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Review

Bioinformatics Strategies in Breast Cancer Research

by
Matteo Veneziano
1,
Isabella Savini
1,
Elisa Cortellesi
1,
Valeria Gasperi
1,
Alessandra Gambacurta
1,2 and
Maria Valeria Catani
1,*
1
Department of Experimental Medicine, Tor Vergata University of Rome, 00133 Rome, Italy
2
NAST Centre (Nanoscience & Nanotechnology & Innovative Instrumentation), Tor Vergata University of Rome, 00133 Rome, Italy
*
Author to whom correspondence should be addressed.
Biomolecules 2025, 15(10), 1409; https://doi.org/10.3390/biom15101409
Submission received: 24 June 2025 / Revised: 9 September 2025 / Accepted: 29 September 2025 / Published: 2 October 2025

Abstract

Breast cancer is a heterogeneous disease and a leading cause of cancer-related deaths worldwide, underscoring the urgent need for effective biomarkers to guide diagnosis, prognosis, and therapeutic decisions. Bioinformatics methodologies, including genomics, transcriptomics, proteomics, and metabolomics data analysis, are essential for deciphering the complex molecular landscape of breast cancer. Bioinformatics tools facilitate the identification of differentially expressed genes, non-coding RNAs, and proteins, unraveling crucial pathways involved in tumor initiation, progression, and metastasis. By constructing and analyzing protein–protein interaction networks and signaling pathways, bioinformatics approaches can identify potential diagnostic, prognostic, and predictive biomarkers. Herein, we explore the role of bioinformatics in breast cancer research and its potential application in identifying novel therapeutic targets and predicting drug response, ultimately enabling the development of tailored treatment strategies. We also address the challenges and future directions in utilizing bioinformatics for biomarker discovery and validation, emphasizing the need for robust statistical methods, standardized data analysis pipelines, and collaborative efforts to translate bioinformatics insights into improved clinical outcomes for breast cancer patients.
Keywords: breast cancer; biomarker; genomics; transcriptomics; proteomics; metabolomics; drug response breast cancer; biomarker; genomics; transcriptomics; proteomics; metabolomics; drug response

Share and Cite

MDPI and ACS Style

Veneziano, M.; Savini, I.; Cortellesi, E.; Gasperi, V.; Gambacurta, A.; Catani, M.V. Bioinformatics Strategies in Breast Cancer Research. Biomolecules 2025, 15, 1409. https://doi.org/10.3390/biom15101409

AMA Style

Veneziano M, Savini I, Cortellesi E, Gasperi V, Gambacurta A, Catani MV. Bioinformatics Strategies in Breast Cancer Research. Biomolecules. 2025; 15(10):1409. https://doi.org/10.3390/biom15101409

Chicago/Turabian Style

Veneziano, Matteo, Isabella Savini, Elisa Cortellesi, Valeria Gasperi, Alessandra Gambacurta, and Maria Valeria Catani. 2025. "Bioinformatics Strategies in Breast Cancer Research" Biomolecules 15, no. 10: 1409. https://doi.org/10.3390/biom15101409

APA Style

Veneziano, M., Savini, I., Cortellesi, E., Gasperi, V., Gambacurta, A., & Catani, M. V. (2025). Bioinformatics Strategies in Breast Cancer Research. Biomolecules, 15(10), 1409. https://doi.org/10.3390/biom15101409

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