Research News: Using Curvature of Cellular Networks to Identify Cancer Cells

A recent issue of the scientific research journal Scientific Reports, published by Nature, highlighted the cancer cell research of computer science professor , post-doctoral researchers, and from Stony Brook University; Tryphon Georgiou (University of Minnesota);  and researchers from Memorial Sloan Kettering Cancer Center.

The paper titled Graph Curvature for Differentiating Cancer Networks reveals the role of curvature as a cancer network characteristic, and its relationship to robustness as a functionality of the network.

The research demonstrates that a certain geometric feature of protein networks can be used to identify cancer cells. Though this study, the research team addresses a key challenge in cancer therapy which is to explain and quantify the robustness of cancer cells. Using proposed geometric notions of curvature on weighted graphs, researchers investigated the features of gene co-expression networks obtained from large-scale genomic cancer studies.

Advances on this front may significantly impact targeted treatment of cancer cell networks. While the paper is focused on cancer cells, it points to the use of the analytical approach to the study of complex cellular networks to understand phenomena in molecular biology.

The project was supported in part by grants from the National Center for Research Resources; the National institute of Biomedical Imaging and Bioengineering of the National Institutes of Health; and Air Force Office of Scientific Research. Read the complete report by clicking