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Series GSE38467 Query DataSets for GSE38467
Status Public on Jul 20, 2012
Title Transcriptional perturbations caused by tumor virus proteins
Organism Homo sapiens
Experiment type Expression profiling by array
Summary 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.
We profiled the transcriptome of human cells expressing tumor virus proteins, in order to trace pathways through which viral proteins could alter cellular states.
Overall design To examine transcriptome network perturbations directly in human cells, we generated expression constructs fusing each viral ORF (open reading frame) to a tandem epitope tag and introduced each construct into IMR-90 normal human diploid fibroblasts. Total RNA was isolated from IMR-90 cells expressing viORFs and gene expression was assayed on Human Gene 1.0 ST arrays.
Contributor(s) Rozenblatt-Rosen O, Deo RC, Padi M, Adelmant G, Hill DE, Münger K, Marto JA, Quackenbush J, Roth FP, DeCaprio JA, Vidal M
Citation(s) 22810586, 29707235, 26576632
Submission date Jun 04, 2012
Last update date Jan 13, 2021
Contact name Megha Padi
Organization name University of Arizona
Department Molecular and Cellular Biology
Street address 1071 East Lowell St.
City Tucson
State/province AZ
ZIP/Postal code 85701
Country USA
Platforms (1)
GPL15648 [HuGene-1_0-st] Affymetrix Human Gene 1.0 ST Array [HuGene10stv1_Hs_ENTREZG version 13.0.0]
Samples (449)
GSM942398 IMR90-POLYOSV40-LT-rep2-C
GSM942399 IMR90-HPV18-E7-E
GSM942400 IMR90-GFP-rep1-A
BioProject PRJNA167934

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE38467_RAW.tar 2.0 Gb (http)(custom) TAR (of CEL)
Raw data provided as supplementary file
Processed data included within Sample table

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