ArticleCell cycle (Georgetown, Tex.)2013
Gene expression is highly correlated on the chromosome level in urinary bladder cancer.
Article in Cell cycle (Georgetown, Tex.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- Article
- Knockdown of fibrous sheath interacting protein 1 expression reduces bladder urothelial carcinoma cell proliferation and induces apoptosis via inhibition of the PI3K/AKT pathway.OncoTargets and therapy · 2018Article
- Predicting the Survival Time for Bladder Cancer Using an Additive Hazards Model in Microarray Data.Iranian journal of public health · 2016Article
- Fractal dimensions of in vitro tumor cell proliferation.Journal of oncology · 2015Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveChromosome 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. MATERIALS AND
methodsFollowing 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.
resultsThe 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 < R(2) < 0.9). The simulations revealed that along the different samples, genes on same chromosomes are expressed in a similar manner.
conclusionsGene 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.
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