Identifying potential therapeutic targets for T-cell acute lymphoblastic leukemia using malignant networks and topological analysis

Abstract

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive and heterogeneous disease requiring new therapeutic targets. We identified overexpressed genes in T-ALL cell lines, built subnetworks using the IntAct interactome, and evaluated the topological role of each gene. An attack strategy, removing one gene at a time, was applied with eleven network measures and persistent homology. A positive control group of essential genes for T-ALL tumorigenesis was included. Clustering, largest connected component, and especially Betti 1 effectively distinguished control genes from others, showing that topological metrics are valuable for target identification. Notably, NPM1 emerged as a key gene for maintaining network integrity, promoting proliferation, and ensuring survival, highlighting its potential as a promising therapeutic target in T-ALL. Significance of the studyThis study proposes an innovative approach to finding therapeutic targets for T-ALL based on oncogenic protein-protein interaction networks and the identification of the most effective analysis metrics following network attacks. These findings can be broadly applied to any neoplasm, seeking more personalized and efficient therapy.