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accession-icon SRP186406
A temporal proteogenomic atlas of HCV-host interactions unravels cell circuits driving viral and metabolic liver disease.
  • organism-icon Homo sapiens
  • sample-icon 63 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Background and aims: Hepatitis C virus (HCV) infection is a major cause of liver disease including steatosis, fibrosis and liver cancer. Viral cure cannot fully eliminate the risk of disease progression and hepatocellular carcinoma (HCC) in advanced liver disease. The mechanisms for establishment of infection, liver disease progression and hepatocarcinogenesis are only partially understood. To address these questions, we probed the functional proteogenomic architecture of HCV infection within a hepatocyte-model. Methods: Time-resolved HCV infection of hepatocyte-like cells was analyzed by RNA sequencing, proteomics, metabolomics, and leveraged by integrative genomic analyses. Using differential expression, gene set enrichment analyses, and protein-protein interaction mapping we identified pathways relevant for liver disease pathogenesis that we validated in livers of 216 cirrhotic patients with HCV. Results: We uncovered marked changes in the protein expression of gene sets involved in innate immunity, metabolism and hepatocarcinogenesis. In infected cells, HCV enhances glucose metabolism and creates a Warburg-like shift of the lactate flux. HCV infection impaired the formation of peroxisomes -organelles required for long-chain fatty acid oxidation- causing intracellular fatty acid accumulation, which is a hallmark of non-alcoholic fatty liver disease (NAFLD). Ex vivo studies confirmed perturbed peroxisomes and revealed an association of hepatic catalase expression with clinical outcomes and phenotypes in HCV-associated cirrhosis, NAFLD and HCC cohorts. Conclusion: Our integrative analyses uncover how HCV perturbs the hepatocyte cell circuits to drive chronic liver disease and hepatocarcinogenesis. This proteogenomic atlas of HCV infection provides a model for the discovery of novel drivers for viral- and non-viral induced liver disease. Overall design: mRNA profiles of either mock or HCV-infected Huh7.5.1dif cells, performed in triplicates and collected every day between days 0 and 10 post infection. HCV infection reached plateau at day 7 post infection (pi). After day 7 pi unspecific effects cannot be excluded.

Publication Title

Combined Analysis of Metabolomes, Proteomes, and Transcriptomes of Hepatitis C Virus-Infected Cells and Liver to Identify Pathways Associated With Disease Development.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE43270
Genome wide-DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge IconIllumina HumanMethylation27 BeadChip (HumanMethylation27_270596_v.1.2), Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Genome-wide DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

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accession-icon GSE43191
Genome wide-DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients (gene expression)
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge IconIllumina HumanMethylation27 BeadChip (HumanMethylation27_270596_v.1.2), Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

The aim of this study is to identify, for the first time, the genome-wide DNA methylation profiles of human articular chondrocytes from OA and healtly cartilage samples.

Publication Title

Genome-wide DNA methylation analysis of articular chondrocytes reveals a cluster of osteoarthritic patients.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

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accession-icon GSE43794
Differentiation of human fetal multipotential neural progenitor cells to astrocytes reveals susceptibility factors for JC Virus
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Viral infections of the CNS are of increasing concern, especially among immunocompromised populations. Rodent models are often inappropriate for studies of CNS infection, as many viruses, including JC Virus (JCV) and HIV, cannot replicate in rodent cells. Consequently, human fetal brain-derived multipotential CNS progenitor cells (NPCs) that can be differentiated into neurons, oligodendrocytes, or astrocytes, have served as a model for CNS studies. NPCs can be non-productively infected by JCV, while infection of progenitor-derived astrocytes (PDAs) is robust. We profiled cellular gene expression at multiple times during differentiation of NPCs to PDAs. Several activated transcription factors show commonality between cells of the brain in which JCV replicates and lymphocytes in which JCV is likely latent. Bioinformatic analysis determined transcription factors that may influence the favorable transcriptional environment for JCV in PDAs. This study attempts to provide a framework for understanding the functional transcriptional profile necessary for productive JCV infection.

Publication Title

Differentiation of human fetal multipotential neural progenitor cells to astrocytes reveals susceptibility factors for JC virus.

