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Updated: Sep 13, 2025
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Bioinformatics and Omics-based Perspectives on Breast Cancer: Advancing Target Gene Identification for the
Irmasari Irmasari1,2, Alim Khodimul Rahmat3, I Made Bayu Kresna Yoga1,2
1Master's Student in Pharmaceutical Sciences, Faculty of Pharmacy, Universitas Gadjah Mada, Sekip Utara II, 55281 Yogyakarta, Indonesia.
Objective:
Breast cancer remains the leading cause of mortality among women worldwide. Innovative strategies, particularly bioinformatics and omics-based approaches, play a crucial role in identifying potential target genes for breast cancer treatment. This review aims to highlight the future acceleration of drug discovery from single natural compounds and plant-derived natural products, including Traditional Chinese Medicines (TCMs), and to explore their potential in enhancing the efficacy of conventional drugs when combined, through the application of bioinformatics tools and various omics-based databases, web servers, or software platforms.
Methods:
This review focuses on research conducted over the past five years, utilizing three major scientific databases: PubMed, ScienceDirect, and Scopus. Using the Rayyan platform, we systematically narrowed 3,800 original studies down to 70 relevant articles.
Result:
The findings present a comprehensive overview of key bioinformatics approaches and omics-based resources, including databases, web servers, and software tools, covering data mining, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Protein-Protein Interaction (PPI) network construction and hub gene selection, genetic alteration, and survival analysis. These tools have been employed to identify potential target genes that contribute to the acceleration of drug discovery from single natural compounds and plant-derived natural products, including Traditional Chinese Medicines (TCMs), as well as their role in improving the therapeutic efficacy of conventional drugs when used in combination.
Conclusion:
A comprehensive understanding of omics-based databases, web servers and software can facilitate the acceleration of new drug discovery and enhance the effectiveness of existing conventional drugs in breast cancer therapy. This approach supports validation in preclinical models, both in vitro and in vivo, ensuring clinical applicability.
Insights
Bioinformatics and omics approaches accelerate breast cancer drug discovery from natural compounds and Traditional Chinese Medicines (TCMs). These methods enhance conventional drug efficacy, supporting preclinical validation for clinical application.
Area of Science:
- Oncology
- Bioinformatics
- Pharmacology
Background:
- Breast cancer is a leading cause of mortality in women globally.
- Identifying novel therapeutic targets is crucial for effective treatment.
- Bioinformatics and omics approaches offer innovative strategies for drug discovery.
Purpose of the Study:
- To review the acceleration of drug discovery from natural compounds and Traditional Chinese Medicines (TCMs) using bioinformatics and omics.
- To explore the potential of these natural products in combination with conventional drugs.
- To highlight the role of bioinformatics tools and omics databases in this process.
Main Methods:
- Systematic literature review of studies from the past five years.
- Searches conducted on PubMed, ScienceDirect, and Scopus databases.
- Rayyan platform used for study selection, narrowing down 3,800 studies to 70 relevant articles.
Main Results:
- Overview of key bioinformatics approaches: data mining, Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.
- Protein-Protein Interaction (PPI) network construction and hub gene selection identified potential targets.
- Application of these tools accelerates discovery of natural compounds and TCMs, enhancing combination therapy efficacy.
Conclusions:
- Understanding omics databases, web servers, and software aids drug discovery and enhances conventional breast cancer therapy.
- This integrated approach supports preclinical validation (in vitro and in vivo) for clinical relevance.
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