cancer translational research and drug discovery and the provision of these data through a ﬂexible user interface. canSAR’s aim is to aid informed hypothesis generation and cancer translational research by a more comprehen- sive, yet concise, view of relevant data, and enabling powerful interrogation and reporting tools. canSAR contains large amounts of data from a variety of sources including chemical screening, gene expression, RNA inter- ference, genomic variation, protein–protein interaction and 3D structural data. A user-driven web interface has been designed and implemented to provide tailored entry methods, and allow logical exploration and interrogation of data within canSAR. The interface allows users to obtain answers to common cancer research questions, such as rapidly obtaining biological and chemical annota- tion together with druggability considerations, explore genomic variation and gene-expression data, identify rele- vant cell lines for experiments, and tool compounds for analysis. Throughout the various levels of the interface, data can be exported in a variety of manners including Excel, SDF and MIABE XML. Also, if registered, user speciﬁc work spaces are available which save searches, ﬁlters and allow larger batch queries to be run. Over the next year, canSAR will be expanded to contain a much larger body of biological data particularly gene expression and RNAi screening data and ex- panded annotation of clinical samples and cell lines. Additionally, in collaboration with protein–protein inter- action data providers listed above, we aim to integrate directionality data into the network diagrams wherever possible. Integrating masses of publicly available information in a consistent and up-to-date manner, canSAR is the largest integrated cancer research and drug discovery resource freely available. The efforts that an individual researcher would have to undertake to collect and process similar amounts of data sources for information on a given target, cell line or compound of interest cannot be over- stated. canSAR removes this arduous and time-consuming step of data collection and processing and provides an intuitive centralized repository of data, allowing research- ers to focus more quickly on speciﬁc areas of interest, or to eliminate potentially time consuming leads early on. Using canSAR, these types of decisions can be better informed and can be made after having taken the whole background of a target into account. SUPPLEMENTARY DATA Supplementary Data are available at NAR Supplementary Figures 1 and 2. Online: ACKNOWLEDGEMENTS The authors acknowledge data providers (ChEMBL, BindingDB, ArrayExpress, Genomics of Drug Sensitivity, Pathway Commons, STRING, ROCK and COSMIC). The authors also thank the users at the Cancer Therapeutics division, Institute of Cancer Research, who have provided ideas and feedback. Nucleic Acids Research, 2012, Vol. 40, Database issue D955 FUNDING Cancer Research UK core drug discovery grant to the ICR [C309/A8274]. NHS funding to the NIHR Biomedical Research Centre. Funding for open access charge: Cancer Research UK grant to the ICR [C309/A8274]. Conﬂict of interest statement. None declared. REFERENCES 1. Schlabach,M., Luo,J., Solimini,N., Hu,G., Xu,Q., Li,M., Zhao,Z., Smogorzewska,A., Sowa,M., Ang,X. et al. (2008) Cancer proliferation gene discovery through functional genomics. Science, 319, 620–624. 2. Zheng-Bradley,X., Rung,J., Parkinson,H. and Brazma,A. (2010) Large scale comparison of global gene expression patterns in human and mouse. 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