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A systems biology approach identifies ANP32E and other biomarkers of glucocorticoid refractoriness in ulcerative colitis

ABSTRACT: A systems biology approach identifies ANP32E and other biomarkers of glucocorticoid refractoriness in ulcerative colitis

PROVIDER: PRJNA471889 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR7178590.fastq.gz	Fastqsanger.gz
	SRR7178600.fastq.gz	Fastqsanger.gz
	SRR7178610.fastq.gz	Fastqsanger.gz
	SRR7178620.fastq.gz	Fastqsanger.gz
	SRR7178630.fastq.gz	Fastqsanger.gz

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A systems biology approach identifies ANP32E and other biomarkers of glucocorticoid refractoriness in ulcerative colitis [microarray]

Project description:BACKGROUND: Glucocorticoid (GC) refractoriness is a common and unpredictable phenomenon in ulcerative colitis (UC). Although it has been demonstrated that NFkB is involved in its mechanism of action (MoA), there are no conclusive studies on the molecular functions involved. The current study describes in depth the MoA related to GC failure, by integrating transcriptomic data from UC patients, and updated molecular data on UC and GC. METHODS: miRNA and mRNA expression from rectal biopsies of active UC patients, obtained before and on the 3rd day of GC treatment, were evaluated by sequencing and microarrays, respectively. The differential results obtained were integrated into the mathematical models generated by Systems Biology. RESULTS: This computational approach identified 64 proteins, among which 18 stand out, either by being associated to the MoA or by providing a major capacity to classify the patients according to GC response. The biological functions of these proteins have been linked with inflammation, machinery GC-induced transcription and angiogenesis. All the selected proteins but one —Acidic leucine-rich Nuclear Phosphoprotein 32 family member E (ANP32E) — had previously been related to UC and/or GC-induced biological actions. ANP32E has been linked to the exchange of H2A to H2A.z histone, which promotes CG receptor complex-activated transcription. Western blot and immunofluorescence assays confirmed the predictive results obtained by Systems Biology. CONCLUSIONS: A comprehensive MoA of GC refractoriness has been described, highlighting the key role of GC-induced transcription in this phenomenon. Several proteins have been identified as putative predictors of GC refractoriness.

2018-11-06 | GSE114527 | GEO

A systems biology approach identifies ANP32E and other biomarkers of glucocorticoid refractoriness in ulcerative colitis [miRNA-Seq]

2018-11-06 | GSE114591 | GEO

A systems biology approach identifies ANP32E and other biomarkers of glucocorticoid refractoriness in ulcerative colitis [microarray]

Project description:A systems biology approach identifies ANP32E and other biomarkers of glucocorticoid refractoriness in ulcerative colitis [microarray]

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A systems biology approach identifies ANP32E and other biomarkers of glucocorticoid refractoriness in ulcerative colitis [miRNA-Seq]

Project description:A systems biology approach identifies ANP32E and other biomarkers of glucocorticoid refractoriness in ulcerative colitis [miRNA-Seq]

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A systems biology approach identifies ANP32E and other biomarkers of glucocorticoid refractoriness in ulcerative colitis

Project description:This SuperSeries is composed of the SubSeries listed below.

2018-11-06 | GSE114603 | GEO

Systems biology approach highlights mechanistic differences between Crohn's disease and ulcerative colitis.

Project description:The molecular mechanisms of IBD have been the subject of intensive exploration. We, therefore, assembled the available information into a suite of causal biological network models, which offer comprehensive visualization of the processes underlying IBD. Scientific text was curated by using Biological Expression Language (BEL) and compiled with OpenBEL 3.0.0. Network properties were analysed by Cytoscape. Network perturbation amplitudes were computed to score the network models with transcriptomic data from public data repositories. The IBD network model suite consists of three independent models that represent signalling pathways that contribute to IBD. In the "intestinal permeability" model, programmed cell death factors were downregulated in CD and upregulated in UC. In the "inflammation" model, PPARG, IL6, and IFN-associated pathways were prominent regulatory factors in both diseases. In the "wound healing" model, factors promoting wound healing were upregulated in CD and downregulated in UC. Scoring of publicly available transcriptomic datasets onto these network models demonstrated that the IBD models capture the perturbation in each dataset accurately. The IBD network model suite can provide better mechanistic insights of the transcriptional changes in IBD and constitutes a valuable tool in personalized medicine to further understand individual drug responses in IBD.

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Project description:In recent studies, the void of evaluation and in-depth understanding of unknown clinically relevant potential molecular biomarkers involved in colorectal cancer (CRC) from the inflammatory stage of ulcerative colitis (UC) to CRC metastasis, which can be suitable therapeutic targets, is deeply felt. The regulation and interaction among different cancer-promoting molecules, including messenger RNAs (mRNAs) and micro RNAs (miRNAs) in CRC and its progression, were the aim we pursued in this study. Using microarray data, we investigated the differential expression for five datasets, including mRNA and microRNA samples related to UC, tumor/normal. Then, using robust data analysis, separate lists of differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) were identified, which were used for robust rank aggregation (RRA) and co-expression network analysis. Then, comprehensive computational systems biology analyses, including gene ontology and Kyoto encyclopedia of genes and genomic pathway enrichment analyses, mRNA-miRNA regulatory network, and survival analysis, were employed to achieve the aim of this study. Finally, we used clinical samples to validate this potential and new target. According to this systems biology approach, a total of 98 DEGs and 8 DEmiRNAs with common differential expression were identified. By combining the distinct results of RRA and network, several potential therapeutic targets, and predictive and prognostic biomarkers for UC and CRC were identified. These targets include six common hub genes, CXCL1, CXCL8, MMP7, SLCA16A9, PLAU, and TIMP1, which are upregulated. Among these, the important and new biomarker SLC16A9 is negatively regulated by hsa-mir-194-5p, and hsa-miR-378a-5p take. The findings of the present study provide new insight into the pathogenesis of CRC in UC. Our study suggests future evaluation of the functional role of SLC16A9 and hsa-mir-194-5p and hsa-miR-378a-5p in CRC development.

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