Comparison of Tumor and Normal Cells Protein-Protein Interaction Network Parameters

TL;DR

This study compares protein-protein interaction networks of cancerous and normal cells across five tissue types, identifying key network parameters that distinguish cancer cells from normal cells, highlighting denser interactions in cancer tissues.

Contribution

It introduces a comparative analysis of network parameters in cancer versus normal cells across multiple tissue types, revealing potential biomarkers.

Findings

Cancer networks have higher degree, centrality, and hub values.

Cancer tissues exhibit denser interaction networks.

Network parameters can differentiate cancer from normal cells.

Abstract

In this paper, we compared cancerous and normal cell according to their protein-protein interaction network. Cancer is one of the complicated diseases and experimental investigations have been showed that protein interactions have an important role in the growth of cancer. We calculated some graph related parameters such as Number of Vertices, Number of Edges, Closeness, Graph Diameter, Graph Radius, Index of Aggregation, Connectivity, Number of Edges divided by the Number of Vertices, Degree, Cluster Coefficient, Subgraph Centrality, and Betweenness. Furthermore, the number of motifs and hubs in these networks have been measured. In this paper bone, breast, colon, kidney and liver benchmark datasets have been used for experiments. The experimental results show that Graph Degree Mean, Subgraph Centrality, Betweenness, and Hubs have higher values in the cancer cells and can be used as a measure to distinguish between normal and cancerous networks. The cancerous tissues of the five studied samples are denser in the interaction networks.