Mapping the p53 gene using STRING software to study the alterations modulating the functioning of associated genes in leukemia

Alteration in the p53 gene leads to uncontrolled cell proliferation and when these changes accumulate, it may result in carcinogenesis. A plethora of proteins have been reported that bind to the various regions of p53 in order to regulate the specificity of its activity. In the present study, our aim was to understand these connections so we have analyzed the networking role of p53 gene using ‘STRING’ software in leukemia [acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic myeloid leukemia (CML) & chronic lymphocytic leukemia (CLL)] with emphasis on ALL, being most prevalent in children. The TP53 protein is an important tumor suppressor protein, found altered in many cancers. Using STRING tool, we successfully determined the protein-protein interaction network and studied its functional interactionpartners with which we could decipher some of the major pathways that may be deregulated in ALL. Applying the clustering algorithm, currently accessible in STRING, i.e., k-Means Clustering, we identified 8 specific non-overlapping clusters of various sizes, which emerged from this huge network of protein-interactors. Since the functionally interacting partners are closely associated with each other, alterations in one might affect the other, thus contributing to disease etiology. In conclusion, our results highlight the interaction of p53 gene network, which modulates hundreds of proteins with a trigger of MDM signaling. Investigating these modulator or trigger proteins as key signaling factors could form targets for new therapeutic intervention sites. Further, these functionally interacting partners of disease proteins could help uncover novel disease mechanisms. From a scientific point of view, our ‘STRING’ results have clearly shown the importance of p53 signaling pathways in leukemia.