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GSE53795
Homo sapiens
24 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The mechanisms of inflammation in acne are not well understood. This study performed in two separate patient populations focused on the activation of adaptive and innate immunity in early inflamed acne. Biopsies were collected from lesional and non-lesional skin of acne patients. Psoriasis patients and healthy volunteers were included in the study for comparison (not included in the records). Using Affymetrix Genechips, we observed significant elevation of the signature cytokines of the Th17 lineage in acne lesions compared to non-lesional skin. The increased expression of IL-17 was confirmed with real-time qPCR (RT-PCR) in two separate patient populations. Cytokines involved in Th17 lineage differentiation (IL-1beta, IL-6, TGF-beta; IL23p19) were remarkably induced at the RNA level. In addition, pro-inflammatory cytokines (IL-8, TNF-), Th1 markers (IL12p40, CXCR3, T-bet, IFN-gamma), T regulatory cell markers (Foxp3, IL-10, TGF-) and antimicrobial peptides (S100A7, S100A9, LNC2, hBD2, hBD3, hCAP18) were induced. Importantly, immunohistochemistry revealed significantly increased numbers of IL-17A positive T cells and CD83 dendritic cells in the acne lesions. In summary our results demonstrate the presence of IL17A positive T cells and the activation of Th17-related cytokines in acne lesions, indicating that the Th17 pathway may play a pivotal role in the disease process, offering new targets of therapy.
Publication Title
IL-17/Th17 pathway is activated in acne lesions.
Sample Metadata Fields
Specimen part
View Samples- Arabidopsis thaliana
- 9 Downloadable Samples
- Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
Inflorescence architecture of Arabidopsis thaliana is regulated by ER-EPFL4/6 signaling module. To analyze the genes governed by this module, the transcriptional profiles of er-2 (allelic to er-106) mutant and epfl4 epfl6 double mutant were investigeted.
Publication Title
Regulation of inflorescence architecture by intertissue layer ligand-receptor communication between endodermis and phloem.
Sample Metadata Fields
Age, Specimen part
View Samples- Sus scrofa
- 8 Downloadable Samples
Illumina HiSeq 2500
Description
Gene expression was examined in granulosa cells and oocytes in various stage of follicle and in vitro grown oocytes and granulosa cells complexes in sus scrofa.
Publication Title
Gene expression patterns in granulosa cells and oocytes at various stages of follicle development as well as in in vitro grown oocyte-and-granulosa cell complexes.
Sample Metadata Fields
Specimen part
View Samples- Arabidopsis thaliana
- 14 Downloadable Samples
- Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
Lateral root initiation was used as a model system to study the mechanisms behind auxin-induced cell division. Genome-wide transcriptional changes were monitored during the early steps of lateral root initiation. Inclusion of the dominant auxin signaling mutant solitary root1 (slr1) identified genes involved in lateral root initiation that act downstream of the AUX/IAA signaling pathway. Interestingly, key components of the cell cycle machinery were strongly defective in slr1, suggesting a direct link between AUX/IAA signaling and core cell cycle regulation. However, induction of the cell cycle in the mutant background by overexpression of the D-type cyclin (CYCD3;1) was able to trigger complete rounds of cell division in the pericycle that did not result in lateral root formation. Therefore, lateral root initiation can only take place when cell cycle activation is accompanied by cell fate respecification of pericycle cells. The microarray data also yielded evidence for the existence of both negative and positive feedback mechanisms that regulate auxin homeostasis and signal transduction in the pericycle, thereby fine-tuning the process of lateral root initiation.
Publication Title
Cell cycle progression in the pericycle is not sufficient for SOLITARY ROOT/IAA14-mediated lateral root initiation in Arabidopsis thaliana.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 56 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Multi-omics study was conducted to elucidate the crucial molecular mechanisms of primary Sjgrens syndrome (SS) pathology. We generated multiple data set from well-defined patients with SS, which includes whole-blood transcriptomes, serum proteomes and peripheral immunophenotyping. Based on our newly generated data, we performed an extensive bioinformatic investigation. Our integrative analysis identified SS gene signatures (SGS) dysregulated in widespread omics layers, including epigenomes, mRNAs and proteins. SGS predominantly involved the interferon signature and ADAMs substrates. Besides, SGS was significantly overlapped with SS-causing genes indicated by a genome-wide association study and expression trait loci analyses. Combining the molecular signatures with immunophenotypic profiles revealed that cytotoxic CD8 T cells were associated with SGS. Further, we observed the activation of SGS in cytotoxic CD8 T cells isolated from patients with SS. Our multi-omics investigation identified gene signatures deeply associated with SS pathology and showed the involvement of cytotoxic CD8 T cells. These integrative relations across multiple layers will facilitate our understanding of SS at the system level.
