title: Outsmarting cancer: the power of hybrid genomic/proteomic biomarkers to predict drug response.
abstract: A recent study by Niepel and colleagues describes a novel approach to predicting response to targeted anti-cancer therapies. The authors used biochemical profiling of signaling activity in basal and ligand-stimulated states for a panel of receptor and intracellular kinases to develop predictive models of drug sensitivity. In some cases, the response to ligand stimulation predicted drug response better than did target abundance or genomic alterations in the targeted pathway. Furthermore, combining biochemical profiles with genomic information was better at predicting drug response. This work suggests that incorporating biochemical signaling profiles with genomic alterations should provide powerful predictors of response to molecularly targeted therapies.
authors.forename: Brent N
authors.initials: BN
authors.lastname: Rexer
authors.forename: Carlos L
authors.initials: CL
authors.lastname: Arteaga
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use*; D014408:Biomarkers, Tumor / Q000037:antagonists & inhibitors* / Q000235:genetics / Q000378:metabolism; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000235:genetics / Q000378:metabolism; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000379:methods; D019869:Phosphatidylinositol 3-Kinases / Q000235:genetics / Q000378:metabolism; D051057:Proto-Oncogene Proteins c-akt / Q000235:genetics / Q000378:metabolism; D015398:Signal Transduction / Q000187:drug effects* / Q000235:genetics; D059467:Transcriptome
chemical_list: D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor; D019869:Phosphatidylinositol 3-Kinases; D051057:Proto-Oncogene Proteins c-akt