Now showing items 1-17 of 17

    • canSAR: an integrated cancer public translational research and drug discovery resource. 

      Halling-Brown, MD; Bulusu, KC; Patel, M; Tym, JE; Al-Lazikani, B (2012-01)
      canSAR is a fully integrated cancer research and drug discovery resource developed to utilize the growing publicly available biological annotation, chemical screening, RNA interference screening, expression, amplification ...
    • canSAR: updated cancer research and drug discovery knowledgebase. 

      Bulusu, KC; Tym, JE; Coker, EA; Schierz, AC; Al-Lazikani, B (2014-01)
      canSAR ( is a public integrative cancer-focused knowledgebase for the support of cancer translational research and drug discovery. Through the integration of biological, pharmacological, chemical, ...
    • ChEMBL: a large-scale bioactivity database for drug discovery. 

      Gaulton, A; Bellis, LJ; Bento, AP; Chambers, J; Davies, M; Hersey, A; Light, Y; McGlinchey, S; Michalovich, D; Al-Lazikani, B; Overington, JP (2012-01)
      ChEMBL is an Open Data database containing binding, functional and ADMET information for a large number of drug-like bioactive compounds. These data are manually abstracted from the primary published literature on a regular ...
    • Combinatorial drug therapy for cancer in the post-genomic era. 

      Al-Lazikani, B; Banerji, U; Workman, P (2012-07-10)
      Over the past decade, whole genome sequencing and other 'omics' technologies have defined pathogenic driver mutations to which tumor cells are addicted. Such addictions, synthetic lethalities and other tumor vulnerabilities ...
    • A comprehensive map of molecular drug targets. 

      Santos, R; Ursu, O; Gaulton, A; Bento, AP; Donadi, RS; Bologa, CG; Karlsson, A; Al-Lazikani, B; Hersey, A; Oprea, TI; Overington, JP (2017-01)
      The success of mechanism-based drug discovery depends on the definition of the drug target. This definition becomes even more important as we try to link drug response to genetic variation, understand stratified clinical ...
    • Development of Bag-1L as a therapeutic target in androgen receptor-dependent prostate cancer. 

      Cato, L; Neeb, A; Sharp, A; Buzón, V; Ficarro, SB; Yang, L; Muhle-Goll, C; Kuznik, NC; Riisnaes, R; Nava Rodrigues, D; Armant, O; Gourain, V; Adelmant, G; Ntim, EA; Westerling, T; Dolling, D; Rescigno, P; Figueiredo, I; Fauser, F; Wu, J; Rottenberg, JT; Shatkina, L; Ester, C; Luy, B; Puchta, H; Troppmair, J; Jung, N; Bräse, S; Strähle, U; Marto, JA; Nienhaus, GU; Al-Lazikani, B; Salvatella, X; de Bono, JS; Cato, AC; Brown, M (2017-08-10)
      Targeting the activation function-1 (AF-1) domain located in the N-terminus of the androgen receptor (AR) is an attractive therapeutic alternative to the current approaches to inhibit AR action in prostate cancer (PCa). ...
    • Drug discovery in advanced prostate cancer: translating biology into therapy. 

      Yap, TA; Smith, AD; Ferraldeschi, R; Al-Lazikani, B; Workman, P; de Bono, JS (2016-10)
      Castration-resistant prostate cancer (CRPC) is associated with a poor prognosis and poses considerable therapeutic challenges. Recent genetic and technological advances have provided insights into prostate cancer biology ...
    • Genomics, bio specimens, and other biological data: Current status and future directions. 

      Rosenstein, BS; Rao, A; Moran, JM; Spratt, DE; Mendonca, MS; Al-Lazikani, B; Mayo, CS; Speers, C (2018-10)
    • Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines. 

