Network based modelling for Neuroblastoma drug discovery
Sam Lee, Nathan P. Williams, Belamy B. Cheung, Glenn Marshall, Jessica K. Holien · 2019
Neuroblastoma is the most common solid tumour in infants. However, due to its heterogeneous presentation successful treatment is rare even with intensive multi-modal therapy. Treatment of Neuroblastoma is further affected by the high rates of refractory and relapsed metastasis that occur in patients. There currently is an unmet need for treatments specific to this relapsed form of the disease. While a number of proteins have been associated with Neuroblastoma (e.g., N-MYC) no druggable targets have been found to date. By utilising multiple extensive public protein-protein interaction networks together with transcriptomic data from Neuroblastoma patients we can identify which aspects of the interaction networks are perturbed within primary and relapsed neuroblastoma. Further, by integration of structural data for proteins in our networks protein interactions between targets that are amenable to structure based drug design can be prioritised for cell based assays. This combination of disease specific data with databases detailing protein interactions and structures allows for richer prediction of potential targets for treatment of Neuroblastoma.