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Updated: Mar 29, 2026
Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer
Published on: March 17, 2016
Crosstalk analysis of pathways in breast cancer using a network model based on overlapping differentially expressed
Yong Sun1, Kai Yuan2, Peng Zhang3
1Department of Breast and Thyroid Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong 250021, P.R. China ; Department of General Surgery, Laiwu Hospital Affiliated to Taishan Medical College, Laiwu, Shandong 271100, P.R. China.
Abstract:
Multiple signal transduction pathways can affect each other considerably through crosstalk. However, the presence and extent of this phenomenon have not been rigorously studied. The aim of the present study was to identify strong and normal interactions between pathways in breast cancer and determine the main pathway. Five sets of breast cancer data were downloaded from the high-throughput Gene Expression Omnibus (GEO) and analyzed to identify differentially expressed (DE) genes using the Rank Product (RankProd) method. A list of pathways with differential expression was obtained by gene set enrichment analysis (GSEA) of the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The DE genes that overlapped between pathways were identified and a crosstalk network diagram based on the overlap of DE genes was constructed. A total of 1,464 DE genes and 26 pathways were identified. In addition, the number of DE genes that overlapped between specific pathways were determined, and the greatest degree of overlap was between the extracellular matrix (ECM)-receptor interaction and Focal adhesion pathways, which had 22 overlapping DE genes. Weighted pathway analysis of the crosstalk between pathways identified that Pathways in cancer was the main pathway in breast cancer.
Insights
This study investigated pathway crosstalk in breast cancer, identifying significant interactions and the central "Pathways in cancer" pathway. Key findings highlight the extracellular matrix (ECM)-receptor interaction and Focal adhesion pathways due to substantial gene overlap.
Area of Science:
- Oncology
- Systems Biology
- Bioinformatics
Background:
- Signal transduction pathways exhibit crosstalk, but its extent in breast cancer remains understudied.
- Understanding pathway interactions is crucial for deciphering complex disease mechanisms.
Purpose of the Study:
- To identify and quantify pathway crosstalk in breast cancer.
- To determine the primary pathway driving breast cancer through interaction analysis.
Main Methods:
- Utilized five breast cancer datasets from Gene Expression Omnibus (GEO).
- Identified differentially expressed (DE) genes using Rank Product (RankProd).
- Performed gene set enrichment analysis (GSEA) on KEGG pathways and constructed a crosstalk network based on overlapping DE genes.
Main Results:
- Identified 1,464 DE genes and 26 differentially expressed pathways.
- Found the highest crosstalk between extracellular matrix (ECM)-receptor interaction and Focal adhesion pathways (22 overlapping DE genes).
- Weighted pathway analysis revealed "Pathways in cancer" as the main pathway in breast cancer.
Conclusions:
- Breast cancer involves significant pathway crosstalk, with specific interactions being more prominent.
- "Pathways in cancer" acts as a central hub, underscoring its importance in the disease.
- The identified crosstalk network provides insights into breast cancer's molecular complexity.
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