We analyzed three clinical parameters with gene expression data from 122 liver tissues. Six healthy samples were used in validation.
Predictive model for inflammation grades of chronic hepatitis B: Large-scale analysis of clinical parameters and gene expressions.
Specimen part
View SamplesIRF9 is ubiquitously expressed and mediates the effects of IFNs, previous study showed that IRF9 played an important role in immunity and cell fate decision. Our recent study revealed that IRF9 involved in cardiac hypertrophy, hepatic steatosis and insulin resistance. However, the function of IRF9 in VSMC and neointima formation was largely unknown. We found that IRF9 expression was significantly increased in the VSMCs of mouse carotid artery. More importantly, we generated SMC-specific IRF9 overexpression transgenic mice (IRF9 TG) and found that IRF9 TG significantly increased VSMC proliferation, migration and neointima formation compared with NTG mice in response to injury. To evaluate the underlying mechanism by which IRF9 promotes VSMC proliferation and migration after vascular injury, IRF9 TG and NTG mice were subjected to wire-injury and the carotid arteries were collected at 14 days post-injury. We combined 3-5 vessels for one sample, and 3 samples for each phenotype. Subsequently, a total of 400ng RNA was used following Affymetrix instruction and 10 ug of cRNA were hybridized for 16 hr at 45. GeneChips were scanned using the Scanner 7G and the data was analyzed with Expression Console using Affymetrix default analysis settings and global scaling as normalization method. RMA analysis was employed to evaluate the gene expression.
Interferon regulatory factor 9 is critical for neointima formation following vascular injury.
Specimen part
View SamplesHepatitis B virus (HBV) infection is a leading risk factor for liver fibrosis (LF) and hepatocellular carcinoma. Emerging evidence indicates that host genetic, virological and immunological factors will influence the fibrotic progress. Many previous studies have focused on specific pathways or genes included in LF mechanism, however global view of the whole genome expresion profile in HBV related LF patients never been studied, and the mechanisms underlying the promotion of liver fibrosis progression remain obscure. Here we collected liver biopsy samples from 124 chronic hepatitis B (CHB) patients and used Affymetrix HG U133 Plus 2.0 microarray to quantify the transcriptome of these patients. Through integrated data analysis, including geneset enrichment analysis (GSEA), weighted gene co-expression analysis (WGCNA), differential expressed gene (DEG) screening, trend test, principle component analysis (PCA) etc., we identified several key pathways and hub genes participated in the initiation and exacerbation of liver fibrotic progress. The function of these hub genes were also validated by in vitro and in vivo experiments using HepG2, Huh7 and LX-2 cell lines and transgenic mice. This is the first large-scale study investigating the gene expression profile in HBV-related LF patients which will be crucial for unlocking the gene functions and gene-gene correlations in fibrosis progess.
Characterization of gene expression profiles in HBV-related liver fibrosis patients and identification of ITGBL1 as a key regulator of fibrogenesis.
Sex, Age, Specimen part
View SamplesRetinal degeneration often affects the whole retina even though the disease-causing gene is specifically expressed in the light-sensitive photoreceptors. These retinal defects can potentially be determined by gene-expression profiling of the whole retina. In this study, we measured the gene-expression profile of retinas microdissected from a zebrafish pde6cw59 (pde6c) mutant. Its retinas display not only photoreceptor degeneration but also issues in other cell types starting from 4 days postfertilization (dpf). To capture these initial changes, we subjected pde6c and wild-type (WT) retinas at 5 dpf to RNA sequencing (RNA-Seq) on the Illumina HiSeq 2000 platform. The sequencing analyses indicate that the RNA-Seq dataset was of high quality. We also validated the RNA-Seq results by Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) of seven phototransduction genes. We found that the fold changes of these genes measured by RT-qPCR highly correlated to those measured by RNA-Seq. Therefore, our RNA-Seq dataset likely captures the molecular changes in the whole pde6c retina. This dataset will facilitate the characterization of the molecular defects in the pde6c retina at the initial stage of retinal degeneration Overall design: 3 samples of pde6c mutant and 3 samples of wild type animals are analyzed.
Expression profiling of the retina of pde6c, a zebrafish model of retinal degeneration.
