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Erschienen in: Breast Cancer 2/2018

23.11.2017 | Original Article

Identification of key gene modules and pathways of human breast cancer by co-expression analysis

verfasst von: Qingnan Zhao, Wenqing Song, Dai yu He, YanSong Li

Erschienen in: Breast Cancer | Ausgabe 2/2018

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Abstract

Background

Breast cancer is the most common and aggressive tumor causing injury to women world wide. Although gene expression analysis had been performed previously, systemic co-expression analysis for this cancer is still lacking to date. We attempted to identify the critical modules of breast cancer.

Methods

Co-expression modules were established with the help of WGCNA and the interactions among them were performed by R language. Biological process and pathways analysis of co-expression genes were figured out by GO and KEGG functional enrichment analysis using DAVID dataset.

Results

In this study, expression data of 4,000 genes from 136 samples with breast cancer was used for the establishment of co-expression modules. And nine modules were identified. There was much higher scale independence among different modules by interactions analysis. Moreover, there was an obvious difference in adjacency degree among different modules. The most enriched pathways as immune response and ubiquitin-mediated proteolysis were identified as the most critical modules of breast cancer by GO and KEGG enrichment analysis.

Conclusion

Our result demonstrated that immune response and ubiquitin-mediated proteolysis could serve as prognostic and predictive markers for the occurrence of breast cancer, providing evidence for further analysis in the prognosis and treatment of breast cancer.
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Metadaten
Titel
Identification of key gene modules and pathways of human breast cancer by co-expression analysis
verfasst von
Qingnan Zhao
Wenqing Song
Dai yu He
YanSong Li
Publikationsdatum
23.11.2017
Verlag
Springer Japan
Erschienen in
Breast Cancer / Ausgabe 2/2018
Print ISSN: 1340-6868
Elektronische ISSN: 1880-4233
DOI
https://doi.org/10.1007/s12282-017-0817-5

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