Centrality-Based Multi-Layer Network Modeling of Cancer Signaling Pathways

Zafreen Kousar, Jayalalitha G

Abstract: Cancer is a compound disorder that entails abnormal cellular signalling and structural alterations of cancerous cells. It is important to understand how tumour traits are tied to each other so as to determine significant indicators of cancer development. This paper uses a centrality-based network modelling technique in order to examine the relationship between tumour morphology features using the Breast Cancer Wisconsin database. The sample size of the dataset consists of 569 tumour samples where several quantitative measurements are given of the tumour cell nuclei structure. A correlation-based network was created in which the tumour features were expressed as nodes and statistical association between the features as edges. Network analysis was further conducted to study the structure of interaction of tumour characteristics. The degree centrality, betweenness centrality, and eigenvector centrality were centrality measures that were applied to identify influential features in the tumour interaction network. They are metrics that quantify the structural significance of nodes in complicated biological networks. The findings indicate that centrality scores are highest within the network on the tumour boundary irregularity features of concavity mean and concave points mean. The centre of the tumour interaction network is made up of these features and has a significant impact on various tumour properties. Studies based on biological networks suggest that the highly connected nodes tend to be important structural components that affect the behaviour of the biological systems. The results indicate that network analysis by centrality can help to show significant structural relationships between tumour characteristics. The method is a good way of analysing the complicated cancer data and determining the driving tumour features to aid in cancer diagnosis and disease analysis.

Keywords: Network biology, Tumour morphology, Centrality measures, Breast cancer diagnosis, Correlation-based network

How to Cite?: Zafreen Kousar, Jayalalitha G, "Centrality-Based Multi-Layer Network Modeling of Cancer Signaling Pathways", Volume 15 Issue 9, September 2026, International Journal of Science and Research (IJSR), Pages: 1020-1025, https://www.ijsr.net/getabstract.php?paperid=SR26916095946, DOI: https://dx.doi.org/10.21275/SR26916095946

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