Publication Title
Multiomic disease signatures converge to cytotoxic CD8 T cells in primary Sjögren's syndrome.
Sample Metadata Fields
Sex, Age, Specimen part, Disease
View Samples- Homo sapiens
- 48 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Multi-omics study was conducted to elucidate the crucial molecular mechanisms of primary Sjgrens syndrome (SS) pathology. We generated multiple data set from well-defined patients with SS, which includes whole-blood transcriptomes, serum proteomes and peripheral immunophenotyping. Based on our newly generated data, we performed an extensive bioinformatic investigation. Our integrative analysis identified SS gene signatures (SGS) dysregulated in widespread omics layers, including epigenomes, mRNAs and proteins. SGS predominantly involved the interferon signature and ADAMs substrates. Besides, SGS was significantly overlapped with SS-causing genes indicated by a genome-wide association study and expression trait loci analyses. Combining the molecular signatures with immunophenotypic profiles revealed that cytotoxic CD8 T cells were associated with SGS. Further, we observed the activation of SGS in cytotoxic CD8 T cells isolated from patients with SS. Our multi-omics investigation identified gene signatures deeply associated with SS pathology and showed the involvement of cytotoxic CD8 T cells. These integrative relations across multiple layers will facilitate our understanding of SS at the system level.
Publication Title
Multiomic disease signatures converge to cytotoxic CD8 T cells in primary Sjögren's syndrome.
Sample Metadata Fields
Sex, Specimen part, Disease, Disease stage, Subject
View Samples- Homo sapiens
- 36 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Multi-omics study was conducted to elucidate the crucial molecular mechanisms of primary Sjgrens syndrome (SS) pathology. We generated multiple data set from well-defined patients with SS, which includes whole-blood transcriptomes, serum proteomes and peripheral immunophenotyping. Based on our newly generated data, we performed an extensive bioinformatic investigation. Our integrative analysis identified SS gene signatures (SGS) dysregulated in widespread omics layers, including epigenomes, mRNAs and proteins. SGS predominantly involved the interferon signature and ADAMs substrates. Besides, SGS was significantly overlapped with SS-causing genes indicated by a genome-wide association study and expression trait loci analyses. Combining the molecular signatures with immunophenotypic profiles revealed that cytotoxic CD8 T cells were associated with SGS. Further, we observed the activation of SGS in cytotoxic CD8 T cells isolated from patients with SS. Our multi-omics investigation identified gene signatures deeply associated with SS pathology and showed the involvement of cytotoxic CD8 T cells. These integrative relations across multiple layers will facilitate our understanding of SS at the system level.
Publication Title
Multiomic disease signatures converge to cytotoxic CD8 T cells in primary Sjögren's syndrome.
Sample Metadata Fields
Sex, Specimen part, Disease, Subject
View Samples- Homo sapiens
- 448 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations. However, it remains challenging to distinguish between background, or passenger and causal, or driver cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. These complementary approaches together result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer.
Publication Title
Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 286 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Multi-omics monitoring of drug response in rheumatoid arthritis in pursuit of molecular remission.
Sample Metadata Fields
Sex, Age, Specimen part, Disease, Disease stage, Subject
View Samples- Homo sapiens
- 238 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Sustained clinical remission (CR) without drug treatment has not been achieved in patients with rheumatoid arthritis (RA). This implies a substantial difference between CR and the healthy state, but it has yet to be quantified. We report a longitudinal monitoring of the drug response at multi-omics levels in the peripheral blood of patients with RA. Our data reveal that drug treatments alter the molecular profile closer to that of HCs at the transcriptome, serum proteome and immunophenotype level. Patient follow-up suggests that the molecular profile after drug treatments is associated with long-term stable CR. In addition, we identify molecular signatures that are resistant to drug treatments. These signatures are associated with RA independently of known disease severity indexes and are largely explained by the imbalance of neutrophils, monocytes, and lymphocytes. This high-dimensional phenotyping provides a quantitative measure of molecular remission and illustrates a multi-omics approach to understanding drug response.
Publication Title
Multi-omics monitoring of drug response in rheumatoid arthritis in pursuit of molecular remission.
Sample Metadata Fields
Sex, Age, Specimen part, Disease, Disease stage, Subject
View Samples