Page 83 - EJMO-9-3

Eurasian Journal of Medicine

and Oncology

ORIGINAL RESEARCH ARTICLE
Mapping breast cancer protein interaction

networks as metric spaces: Insights into central
zones and drug discovery targets

Emad Fadhal *
1,2
1 Department of Mathematics and Statistics, College of Science, King Faisal University, Al-Ahsa,
Saudi Arabia
2 Department of Mathematics and Applied Mathematics, University of the Western Cape, Bellville,
South Africa

Abstract

Introduction: Graph theory was employed in recent advances of cancer research
for gain deeper insights into the complex structure and function of protein-protein
interaction (PPI) networks.
Objective: By representing proteins as nodes and their interactions as edges, graph
theory offers a comprehensive framework for analyzing the topological properties of
these networks and identifying key nodes that regulate critical biological processes. This
approach has been widely applied to study various cancers, including breast cancer.
Methods: To investigate the molecular organization and critical pathways in breast
*Corresponding author:
Emad Fadhal cancer, we constructed a breast cancer protein-protein interaction network (BCPIN)
(efadhal@kfu.edu.sa) and analyzed its hierarchical structure. The network was modeled as a metric space
Citation: Fadhal E. Mapping breast to delineate its central zones, facilitating the identification of essential hubs enriched
cancer protein interaction networks with signaling pathways critical for cancer progression.
as metric spaces: Insights into Results: Our study demonstrates the potential of hierarchical modeling of the BCPIN
central zones and drug discovery
targets. Eurasian J Med Oncol. in unraveling its molecular organization and identifying therapeutic opportunities.
2025;9(3):75-85. By analyzing PPI network as a metric space, we highlight central zones 1 – 3 as critical
doi: 10.36922/ejmo.8208 hubs enriched with key signaling pathways, such as DNA repair, Notch signaling, and
Received: December 25, 2024 p53 signaling, which are essential to cancer progression. The identification of MAPK14
as a central node emphasizes its significant role in cancer biology and its value as
1st revised: December 31, 2024
a therapeutic target. The predominance of signaling proteins within these zones
2nd revised: February 8, 2025 underscores their functional relevance, offering a strong rationale for prioritizing them
3rd revision: February 23, 2025 in drug development.
Conclusion: By modeling the PPI network as a metric space, we uncovered important
Accepted: March 6, 2025
insights into its architecture and the central zone’s critical role in facilitating key
Published online: March 20, 2025 cellular processes. Our results indicate that zones 1 – 3, particularly the central zone,
Copyright: © 2025 Author(s). may serve as promising targets for drug discovery in cancer biology.
This is an Open-Access article
distributed under the terms of the
Creative Commons Attribution Keywords: Protein interaction networks; Metric spaces; Signaling pathways; Breast
License, permitting distribution,
and reproduction in any medium, cancer; Central zones; Drug discovery
provided the original work is
properly cited.
Publisher’s Note: AccScience 1. Introduction
Publishing remains neutral with Breast cancer remains the leading cause of cancer-related mortality worldwide, with
regard to jurisdictional claims in
published maps and institutional its complexity driven by dysregulated protein-protein interaction (PPI) networks that
1
affiliations. control critical cellular processes such as proliferation, apoptosis, and metastasis.

Volume 9 Issue 3 (2025) 75 doi: 10.36922/ejmo.8208