Network analysis of immunotherapy-induced regressing tumours identifies novel synergistic drug combinations

Willem Lesterhuis, C. Rinaldi, Anya Jones, Esdy Rozali, Ian Dick, Andrea Khong, L. Boon, Bruce Robinson, Anna Nowak, Anthony Bosco, Richard Lake

Research output: Contribution to journalArticlepeer-review

53 Citations (Web of Science)


© 2015, Nature Publishing Group. All rights reserved. Cancer immunotherapy has shown impressive results, but most patients do not respond. We hypothesized that the effector response in the tumour could be visualized as a complex network of interacting gene products and that by mapping this network we could predict effective pharmacological interventions. Here, we provide proof of concept for the validity of this approach in a murine mesothelioma model, which displays a dichotomous response to anti-CTLA4 immune checkpoint blockade. Network analysis of gene expression profiling data from responding versus non-responding tumours was employed to identify modules associated with response. Targeting the modules via selective modulation of hub genes or alternatively by using repurposed pharmaceuticals selected on the basis of their expression perturbation signatures dramatically enhanced the efficacy of CTLA4 blockade in this model. Our approach provides a powerful platform to repurpose drugs, and define contextually relevant novel therapeutic targets.
Original languageEnglish
Article number12298
Pages (from-to)1-11
Number of pages11
JournalScientific Reports
Publication statusPublished - 21 Jul 2015


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