      Campbell, J; Ryan, CJ; Brough, R; Bajrami, I; Pemberton, HN; Chong, IY; Costa-Cabral, S; Frankum, J; Gulati, A; Holme, H; Miller, R; Postel-Vinay, S; Rafiq, R; Wei, W; Williamson, CT; Quigley, DA; Tym, J; Al-Lazikani, B; Fenton, T; Natrajan, R; Strauss, SJ; Ashworth, A; Lord, CJ (2016-03-02)
      One approach to identifying cancer-specific vulnerabilities and therapeutic targets is to profile genetic dependencies in cancer cell lines. Here, we describe data from a series of siRNA screens that identify the kinase ...
    • Leveraging human genetics to guide cancer drug development 

      Kinnersley, B; Sud, A; Coker, EA; Tym, JE; Di Micco, P; Al-Lazikani, B; Houlston, RS
    • A novel serum protein signature associated with resistance to epidermal growth factor receptor tyrosine kinase inhibitors in head and neck squamous cell carcinoma. 

      Box, C; Mendiola, M; Gowan, S; Box, GM; Valenti, M; Brandon, AH; Al-Lazikani, B; Rogers, SJ; Wilkins, A; Harrington, KJ; Eccles, SA (2013-07)
      BACKGROUND: Acquired resistance to tyrosine kinase inhibitors (TKIs) is becoming a major challenge in the treatment of many cancers. Epidermal growth factor receptor (EGFR) is overexpressed in squamous carcinomas, notably ...
    • Objective, Quantitative, Data-Driven Assessment of Chemical Probes. 

      Antolin, AA; Tym, JE; Komianou, A; Collins, I; Workman, P; Al-Lazikani, B (2018-02-15)
      Chemical probes are essential tools for understanding biological systems and for target validation, yet selecting probes for biomedical research is rarely based on objective assessment of all potential compounds. Here, we ...
    • Polypharmacology in Precision Oncology: Current Applications and Future Prospects. 

      Antolin, AA; Workman, P; Mestres, J; Al-Lazikani, B (2016-09-23)
      Over the past decade, a more comprehensive, large-scale approach to studying cancer genetics and biology has revealed the challenges of tumor heterogeneity, adaption, evolution and drug resistance, while systems-based ...
    • Rational design of non-resistant targeted cancer therapies. 

      Martínez-Jiménez, F; Overington, JP; Al-Lazikani, B; Marti-Renom, MA (2017-04-24)
      Drug resistance is one of the major problems in targeted cancer therapy. A major cause of resistance is changes in the amino acids that form the drug-target binding site. Despite of the numerous efforts made to individually ...
    • Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets. 

      Wedge, DC; Gundem, G; Mitchell, T; Woodcock, DJ; Martincorena, I; Ghori, M; Zamora, J; Butler, A; Whitaker, H; Kote-Jarai, Z; Alexandrov, LB; Van Loo, P; Massie, CE; Dentro, S; Warren, AY; Verrill, C; Berney, DM; Dennis, N; Merson, S; Hawkins, S; Howat, W; Lu, Y-J; Lambert, A; Kay, J; Kremeyer, B; Karaszi, K; Luxton, H; Camacho, N; Marsden, L; Edwards, S; Matthews, L; Bo, V; Leongamornlert, D; McLaren, S; Ng, A; Yu, Y; Zhang, H; Dadaev, T; Thomas, S; Easton, DF; Ahmed, M; Bancroft, E; Fisher, C; Livni, N; Nicol, D; Tavaré, S; Gill, P; Greenman, C; Khoo, V; Van As, N; Kumar, P; Ogden, C; Cahill, D; Thompson, A; Mayer, E; Rowe, E; Dudderidge, T; Gnanapragasam, V; Shah, NC; Raine, K; Jones, D; Menzies, A; Stebbings, L; Teague, J; Hazell, S; Corbishley, C; CAMCAP Study Group; de Bono, J; Attard, G; Isaacs, W; Visakorpi, T; Fraser, M; Boutros, PC; Bristow, RG; Workman, P; Sander, C; TCGA Consortium; Hamdy, FC; Futreal, A; McDermott, U; Al-Lazikani, B; Lynch, AG; Bova, GS; Foster, CS; Brewer, DS; Neal, DE; Cooper, CS; Eeles, RA (2018-05)
      Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer ...
    • SiGNet: A signaling network data simulator to enable signaling network inference. 

      Coker, EA; Mitsopoulos, C; Workman, P; Al-Lazikani, B (2017)
      Network models are widely used to describe complex signaling systems. Cellular wiring varies in different cellular contexts and numerous inference techniques have been developed to infer the structure of a network from ...