Page 90 - EJMO-9-3

Eurasian Journal of
Medicine and Oncology Mapping breast cancer PPI networks for targets

and centrality, making them critical in breast cancer given the significant heterogeneity in breast cancer,
progression. The high concentration of signaling, growth- future research should stratify PPI networks by molecular
related, and oncogenic proteins in these zones underscores subtypes to enhance the precision of therapeutic targeting
their functional importance in tumor biology (Tables 2-10). strategies.
The analysis of protein distribution reinforces the
hypothesis that central network zones serve as functional 5. Conclusion
hubs critical to disease biology. This hierarchical The hierarchical structure of breast cancer PPIs reveals
organization suggests an evolutionary optimization, where a dense core enriched with essential proteins and drug
essential and highly interactive proteins are placed at the targets, offering a compelling framework to understand
network core to enhance robustness and efficiency in the molecular organization underlying cancer biology. By
information processing. 4 modeling BCPIN as a metric space, our study identifies
The structural and functional observations in BCPIN the central zones 1 – 3 as hubs for critical signaling
corroborate previous studies on protein interaction pathways, including DNA repair, Notch signaling, and
networks, which demonstrated similar core-periphery p53 signaling, which are crucial to cellular processes and
structures in biological networks, with central zones cancer progression.
enriched for essential and druggable proteins. 46-49 The The identification of MAPK14 as a central node
higher concentration of proteins involved in apoptosis, underscores its multifaceted role in disease states,
signal transduction, and immune response pathways particularly in cancer, and supports the importance of
in zones 1 and 2 aligns with previous studies, 50-52 which targeting central zones in therapeutic development.
reported these pathways as critical hubs in cancer-related The predominance of signaling proteins in these zones
networks. highlights their functional significance, making them
While previous work focused on general cancer central points for prioritizing drug targets. These findings
networks, our study uniquely emphasizes the zonal demonstrate the translational potential of network-based
classification and highlights the centrality of MAPK14 approaches and suggest that integrating experimental
as a key node. This approach provides a more specific validation with other omics data could advance our
understanding of protein organization and functional understanding of these networks and guide novel strategies
specialization within the network. for breast cancer treatment.
4.2. Comparison with prior studies Acknowledgments
Our findings align with previous research that emphasizes This work is based on research supported by the Faculty of
the role of network topology in cancer biology. For Natural Science research office at University of the Western
instance, studies on glioblastoma and lung cancer have Cape. The opinions and conclusions expressed are those of
demonstrated that central proteins in PPIs are often the author and should not necessarily be attributed to the
associated with poor prognosis and therapeutic resistance.
However, unlike previous analyses that primarily focus on research office.
individual protein interactions, our metric space modeling Funding
provides a hierarchical framework to understand spatial
distributions within the network. This approach allows None.
us to quantify the impact of protein positioning and
connectivity, offering a systematic method to prioritize Conflict of interest
drug targets. The authors declare no conflicts of interest.
4.3. Limitations and future directions Author contributions
Our study offers valuable insights into breast cancer This is a single-authored article.
PPIs, but certain limitations must be acknowledged.
First, our analysis depends on publicly available PPI Ethics approval and consent to participate
datasets, which may contain biases due to experimental
constraints and incomplete annotations. Second, while our Not applicable.
computational predictions identify potential therapeutic Consent for publication
targets, experimental validation is essential to confirm
their biological relevance in cancer progression. Finally, Not applicable.

Volume 9 Issue 3 (2025) 82 doi: 10.36922/ejmo.8208