ArticleBMC systems biology2018
Comparisons of gene coexpression network modules in breast cancer and ovarian cancer.
Article in BMC systems biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 30 citations in OpenAlex.
- Insight into Mantle Cell Lymphoma Pathobiology, Diagnosis, and Treatment Using Network-Based and Drug-Repurposing Approaches.International journal of molecular sciences · 2024Article
- Analysis of Tumor-Infiltrating T-Cell Transcriptomes Reveal a Unique Genetic Signature across Different Types of Cancer.International journal of molecular sciences · 2022Article
- Clinical characteristics and survival outcomes of patients with both primary breast cancer and primary ovarian cancer.Medicine · 2020Article
- An Integrative Computational Approach Based on Expression Similarity Signatures to Identify Protein-Protein Interaction Networks in Female-Specific Cancers.Frontiers in genetics · 2020Article
- Network spectra for drug-target identification in complex diseases: new guns against old foes.Applied network science · 2018Review
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Authors and funding
1 author at 1 institution in 1 country.
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Abstract
backgroundBreast 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.
methodsWe 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.
resultsWe 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.
conclusionBreast cancer and ovarian cancer share some common properties on the module level. Integration of both cancers helps identifying the potential cancer associated modules.
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