gse28619

Maria Teresa Rubio Martinez-Abarca and Guillermo Ayala

2025-03-11

Abstract

> Alcoholic hepatitis (AH) is the most severe form of alcoholic liver disease and occurs in patients with excessive alcohol intake It is characterized by marked hepatocellular damage, steatosis and pericellular fibrosis. Patients with severe AH have a poor short-term prognosis. Unfortunately, current therapies (i.e. corticosteroids and pentoxyphylline) are not effective in many patients and novel targeted therapies are urgently needed. The development of such therapies is hampered by a poor knowledge of the underlying molecular mechanisms. Based on studies from animal models, TNF alfa was proposed to play a pivotal role in the mechanisms of AH. Consequently, drugs interfering TNF alfa were tested in these patients. The results were disappointing due to an increased incidence of severe infections. Unluckily, there are not experimental models that mimic the main findings of AH in humans. To overcome this limitation, translational studies with human samples are required. We previously analyzed samples from patients with biopsy-proven AH. In these previous studies, we identified CXC chemokines as a potential therapeutic target for these patients. We expanded these previous observations by performing a high-throughout transcriptome analysis.

The data has been downloaded from GEO.

Packages

library(GEOquery)
library(affy)
library(hgu133plus2.db)

Downloading the dataset

gcel = getGEOSuppFiles("GSE28619")
system("tar xvf GSE28619/GSE28619_RAW.tar")
gse28619raw = ReadAffy()
gse28619 = rma(gse28619raw)
type = factor(rep(1:2,c(7,15)),levels=1:2,labels=c("control","alcoholic"))
pData(gse28619) = data.frame(type)
experimentdata0 = new('MIAME', name ='Juanjo Lozano et al.',
                       lab ='CIBEREHD',
                       contact ='juanjo.lozano@ciberehd.org',
                       title = 'Transcriptome analysis identifies TNF 
                       superfamily receptors as potential therapeutic 
                       targets in alcoholic hepatitis.',
                       abstract = 'Alcoholic hepatitis (AH) is the most severe 
                       form of alcoholic liver disease and occurs in patients 
                       with excessive alcohol intake It is characterized by 
                       marked hepatocellular damage, steatosis and pericellular
                       fibrosis. Patients with severe AH have a poor short-term
                       prognosis. Unfortunately, current therapies (i.e.
                       corticosteroids and pentoxyphylline) are not effective 
                       in many patients and novel targeted therapies are urgently
                       needed. The development of such therapies is hampered by a
                       poor knowledge of the underlying molecular mechanisms. 
                       Based on studies from animal models, TNF alfa was proposed 
                       to play a pivotal role in the mechanisms of AH. 
                       Consequently, drugs interfering TNF alfa were tested 
                       in these patients. The results were disappointing due 
                       to an increased incidence of severe infections. 
                       Unluckily, there are not experimental models that 
                       mimic the main findings of AH in humans. To overcome 
                       this limitation, translational studies with human samples 
                       are required. We previously analyzed samples from 
                       patients with biopsy-proven AH. In these previous studies, 
                       we identified CXC chemokines as a potential therapeutic 
                       target for these patients. We expanded these previous
                       observations by performing a high-throughout transcriptome
                       analysis.',
                       url = 'http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28619')

experimentData(gse28619) = experimentdata0

Guardar ExpressionSet

Additional identifiers per gene.

a = AnnotationDbi::select(hgu133plus2.db,keys=featureNames(gse28619),
                          columns=c("ENTREZID","ENSEMBL","GO"),keytype="PROBEID")
b = BiocGenerics::match(featureNames(gse28619),a[,"PROBEID"])
fData(gse28619) =  a[b,]

Saving the ExpressionSet.

save(gse28619,file="gse28619.rda")