Microarray profiling using the Affymetrix GeneChip Human Genome U133 plus 2.0 arrays was performed to comprehensively determine global changes in transcript levels in bronchial epithelial cells following elastase treatment. Elastase caused a significant change in expression (P < 0.05, fold change 1.5) of 364 transcripts corresponding to 348 genes. Elastase affected the expression of signaling molecules including chemokines, cytokines, and receptors, as well as components of the spliceosome, transcription machinery, cell cycle and ubiquitin-mediated proteolysis.
Potent elastase inhibitors from cyanobacteria: structural basis and mechanisms mediating cytoprotective and anti-inflammatory effects in bronchial epithelial cells.
Specimen part, Treatment
View SamplesThis SuperSeries is composed of the SubSeries listed below.
The Msx1 Homeoprotein Recruits Polycomb to the Nuclear Periphery during Development.
Specimen part, Cell line
View SamplesThis SuperSeries is composed of the SubSeries listed below.
AML1/ETO oncoprotein is directed to AML1 binding regions and co-localizes with AML1 and HEB on its targets.
No sample metadata fields
View SamplesMutations of RUNX1 are detected in patients with myelodysplastic syndrome (MDS). In particular, C-terminal truncation mutations lack a transcription regulatory domain and have increased DNA binding through the runt homology domain (RHD). The expression of the RHD, RUNX1(41-214), in mouse hematopoietic cells induced progression to MDS and acute myeloid leukemia (AML). Analysis of pre-myelodysplastic animals revealed expansion of c-Kit+Sca-1+Lin- (KSL) cells and skewed differentiation to myeloid at the expense of the lymphoid lineage. These abnormalities correlate with the phenotype of Runx1-deficient animals, as expected given the reported dominant-negative role of C-terminal mutations over the full-length RUNX1. However, MDS is not observed in Runx1-deficient animals. Gene expression profiling revealed that RUNX1(41-214) KSLs have an overlapping yet distinct gene expression profile from Runx1-deficient animals. Moreover, an unexpected parallel was observed between the hematopoietic phenotype of RUNX1(41-214) and aged animals. Genes deregulated in RUNX1(41-214), but not in Runx1-deficient animals, were inversely correlated with the aging gene signature of hematopoietic stem cells (HSC), suggesting that disruption of the expression of genes related to normal aging by RUNX1 mutations contributes to development of MDS. The data presented here provide insights into the mechanisms of development of MDS in HSCs by C-terminal mutations of RUNX1.
Expression of the runt homology domain of RUNX1 disrupts homeostasis of hematopoietic stem cells and induces progression to myelodysplastic syndrome.
Specimen part
View SamplesApproximately 20% of Acute Myelogenous Leukemia (AML) cases carry the t(8;21) translocation, which involves the AML1 and ETO genes, and express the resulting AML1/ETO fusion protein that functions as a transcriptional repressor by recruiting NCoR/SMRT/HDAC complexes to DNA.
AML1/ETO oncoprotein is directed to AML1 binding regions and co-localizes with AML1 and HEB on its targets.
No sample metadata fields
View SamplesCellular dormancy and heterogeneous cell cycle lengths provide important explanations for treatment failure following adjuvant therapy with S-phase cytotoxics in colorectal cancer (CRC) yet the molecular control of the dormant versus cycling state remains unknown. In CRCs dormant cells are found to be highly clonogenic and resistant to chemotherapies. We sought to understand the molecular features of dormant CRC cells to facilitate rationale identification of compounds to target both dormant and cycling tumour cells. Overall design: Six colorectal cancer cell lines (DLD1, HCT15, HT55, SW948, RKO and SW48) were labelled with the cell permeable dye CFSE and then grown in non-adherent spheroid culture for 6 days to enable identification of dormant cells that retain CFSE (LRC) and cycling cells (BULK). LRCs and BULK populations were then FACS sorted from each cell line in quadruplicate. As a control experiment, to identify off-target effects of the CFSE dye and culture artefacts, BULK populations from DLD1 cells at d1 and d6 after seeding both with and without CFSE labelling were included in the RNAseq analysis. RNA was extracted using the RNAeasy Micro Plus kit (Qiagen) and quantified using the Qubit RNA Assay Kit (Thermo Fisher Scientific). RNA quality was assessed using the Agilent Bioanalyser system as per manufacturer's instructions. Following normalisation and sample randomisation, Truseq library (Illumina) preparation was carried out at the CRUK CI genomics facility and subsequent single end, 50bp sequencing using the HiSeq system (Illumina). Following human genome alignment (hg19), read counts were normalised and differential expression tested using the DEseq protocol.
