Using functional genomics and systems biology approach to understand breast cancer progression: An in-silico study

Objectives Breast cancer (BC) stands as the foremost malignancy among females, annually contributing to substantial mortality despite its often-asymptomatic nature. The latest GLOBOCAN 2024 data reveals Asia’s staggering burden, with 2,144,232 reported cases, prominently led by China (44%) and India (26%). Materials and Methods Gene expression datasets are retrieved from popular databases, namely NCBI’s Gene Expression Omnibus . Differential expression analysis was executed using an identified set of key genes implicated in breast cancer progression. Further exploration included a data pre-processing pipeline, disease-gene associations, principal component analysis, and Kaplan-Meier survival estimations, providing comprehensive insights into the functional roles of these genes within breast cancer pathways. Results RELB, PRDX5, CDKN1A, CST4, and UPP1 emerged as pivotal genes significantly influencing breast carcinoma progression in females. These findings underscore the critical roles of identified genes and advocate for their integration into a refined breast cancer network model. Conclusion Future research should focus on elucidating the specific functional attributes of RELB, PRDX5, CDKN1A, CST4, and UPP1 to enhance targeted therapeutic strategies and prognostic assessments in breast cancer management. Our research work not only advances our understanding of breast cancer biology but also highlights actionable targets for improved clinical outcomes and patient care.