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Updated: Jun 30, 2025
Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer
Published on: March 17, 2016
Deciphering Breast Cancer Metastasis Cascade: A Systems Biology Approach Integrating Transcriptome and Interactome
Bikashita Kalita1, Mohane Selvaraj Coumar1
1Department of Bioinformatics, School of Life Sciences, Pondicherry University, Pondicherry, India.
Abstract:
Breast cancer is the lead cause of cancer-related deaths among women globally. Breast cancer metastasis is a complex and still inadequately understood process and a key dimension of mortality attendant to breast cancer. This study reports dysregulated genes across metastatic stages and tissues, shedding light on their molecular interplay in disease pathogenesis and new possibilities for drug discovery. Comprehensive analyses of gene expression data from primary breast tumor, circulating tumor cells, and distant metastatic sites in the brain, lung, liver, and bone were conducted. Genes dysregulated across multiple stages and tissues were identified as metastatic cascade genes, and are further classified based on functional associations with metastasis-related mechanisms. Their interactions with HUB genes in interactome networks were scrutinized, followed by pathway enrichment analysis. Validation for their potential as targets included assessments for survival, druggability, prognostic marker status, secretome annotation, protein expression, and cell type marker association. Results displayed critical genes in the metastatic cascade and those specific to metastatic sites, revealing the involvement of the collagen degradation and assembly of collagen fibrils and other multimeric structure pathways in driving metastasis. Notably, pivotal cascade genes FABP4, CXCL12, APOD, and IGF1 emerged with high metastatic potential, linked to significant druggability and survival scores, establishing them as potential molecular targets. The significance of this research lies in its potential to uncover novel biomarkers for early detection, therapeutic targets, and a deeper understanding of the molecular mechanisms underpinning the metastatic cascade in breast cancer, and with an eye to precision/personalized medicine.
Insights
This study identifies key genes driving breast cancer metastasis across different tissues. These metastatic cascade genes, including FABP4, CXCL12, APOD, and IGF1, offer potential new targets for precision medicine and early detection.
Area of Science:
- Oncology
- Molecular Biology
- Genomics
Background:
- Breast cancer remains a leading cause of cancer mortality globally, with metastasis being a primary driver of death.
- The molecular mechanisms underlying breast cancer metastasis are complex and not fully understood, hindering effective treatment strategies.
Purpose of the Study:
- To identify and characterize dysregulated genes involved in the breast cancer metastatic cascade across various stages and tissues.
- To explore the potential of these identified genes as novel biomarkers and therapeutic targets for precision medicine.
Main Methods:
- Comprehensive analysis of gene expression data from primary tumors, circulating tumor cells, and distant metastatic sites (brain, lung, liver, bone).
- Identification of metastatic cascade genes, functional classification, interactome network analysis with HUB genes, and pathway enrichment.
- Validation of potential targets through assessments of survival, druggability, prognostic value, secretome, protein expression, and cell type markers.
Main Results:
- Identified critical genes in the metastatic cascade and site-specific genes, highlighting pathways like collagen degradation and fibril assembly.
- Pivotal cascade genes FABP4, CXCL12, APOD, and IGF1 demonstrated high metastatic potential, druggability, and significant survival associations.
- Revealed the molecular interplay of genes in disease pathogenesis and identified potential therapeutic targets.
Conclusions:
- The study elucidates key molecular players in breast cancer metastasis, offering insights into pathogenesis.
- Identified genes like FABP4, CXCL12, APOD, and IGF1 represent promising candidates for developing novel diagnostic and therapeutic strategies.
- Findings support the advancement of precision medicine approaches for breast cancer by uncovering potential molecular targets.
