Dataset Information

Comparisons of gene coexpression network modules in breast cancer and ovarian cancer.

ABSTRACT: BACKGROUND:Breast cancer and ovarian cancer are hormone driven and are known to have some predisposition genes in common such as the two well known cancer genes BRCA1 and BRCA2. The objective of this study is to compare the coexpression network modules of both cancers, so as to infer the potential cancer-related modules. METHODS:We applied the eigen-decomposition to the matrix that integrates the gene coexpression networks of both breast cancer and ovarian cancer. With hierarchical clustering of the related eigenvectors, we obtained the network modules of both cancers simultaneously. Enrichment analysis on Gene Ontology (GO), KEGG pathway, Disease Ontology (DO), and Gene Set Enrichment Analysis (GSEA) in the identified modules was performed. RESULTS:We identified 43 modules that are enriched by at least one of the four types of enrichments. 31, 25, and 18 modules are enriched by GO terms, KEGG pathways, and DO terms, respectively. The structure of 29 modules in both cancers is significantly different with p-values less than 0.05, of which 25 modules have larger densities in ovarian cancer. One module was found to be significantly enriched by the terms related to breast cancer from GO, KEGG and DO enrichment. One module was found to be significantly enriched by ovarian cancer related terms. CONCLUSION:Breast cancer and ovarian cancer share some common properties on the module level. Integration of both cancers helps identifying the potential cancer associated modules.

SUBMITTER: Zhang S

PROVIDER: S-EPMC5907153 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Comparisons of gene coexpression network modules in breast cancer and ovarian cancer.

Zhang Shuqin S

BMC systems biology 20180411 Suppl 1

<h4>Background</h4>Breast cancer and ovarian cancer are hormone driven and are known to have some predisposition genes in common such as the two well known cancer genes BRCA1 and BRCA2. The objective of this study is to compare the coexpression network modules of both cancers, so as to infer the potential cancer-related modules.<h4>Methods</h4>We applied the eigen-decomposition to the matrix that integrates the gene coexpression networks of both breast cancer and ovarian cancer. With hierarchica ...[more]

PMID: 29671401

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Dataset Information

Comparisons of gene coexpression network modules in breast cancer and ovarian cancer.

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Comparisons of gene coexpression network modules in breast cancer and ovarian cancer.

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