Itraconazole targets cell cycle heterogeneity in colorectal cancer.
Specimen part, Cell line, Subject
View SamplesTwo cell lines (HT55 and SW948) were found responsive to itraconazole treatment. To identify the mode of action cells were treated with itraconazole or control (DMSO) and then subjected to RNAseq analysis once the phenotype had developed Overall design: HT55 and SW948 cells were seeded in adherent culture and treated with 5uM itraconazole or DMSO for 6 days. Cells then underwent RNA extraction using the RNAeasy Micro Plus kit (Qiagen) and quantified using the Qubit RNA Assay Kit (Thermo Fisher Scientific). RNA quality was assessed using the Agilent Bioanalyser system as per manufacturer's instructions. Following normalisation and sample randomisation, Truseq library (Illumina) preparation was carried out at the CRUK CI genomics facility and subsequent single end, 50bp sequencing using the HiSeq system (Illumina). Following human genome alignment (hg19), read counts were normalised and differential expression tested using the DEseq protocol.
Itraconazole targets cell cycle heterogeneity in colorectal cancer.
Specimen part, Cell line, Treatment, Subject
View SamplesThe objective of this study was to compare recall responses to vaccine antigens at 3 months and 9 months of age in infants who were vaccinated at birth or at 1 month.
Pneumococcal conjugate vaccination at birth in a high-risk setting: no evidence for neonatal T-cell tolerance.
Age, Specimen part, Treatment
View SamplesPrecise localization of the histone H3 variant CENP-A(Cse4) to centromeres is essential for accurate chromosome segregation. In budding yeast, CENP-A(Cse4) is regulated by ubiquitin-mediated proteolysis to ensure its exclusive localization to the centromere. Overexpression of CENP-A(Cse4) is lethal when the CENP-A(Cse4) E3 ubiquitin ligase, Psh1, is deleted. CENP-A(Cse4) mislocalizes to promoters in this condition, so we investigated if there was an effect on gene expression of downstream genes using RNA-seq. Overall design: RNA-seq from two or three biological replicates each, at t0 and t2 hours after adding galactose for each of 6 experimental genotypes.
Regulation of Budding Yeast CENP-A levels Prevents Misincorporation at Promoter Nucleosomes and Transcriptional Defects.
Subject, Time
View SamplesRegulatory CD4+ T cells (Tregs) are functionally distinct from conventional CD4+ T cells (Tconvs). To understand Treg identity, we have compared by proteomics and transcriptomics human naïve (n) and effector (e)Tregs, Tconvs and transitional FOXP3+ cells. Among these CD4+ T cell subsets, we detected differential expression of 421 proteins and 640 mRNAs, with only 48 molecules shared. Fifty proteins discriminated Tregs from Tconvs. This common Treg protein signature indicates altered signaling by TCR-, TNF receptor-, NFkB-, PI3 kinase/mTOR-, NFAT- and STAT pathways and unique cell biological and metabolic features. Another protein signature uniquely identified eTregs and revealed active cell division, apoptosis sensitivity and suppression of NFkB- and STAT signaling. eTreg fate appears consolidated by FOXP3 outnumbering its partner transcription factors. These features explain why eTregs cannot produce inflammatory cytokines, while transitional FOXP3+ cells can. Our collective data reveal that Tregs protect their identity by a unique “wiring” of signalling pathways Overall design: mRNA profiles of 5 CD4+ T cell populations were generated by deep sequencing, in triplicate
Proteomic Analyses of Human Regulatory T Cells Reveal Adaptations in Signaling Pathways that Protect Cellular Identity.
Subject
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