SSc) and rheumatoid arthritis (RA), which are similar but distinct systemic autoimmune diseases. However, the differences at the genetic level are not yet clear. Therefore, the aim of the present study was to identify key differential genes between patients with SSc and RA.MethodsThe Gene Expression Omnibus database was used to identify differentially expressed genes (DEGs) between SSc and RA biopsies. The DEGs were then functionally annotated using Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways with the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools. A protein-protein interaction (PPI) network was constructed with Cytoscape software. The Molecular Complex Detection (MCODE) plugin was also used to evaluate the biological importance of the constructed gene modules.ResultsA total of 13,556 DEGs were identified between the five SSc patients and seven RA patients, including 13,465 up-regulated genes and 91 down-regulated genes. Interestingly, the most significantly enriched GO terms of up- and down-regulated genes were related to extracellular involvement and immune activity, respectively, and the top six highly enriched KEGG pathways were related to the same processes. In the PPI network, the top 10 hub nodes and top four modules harboured the most relevant genes contributing to the differences between SSc and RA, including key genes such as IL6, EGF, JUN, FGF2, BMP2, FOS, BMP4, LRRK2, CTNNB1, EP300, CD79, and CXCL13.ConclusionsThese genes such as IL6, EGF, JUN, FGF2, BMP2, FOS, BMP4, LRRK2, CTNNB1, EP300, CD79, and CXCL13 can serve as new targets for focused research on the distinct molecular pathogenesis of SSc and RA. Furthermore, these genes could serve as potential biomarkers for differential diagnoses or therapeutic targets for treatment.
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Project description:The miR-371~373 cluster is a suspected repressor of colon cancer initiation and progression. To better understand its role in metastasis initiation, we used microarray expression analysis to identify potential target genes of this miRNA cluster Potential target genes were defined as significantly downregulated genes after stable overexpression of the miR-371~373 cluster
2018-07-23 | GSE102001 | GEO
Project description:Liver Hepatocellular Carcinoma (LIHC), a malignant tumor with high incidence and mortality, is one of the most common cancers in the world. Multiple studies have found that the aberrant expression of rhythm genes is closely related to the occurrence of LIHC. This study aimed to use bioinformatics analysis to identify differentially expressed rhythm genes (DERGs) in LIHC. A total of 563 DERGs were found in LIHC, including 265 downregulated genes and 298 upregulated genes. KEGG pathway enrichment and GO analyses showed that DERGs were significantly enriched in rhythmic and metabolic processes. Survival analysis revealed that high expression levels of CNK1D, CSNK1E, and NPAS2 were significantly associated with the low survival rate in LIHC patients. Through cell experiment verification, the mRNA expression levels of CSNK1D, CSNK1E, and NPAS2 were found to be strongly upregulated, which was consistent with the bioinformatics analysis of LIHC patient samples. A total of 23 nodes and 135 edges were involved in the protein-protein interaction network of CSNK1D, CSNK1E, and NPAS2 genes. Clinical correlation analyses revealed that CSNK1D, CSNK1E, and NPAS2 expression levels were high-risk factors and independently connected with the overall survival rate in LIHC patients. In conclusion, the identification of these DERGs contributes to the exploration of the molecular mechanisms of LIHC occurrence and development and may be used as diagnostic and prognostic biomarkers and molecular targets for chronotherapy in LIHC patients in the future.
| S-EPMC8211427 | biostudies-literature
Project description:Berberine has been identified with anti-proliferative effects on various cancer cells. Many researchers have been trying to elucidate the anti-cancer mechanisms of berberine based on differentially expressed genes. However, differentially alternative splicing genes induced by berberine might also contribute to its pharmacological actions and have not been reported yet. Moreover, the potential functional cross-talking between the two sets of genes deserves further exploration. In this study, RNA-seq technology was used to detect the differentially expressed genes and differentially alternative spliced genes in BEL-7402 cancer cells induced by berberine. Functional enrichment analysis indicated that these genes were mainly enriched in the p53 and cell cycle signalling pathway. In addition, it was statistically proven that the two sets of genes were locally co-enriched along chromosomes, closely connected to each other based on protein-protein interaction and functionally similar on Gene Ontology tree. These results suggested that the two sets of genes regulated by berberine might be functionally cross-talked and jointly contribute to its cell cycle arresting effect. It has provided new clues for further researches on the pharmacological mechanisms of berberine as well as the other botanical drugs.
