Abstract
Biological networks display high robustness against random failures but are vulnerable to targeted attacks on central nodes. Thus, network topology analysis represents a powerful tool for investigating network susceptibility against targeted node removal. Here, we built protein interaction networks associated with chemoresistance to temozolomide, an alkylating agent used in glioma therapy, and analyzed their modular structure and robustness against intentional attack. These networks showed functional modules related to DNA repair, immunity, apoptosis, cell stress, proliferation and migration. Subsequently, network vulnerability was assessed by means of centrality-based attacks based on the removal of node fractions in descending orders of degree, betweenness, or the product of degree and betweenness. This analysis revealed that removing nodes with high degree and high betweenness was more effective in altering networks’ robustness parameters, suggesting that their corresponding proteins may be particularly relevant to target temozolomide resistance. In silico data was used for validation and confirmed that central nodes are more relevant for altering proliferation rates in temozolomide-resistant glioma cell lines and for predicting survival in glioma patients. Altogether, these results demonstrate how the analysis of network vulnerability to topological attack facilitates target prioritization for overcoming cancer chemoresistance.
Highlights
The topological analysis of scale-free networks demonstrated their high degree of tolerance against network fragmentation after random failures[8]
The molecular mechanisms of therapeutic resistance have been extensively investigated in cancer research, which resulted in the addition of novel drugs to standard chemotherapies for overcoming cancer resistance[29]
We explored here protein-protein interaction networks associated to TMZ resistance in order to predict key targets for tackling glioma drug resistance
Summary
The topological analysis of scale-free networks demonstrated their high degree of tolerance against network fragmentation after random failures[8]. For gliomas, primary malignant brain tumors with poor survival rates, the acquired resistance to the alkylating agent temozolomide (TMZ) remains a major challenge limiting its clinical efficacy[13,14]. In this field, there is a paucity of information about the molecular mechanisms underlying TMZ resistance. We analyzed here the topological features of protein interaction networks linked to TMZ resistance and their resilience against targeted attack in order to reveal key targets for overcoming drug resistance in glioma These targets were validated in silico using proliferation data from temozolomide-resistant glioma cells and co-occurrence relationships between gene expression levels and the prognosis of glioma patients
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