DAVID and KEGG-Based Functional Enrichment Analysis of Breast Cancer Transcriptome: Mapping ECM Remodeling and Cell Division Pathways - Aloqbi, Akram Ahmed (International Journal of Pharmaceutical Investigation, 2026)
Background Breast cancer, affecting roughly 2.3 million people each year, stands as a major global health concern due to its molecular complexity across subtypes such as luminal, HER2-enriched, and triple-negative. These subtypes lead to diverse clinical outcomes, highlighting the urgent need for deeper molecular understanding of tumor development. Advanced genomic tools, including microarrays and RNA-sequencing, have significantly improved our ability to pinpoint genes involved in cancer, but challenges in integrating complex datasets and applying these insights to patient care persist. This study investigates molecular mechanisms to guide the development of innovative treatment approaches. Materials and Methods Using the GSE54002 dataset (216 samples: 200 breast cancer, 16 normal) from the Affymetrix Human Genome U133 Plus 2.0 Array, we applied GEO2R to identify significant genes (adjusted p-value <0.05, |log2FC|>1). Functional enrichment with DAVID and KEGG elucidated biological processes and pathways, focusing on cell proliferation, Extracellular Matrix (ECM) remodeling, and cytoskeletal dynamics. Results GEO2R analysis identified genes distinguishing breast cancer from normal tissue. Enrichment studies with DAVID and KEGG revealed key processes and pathways involved in tumor progression, in consistent with established breast cancer etiology. These findings highlighted potential molecular targets for possible therapeutic interventions. Conclusion The current study prominently demonstrates the utility of GEO2R, DAVID, and KEGG tools in understanding and interpreting the complex transcriptomic data and to explore prominent breast cancer’s molecular markers. The results also help us in improving the diagnostic and personalized treatment approaches. Further validation studies of current findings, could also help us to develop more precise treatments and improved patient outcomes in cancer care.
Keywords: Affymetrix Chips; Functional Enrichment Analysis; DAVID; KEGG; Breast Cancer; GEO2R.