Abstract 4383: SOCRATES: integrating ex vivo and in silico analysis to identify optimal drug combinations for patients

Abstract

Abstract Recent work on cancer heterogeneity and evolution has greatly enhanced our understanding of drivers of drug resistance, but this has also highlighted the need to move away from generic, “one-size-fits-all” treatment regimes. It is clear that we should tailor therapy to individual patients at different stages of disease based on the current behaviour of their tumour cells, yet detailed experimental characterisation and analysis of patient tissue is impractical and costly. Predictive computational models that can produce patient-specific recommendations of drug combinations would therefore be of great value to the field of personalised medicine. In silico modelling has already been used to successfully predict synergistic drug combinations in single cell lines in the lab, but such approaches have not yet been translated to dynamic, real patient data in the clinic. The SOCRATES project (Signalling output to rationalise combinations of targeted anticancer therapies) integrates experimental data and computational analysis to predict context-specific synergistic drug combinations. Here we present ambitious computational modelling of dynamic signalling network changes in response to ex vivo exposure of seven targeted drugs used singly at clinically appropriate concentrations. We also apply our adaptive modelling to genomics and proteomics data from 54 proteins in over 30 non small-cell lung cancer cell lines and ten patient samples to predict and experimentally validate personalised, context specific drug combinations. We will describe our adaptive, in silico modelling for predicting response to drug combinations, including novel methods utilizing network topology. We have predicted over 50 synergistic drug combinations and will present our predictions alongside initial results of experimental validation in the lab. We will also illustrate the differences observed in various cell lines and patient derived cells depending on genetic context. SOCRATES is, to our knowledge, the first project of its kind and is a prototype for the future of adaptive, individualised cancer treatment. Citation Format: Elizabeth A. Coker, Adam Stewart, Anna Minchom, Mary O’Brien, Timothy Yap, Paul Workman, Udai Banerji, Bissan Al-Lazikani. SOCRATES: integrating ex vivo and in silico analysis to identify optimal drug combinations for patients. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4383.