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Updated: May 10, 2025
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Network-Based Integrative Analysis to Identify Key Genes and Corresponding Reporter Biomolecules for Triple-Negative
Pooja Singh1, Rupesh Chaturvedi2, Pallavi Somvanshi1
1School of Computational & Sciences (SCIS), Jawaharlal Nehru University, New Delhi, India.
Background:
The malignant neoplasm of the TNBC is the leading cause of death among Indian women. Recent studies identified the global burden of TNBC affecting approximately more than 40 percent of all BC cases in women worldwide. The absence of expression of receptors such as ER, PR, and HER2 characterizes TNBC.
Objectives:
Due to the lack of specific targets, standard treatment options for TNBC are limited. This integrative study aims to identify key genes and provide insights into the underlying molecular mechanisms of TNBC, which can potentially lead to the development of more effective therapeutic strategies.
Material And Methodology:
This study integrates PPI and WGCNA analysis of TNBC-related datasets (GSE52194 and GSE58135) to identify key genes. Subsequently, downstream analysis is conducted to explore potential therapeutic targets for TNBC.
Results:
The present study renders the potential 13 key genes (PLCG2, CXCL10, CDK1, STAT1, IL6, PLK1, CCNB1, AURKA, NDC80, EGFR, 1L1B, FN1, BUB1B), along with their associated 6 TFs and 20 miRNAs, as reporter biomolecules around which the most significant changes occur. There were some miRNAs hsa-mir-449b-5p, hsa-let-7b-5p, hsa-mir-26a-5p, hsa-mir-155-5p, hsa-mir-24-3p, hsa-mir-212-3p, hsa-mir-21-5p, hsa-mir-210-3p and hsa-mir-20a-5p whose association with other cancers and other BC subtypes have been reported but their association with TNBC need to be explored. Further, enrichment and cumulative survival analysis support the disease association of identified key genes with TNBC.
Conclusion:
This integrative analysis could be regarded for experimental inspection as it provides the platform for future researchers in drug designing and biomarker discovery for TNBC diagnosis and treatment.
Insights
Triple-negative breast cancer (TNBC) is a deadly disease with limited treatments. This study identified 13 key genes and associated molecules, offering potential new targets for TNBC diagnosis and drug development.
Area of Science:
- Genomics and Bioinformatics
- Molecular Oncology
- Biomarker Discovery
Background:
- Triple-negative breast cancer (TNBC) is a significant cause of cancer death in Indian women and globally, accounting for over 40% of breast cancer cases.
- TNBC is defined by the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression.
- Limited targeted treatment options exist for TNBC due to the absence of specific molecular targets.
Purpose of the Study:
- To identify key genes and elucidate molecular mechanisms underlying TNBC.
- To explore potential therapeutic targets for improving TNBC treatment strategies.
- To provide a foundation for future drug design and biomarker discovery in TNBC.
Main Methods:
- Integration of Protein-Protein Interaction (PPI) and Weighted Gene Co-expression Network Analysis (WGCNA).
- Analysis of TNBC-related gene expression datasets (GSE52194 and GSE58135).
- Downstream analysis including identification of transcription factors (TFs) and microRNAs (miRNAs) associated with key genes.
Main Results:
- Identification of 13 key genes (e.g., PLCG2, CXCL10, CDK1, STAT1, IL6, PLK1, CCNB1, AURKA, NDC80, EGFR, IL1B, FN1, BUB1B) as significant reporter biomolecules in TNBC.
- Association of 6 transcription factors and 20 miRNAs with these key genes, including several miRNAs with previously reported links to other cancers.
- Enrichment and cumulative survival analyses confirmed the disease association of the identified key genes with TNBC.
Conclusions:
- The identified key genes, TFs, and miRNAs provide a potential platform for experimental validation.
- This integrative analysis supports the discovery of novel biomarkers for TNBC diagnosis.
- The findings offer promising avenues for developing targeted therapeutic strategies for TNBC.