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Project description:To provide further insight to the signaling pathways deregulated by SPOP mutation and determine the relevance of these models to human prostate cancer, we performed RNA-seq on SPOP mutant organoids and controls. RNA-seq reads mapped to human and mouse SPOP confirmed appropriate expression of the F133V transgenic transcript without overexpression compared to endogenous mouse Spop. Quantification of gene expression was performed via RSEQtools using GENCODE as reference gene–annotation set. Both SPOPmut and SPOPwt were done in the same run. S0 was done in first run; S1 and S2 were done in second run. S3, S4 and S5 were done in third run. S5mut and S5wt were excluded from differentially expressed genes analysis, due to the different mouse line.
2017-03-13 | GSE94839 | GEO
Project description:Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world. Liver transplantation (LT) represents a curative treatment for "small" HCC. Preoperative staging is critical in selecting optimal candidates for LT to optimize the use of this scarce resource. From December 1997 to February 2004, 148 patients diagnosed with cirrhosis and HCC were evaluated at our center. After staging, the patients were listed for LT according to United Network for Organ Sharing (UNOS) criteria. When pretransplant liver MRIs were compared with the findings of the explanted livers, 8 of 35 patients (22.8%) were understaged. Three of the 8 patients (37.5%) had recurrence post-LT. A retrospective gene expression profiling study was done using microarray technology for tumor samples in the pretransplant hepatitis C virus (HCV)-HCC understaged patients and in a contemporaneous group of HCV-HCC patients that were accurately staged. Two sample t tests comparing the early versus advanced HCV-HCCs with respect to gene expression showed an important set of genes differentially expressed among the samples. Hierarchical clustering analysis of the gene expression profiling classified 93.8% of the total tumor samples and 85.7% of the understaged samples in concordance with the explanted pathological staging. We found a distinctive pattern of gene expression between early and advanced HCV-HCCs. These results suggest that gene expression profiling could improve the pre-LT HCC staging to more closely mimic the explant pathology. Whether gene expression profiling of HCC will be refined to the point of predicting potential metastatic biologic behavior to predict post-LT recurrence will require longitudinal prospective study of this gene array technology.
| S-EPMC1578766 | biostudies-literature
Project description:BackgroundExosomes are involved in cell-to-cell communication, neovascularization, cancer metastasis, and drug resistance, which all play an important role in the occurrence and progression of hepatocellular carcinoma (HCC). Because there are few mechanistic studies about the function of exosomes in HCC, the goals of this study were to identify exosome-related genes in HCC, to establish a reliable prognostic model for HCC, and to explore underlying mechanisms.MethodsThe exoRBase and The Cancer Genome Atlas (TCGA) databases were used to analyze differentially expressed genes (DEGs). Cox regression and least absolute shrinkage and selection operator analyses were used to identify DEGs closely related to the overall survival of patients with HCC. An exosome-related prognostic model was then constructed in TCGA and validated in the International Cancer Genome Consortium database. A nomogram was developed to predict survival. CIBERSORT was used to estimate the abundance of different types of immune cells. Immunotherapy-related DEGs were used to predict the effect of immunotherapy.ResultsForty-eight exosome-related DEGs were obtained; of them, five [exportin 1 (XPO1), lysosomal thiol reductase (IFI30), F-box protein 16 (FBXO16), calmodulin 1 (CALM1), MORC family CW-type zinc finger 3 (MORC3)] were selected to construct a predictive model. Patients with HCC were then divided into low- and high-risk groups using the best cut-off value, as determined by the X-tile software. Prognosis was significantly poorer in the high-risk than in the low-risk group (P=0.009; hazard ratio =2.65). Features related to exosomes were found to positively regulate immune response. Further analysis showed a higher risk score was associated with higher expression of immune checkpoint molecules, including programmed death ligand 1 (PD-L1), programmed death ligand 2 (PD-L2), T cell Ig and ITIM domain (TIGIT), and indoleamine-2,3-dioxygenase 1 (IDO1).ConclusionsThis study has identified a novel signature based on exosome-related genes that has potential as a prognostic biomarker for HCC. Our research provides an immunological perspective for the development of precision treatment for HCC.
| S-EPMC9403937 | biostudies-literature