No sample metadata fields
View SamplesWe have used RNA-seq to examine circular RNAs from poly(A)- and poly(A)-/RNaseR RNAs in human PA1 cells Overall design: In order to identify novel circular RNAs from PA1 cells
Diverse alternative back-splicing and alternative splicing landscape of circular RNAs.
No sample metadata fields
View SamplesChinese lung adenocarcinomas exon-level expression
A novel PHD-finger protein 14/KIF4A complex overexpressed in lung cancer is involved in cell mitosis regulation and tumorigenesis.
Specimen part
View SamplesChinese lung ADC adjacent normal sample exon-level expression
A novel PHD-finger protein 14/KIF4A complex overexpressed in lung cancer is involved in cell mitosis regulation and tumorigenesis.
Specimen part
View SamplesReprogramming metabolism plays an important role in tumor cells for maintaining their abnormal biologic behaviors. Therefore, special factors could regulate metabolic processes and influence the overall status of tumor cells. This phenomenon was obviously found in melanoma. Fumarylacetoacetate hydrolase (fumarylacetoacetase, FAH) is an enzyme encoded by the FAH gene located on the chromosome 15q25.1 region and contains 14 exons. FAH enzyme catalyzes the hydrolysis of 4- fumarylacetoacetase into fumarate and acetoacetate. It is the last enzyme in the subpathway from L-phenylalanine and tyrosine degradation. Mutations in the FAH gene cause type I tyrosinemia, which is a hereditary error of metabolism that is characterized by increased tyrosine levels in the blood and urine of patients. In the present study, we will explore whether FAH is an essential enzyme to promote multiple metabolic processes and elucidate the functions of FAH in melanoma. Gene microarrays and bioinformatics analysis of the differentially expressed genes (DEGs) were performed using A375 cells, and we concentrated on the biologic functions of FAH. In general, our work revealed several functional mechanisms of FAH in melanoma, which indicated FAH might be a potentially therapeutic target and an independent prognostic indicator for this disease.
CDC5L drives FAH expression to promote metabolic reprogramming in melanoma.
Cell line
View SamplesThe goals of this study is to compare the whole genome transcriptome of gefitinib-resistant NSCLC cell line (PC9R) with its gefitinib-sensitive counterpart (PC9) using RNA-seq tecnology Methods: Genome-wide mRNA profiles of the PC9R and PC9 cells were generated by deep sequencing, using Illumina Hiseq2000. The sequence reads that passed quality filters were analyzed in the following steps: 1) RNA-seq reads were aligned to the hg19 genome assembly using TopHat (http://bioinformatics.oxfordjournals.org/content/25/9/1105.short) with the default parameters; 2) Expression index was generated using GFOLD V1.0.9 job count (http://bioinformatics.oxfordjournals.org/content/early/2012/08/23/bioinformatics.bts515); 3) Differential expression were calculated using GFOLD V1.0.9 job diff. Gene expression was quantified in rpkm (reads per kilobase of exon per million mapped sequence reads); 4) GFOLD, a generalized fold change, was used to rank the differentially expressed genes from the RNA-seq data. The GFOLD value can be considered as a reliable log2-fold change when only a single biological replicate is available Results: We found that hundreds of genes were either down- or up-regulated in the PC9R cells compared with the PC9 cells. Specifically, 6% of the total detected genes (1487 genes) were up-regulated in the PC9R cells, with a GFOLD value over 1, and 5% of the total detected genes (1112 genes) were down-regulated, with a GFOLD value less than -1. Conclusions: Our study reveals the differentially expressed genes in gefitinib-resistant NSCLC cells comparing with the sensitive cells in a genome-wide scale. This results help to provide the novel insight into the gefitinib-resistant mechanism. Overall design: The genome-wdie transcriptome study of gefitinib-resistant NSCLC cells (PC9R) comparing with the sensitive cells (PC9) using mRNA-seq technology
ERK inhibition represses gefitinib resistance in non-small cell lung cancer cells.
No sample metadata fields
View SamplesWe used microarrays to detail the global gene expression in dendritic cells transfected with piNC or td-piR(Glu)
IL-4 Inhibits the Biogenesis of an Epigenetically Suppressive PIWI-Interacting RNA To Upregulate CD1a Molecules on Monocytes/Dendritic Cells.
Specimen part
View Samples