ISSN: 2691-5782
Authors: Asmita Das* and Kapil Jangra
Cervical cancer is a major cause of death in women. The total number of genes that are associated with cervical cancer is 3099. We created a PPI network and then studied the topological properties of the network that gave evidence that the network is scale free, the degree distribution obeys power law and have some nodes (vertices) that play a crucial role during cancer progression. The aim of this project was to identify these nodes (also called key regulators) and the strategy used for this, is based on Barabasi-Albert model (which is a bottom up approach).The model suggested that the network we created, is evolved in nature by growth and preferential attachment concept, and have hub nodes. Finally, we concluded that there are seven important key regulators (viz. CDK2, E2F1, CDKN1A, CDKN2A, TP53, PTGS2 and CTNNB1) that are present in our network, which implies that if we are able to delete these key regulators, the whole network would collapse. So, by understanding the complex functionality and regulation of these fundamental key regulators, we can identify the diagnostic biomarkers and can develop early detection techniques and therapy for cervical cancer.
Keywords: Cancer network; Cervical cancer; Scale free network; Cancer biomarker; Therapies; CDK2; E2F1; CDKN1A; TP53; PTGS2; CTNNB1
