Developing new paradigms for overcoming drug resistance in cancer using novel humanised mouse models

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Although there have been significant advances in the development of new treatments for cancer, where the drugs are now targeted at the genetic changes which drive tumour growth, major challenges still exist in translating this into long-term patient survival. In addition, drug side-effects particularly of new combination treatments, continue to be a major problem. The reason why the often dramatic patient responses, have not resulted in sustained long-term survival is because the tumours rapidly become resistant to the high concentrations of these very potent drugs. Whereas there is currently an enormous emphasis on cancer genomics, tumour cell heterogeneity, microenvironment, etc., there are essentially no studies on drug pharmacology i.e. how to use the new drugs optimally. Defining the pharmacology of emerging targeted anti-cancer drugs, rather than using dosing regimens based on MTD, has to be a fundamental component of developing new effective treatments for cancer, particularly for drug combinations. Understanding how best to use targeted agents can make the difference between success and failure of potentially promising new treatment regimens.Historical evidence, based particularly on the treatment of infectious diseases, has taught us that drug resistance can be overcome by either using combinations of drugs concomitantly, or by altering the drug dosing regimen. A major challenge for the improved treatment of cancer is therefore which combination of drugs should be used and what is the dosing schedule? Based on the enormous number of emerging targeted anti-tumour agents, it is impossible to address this challenge by clinical trial alone, and new pre-clinical models which are more predictive of patient responses are urgently needed. An important difference between animal models and humans is how drugs are handled by the body. This results in different rates of drug exposure and elimination and different drug metabolites. To address this problem, we have made a number of genetically altered mouse models in which drugs are metabolised in a manner similar to that observed in humans. It is the aim of this project to establish the potential of this model system to predict drug responses in man and to use this model to test whether drugs are still effective, alone or in combination, at doses which will be tolerated by patients. Our ultimate aim is to develop a computer-based model which will be used for the informed design of combination clinical trials which delay the onset of drug resistance. If successful, the application of the model systems developed in this programme could be of enormous benefit for the improved treatment of cancer, both in terms of patient survival and reduction in drug side-effects. The model validated in this programme could be of great for the development of new drugs, not only for the treatment of cancer but also for the treatment of other human diseases.