Introduction: Genomics analysis of intratumour heterogeneity and drug resistance mechanisms in cancer medicine
Session type: Parallel sessions
Drug resistance contributes to early treatment failure and deteriorating quality of life in patients with cancer. Deriving gene expression signature based predictors of cancer drug response from microarray data is an associative learning process and is inherently vulnerable to over-fitting of data. To address this problem, RNA interference screening approaches are increasingly being used to identify functionally relevant gene modules predictive of therapeutic response. Parallel developments in clinical trial design, enabling sequential tumour tissue genomics analysis during treatment and following acquisition of drug resistance, when integrated with functional genomics analyses are likely to contribute to the discovery of tumour and stromal-derived biomarkers governing response to therapy. Finally, intra-tumour heterogeneity is likely to impact upon biomarker validation, the acquisition of drug resistance and the implementation of personalised medicine approaches. This session will review developments in the field of functional genomics approaches to the discovery of predictive biomarkers of response to therapy and challenges imposed by intra-tumour heterogeneity on biomarker validation and drug resistance.