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Integrated gene network analysis and text mining revealing PIK3R1 regulated by miR-127 in human bladder cancer.


ABSTRACT:

Background

Cancer is the result of a complex multistep process that involves the accumulation of sequential alterations of several genes, including those encoding microRNAs (miRNAs) that have critical roles in the regulation of gene expression.In this study, we aimed to predict potential mechanisms of bladder cancer related miRNAs and target genes by bioinformatics analyses.

Methods

Here we used the method of text mining to identify nine miRNAs in bladder cancer and adopted protein-protein interaction analysis to identify interaction sites between these miRNAs and related-target genes.

Results

There are two relationship types between bladder cancer and its related miRNAs: causal and unspecified. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment test showed that there were three pathways related to four miRNA targeted genes. The remaining five miRNAs annotated to disease are not enriched in the KEGG pathways. Of these, PIK3R1 is the overlapping gene among 38 genes in the cancer and bladder cancer pathways.

Conclusions

These findings provide new insights into the role of miRNAs in the pathway of cancer and give us a hypothesis that miR-127 might play a similar role in regulation and control of PIK3R1.

SUBMITTER: Xu Y 

PROVIDER: S-EPMC3766679 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Publications

Integrated gene network analysis and text mining revealing PIK3R1 regulated by miR-127 in human bladder cancer.

Xu Yahong Y   Luo Shunwen S   Liu Yang Y   Li Jian J   Lu Yi Y   Jia Zhigang Z   Zhao Qihua Q   Ma Xiaoping X   Yang Minghui M   Zhao Yue Y   Chen Ping P   Guo Yu Y  

European journal of medical research 20130901


<h4>Background</h4>Cancer is the result of a complex multistep process that involves the accumulation of sequential alterations of several genes, including those encoding microRNAs (miRNAs) that have critical roles in the regulation of gene expression.In this study, we aimed to predict potential mechanisms of bladder cancer related miRNAs and target genes by bioinformatics analyses.<h4>Methods</h4>Here we used the method of text mining to identify nine miRNAs in bladder cancer and adopted protei  ...[more]

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