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Updated: May 12, 2026
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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Using Frequent Co-expression Network to Identify Gene Clusters for Breast Cancer Prognosis
Jie Zhang1, Kun Huang, Yang Xiang
1Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
Proceedings ... International Joint Conference on Bioinformatics, Systems Biology and Intellgent Computing. International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing
|April 26, 2013
Summary
This study used gene co-expression network analysis to find new biomarkers for breast cancer prognosis. These biomarkers can help categorize patients into groups with different survival outcomes.
Area of Science:
- Genomics
- Bioinformatics
- Cancer Research
Background:
- Accurate breast carcinoma prognosis is crucial for effective treatment strategies.
- Identifying reliable prognostic biomarkers remains a significant challenge in oncology.
Purpose of the Study:
- To identify potential gene biomarkers for breast carcinoma prognosis using gene co-expression network analysis.
- To categorize breast cancer patients into distinct prognostic groups based on identified gene clusters.
Main Methods:
- Utilized the CODENSE network mining algorithm to identify genome-wide gene co-expression networks across various cancer types.
- Applied resulting gene clusters to breast cancer microarray datasets for patient stratification.
- Compared identified gene clusters with subsets from similar studies using alternative clustering algorithms.
Main Results:
- Identified a set of genes that serve as potential biomarkers for breast cancer prognosis.
- Successfully categorized patients into two groups with significantly different prognostic outcomes.
- Demonstrated the utility of CODENSE in discovering biologically relevant gene modules.
Conclusions:
- Gene co-expression network analysis, particularly with CODENSE, is a powerful approach for identifying prognostic biomarkers in breast cancer.
- The discovered gene set offers potential for improving patient stratification and personalized treatment decisions.
- Further validation of these biomarkers in larger, independent cohorts is warranted.
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