Sample Metadata Fields

Specimen part, Time

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accession-icon GSE12172
Common activation of RAS_MAPK pathway in serous LMP tumours
  • organism-icon Homo sapiens
  • sample-icon 83 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Expression profile of 30 LMP tumours and 60 Serous tumours were compared to identify the biolgical pathways specific to these groups. Genotyping was done to identify the mutations potentially causing these phenotypes

Publication Title

Mutation of ERBB2 provides a novel alternative mechanism for the ubiquitous activation of RAS-MAPK in ovarian serous low malignant potential tumors.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE58841
Effect of HPV 16 E6, E7 oncoproteins on the expression level of cellular genes
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The life cycle of human papillomaviruses (HPV) is strictly linked to the differentiation of their natural host cells. The HPV E6 and E7 oncoproteins can delay the normal differentiation program of keratinocytes, however, the exact mechanisms responsible for this have not yet been identified. The goal of this study was to investigate the effects of HPV16 oncoproteins on the expression of genes involved in keratinocyte differentiation. Primary human keratinocytes transduced by LXSN (control) retroviruses or virus vectors expressing HPV16 E6, E7 or E6/E7 genes were subjected to gene expression profiling. The results of microarray analysis showed that HPV 16 E6 and E7 have the capacity to down-regulate the expression of several genes involved in keratinocyte differentiation. Quantitative real-time polymerase chain reaction (qRT-PCR) assays were performed to confirm microarray data. To investigate the effects of the HPV oncoproteins on the promoters of selected keratinocyte differentiation genes, luciferase reporter assays were performed. Our results suggest that the HPV 16 E6 and/or E7 oncogenes are able to down-regulate the expression of several genes involved in keratinocyte differentiation, at least partially by down-regulating their promoter activity. This activity of the HPV oncoproteins may have a role in the productive virus life cycle, and also in virus induced carcinogenesis.

Publication Title

Transcriptional regulation of genes involved in keratinocyte differentiation by human papillomavirus 16 oncoproteins.

Sample Metadata Fields

Specimen part

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accession-icon GSE9899
Expression profile of ovarian tumour samples
  • organism-icon Homo sapiens
  • sample-icon 292 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE9891
Expression profile of 285 ovarian tumour samples
  • organism-icon Homo sapiens
  • sample-icon 282 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarrays to profile the expression levels of 285 ovarian samples in order to identify molecular subtypes of the tumour

Publication Title

Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE9890
Expression profile of 5 ovarian tumour samples (two different cell types from each sample profiles)
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarrays to profile the expression levels of 5 tumour samples

Publication Title

Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE45639
Clonal Immortalized Human Glial Cell Lines Support Varying Levels of JC Virus Infection due to Differences in Cellular Gene Expression
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

JC virus (JCV) is a ubiquitous human polyomavirus that causes the demyelinating disease Progressive Multifocal Leukoencephalopathy (PML). JCV replicates in limited cell types in culture, predominantly in human glial cells. Thus, productive JCV infection is an indicator of the host cell transcription environment. Following introduction of a replication defective SV40 mutant that expressed large T protein into a heterogeneous culture of human fetal brain cells, multiple phenotypes became immortalized (SVG cells). A subset of SVG cells could support JCV replication. This mixed culture was called SVG cells. In the current study, clonal cell lines were selected from the original SVG cell culture. The SVG-5F4 clone showed low levels of viral growth. The SVG-10B1 clone was highly permissive for JCV DNA replication and gene expression. Microarray analysis revealed that viral infection did not significantly change gene expression in these cells. More resistant 5F4 cells expressed high levels of transcription factors known to inhibit JCV transcription. Interestingly, 5F4 cells highly expressed RNA of markers of Bergman or radial glia and 10B1 cells had high expression of markers of immature glial cells and activation of transcription regulators important for stem/progenitor cell self-renewal. These SVG-derived clonal cell lines provide a biologically relevant model to investigate cell type differences in JCV host range and pathogenesis, as well as neural development.

Publication Title

Clonal immortalized human glial cell lines support varying levels of JC virus infection due to differences in cellular gene expression.

Sample Metadata Fields

Specimen part, Time

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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