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dc.contributor.authorLambrou, George I.
dc.contributor.authorAdamaki, Maria
dc.contributor.authorDelakas, Dimitrios S.
dc.contributor.authorSpandidos, Demetrios A.
dc.contributor.authorVlahopoulos, Spiros
dc.contributor.authorZaravinos, Apostolos
dc.date.accessioned2018-10-29T12:04:20Z
dc.date.available2018-10-29T12:04:20Z
dc.date.issued2013-05-15
dc.identifierSCOPUS_ID:84877959594
dc.identifier.issn15384101
dc.identifier.otherPubMed ID: 23624844
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84877959594&origin=inward
dc.identifier.urihttps://repo.euc.ac.cy/handle/123456789/603
dc.description.abstractObjective: Chromosome correlation maps display correlations between gene expression patterns on the same chromosome. Our goal was to map the genes on chromosome regions and to identify correlations through their location on chromosome regions. Results: The top deregulated molecules among 129 bladder cancer samples were implicated in the PI3K/AKT signaling, cell cycle, Myc-mediated apoptosis signaling and ERK5 signaling pathways. Their most prominent molecular and cellular functions were related to cell cycle, cell death, gene expression, molecular transport and cellular growth and proliferation. Chromosome correlation maps allowed us to detect significantly co-expressed genes along the chromosomes. We identified strong correlations among tumors of Tα-grade 1, as well as for those of Tα-grade 2, in chromosomes 1, 2, 3, 7, 12 and 19. Chromosomal domains of gene co-expression were revealed for the normal tissues, as well. The expression data were further simulated, exhibiting an excellent fit (0.7 < R2 < 0.9). The simulations revealed that along the different samples, genes on same chromosomes are expressed in a similar manner. Materials and Methods: Following microarray analysis we used Ingenuity Pathway Analysis (IPA) to construct gene networks of the co-deregulated genes in bladder cancer. Chromosome mapping, mathematical modeling and data simulations were performed using the WebGestalt and Matlab® softwares. Conclusions: Gene expression is highly correlated on the chromosome level. Chromosome correlation maps of gene expression signatures can provide further information on gene regulatory mechanisms. Gene expression data can be simulated using polynomial functions.
dc.relation.ispartofCell Cycle
dc.titleGene expression is highly correlated on the chromosome level in urinary bladder cancer
elsevier.identifier.doi10.4161/cc.24673
elsevier.identifier.eid2-s2.0-84877959594
elsevier.identifier.scopusidSCOPUS_ID:84877959594
elsevier.volume12
elsevier.issue.identifier10
elsevier.coverdate2013-05-15
elsevier.coverdisplaydate15 May 2013
elsevier.openaccess1
elsevier.openaccessflagtrue
elsevier.aggregationtypeJournal


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