title: Data integration to prioritize drugs using genomics and curated data.
abstract: BACKGROUND
  Genomic alterations affecting drug target proteins occur in several tumor types and are prime candidates for patient-specific tailored treatments. Increasingly, patients likely to benefit from targeted cancer therapy are selected based on molecular alterations. The selection of a precision therapy benefiting most patients is challenging but can be enhanced with integration of multiple types of molecular data. Data integration approaches for drug prioritization have successfully integrated diverse molecular data but do not take full advantage of existing data and literature.
  
  
  RESULTS
  We have built a knowledge-base which connects data from public databases with molecular results from over 2200 tumors, signaling pathways and drug-target databases. Moreover, we have developed a data mining algorithm to effectively utilize this heterogeneous knowledge-base. Our algorithm is designed to facilitate retargeting of existing drugs by stratifying samples and prioritizing drug targets. We analyzed 797 primary tumors from The Cancer Genome Atlas breast and ovarian cancer cohorts using our framework. FGFR, CDK and HER2 inhibitors were prioritized in breast and ovarian data sets. Estrogen receptor positive breast tumors showed potential sensitivity to targeted inhibitors of FGFR due to activation of FGFR3.
  
  
  CONCLUSIONS
  Our results suggest that computational sample stratification selects potentially sensitive samples for targeted therapies and can aid in precision medicine drug repositioning. Source code is available from http://csblcanges.fimm.fi/GOPredict/.
authors.affiliation: Genome Scale Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Helsinki, FI-00014 Finland.
authors.forename: Riku
authors.initials: R
authors.lastname: Louhimo
authors.affiliation: Genome Scale Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Helsinki, FI-00014 Finland.
authors.forename: Marko
authors.initials: M
authors.lastname: Laakso
authors.affiliation: Translational Cancer Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Helsinki, FI-00014 Finland.
authors.forename: Denis
authors.initials: D
authors.lastname: Belitskin
authors.affiliation: Translational Cancer Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Helsinki, FI-00014 Finland.
authors.forename: Juha
authors.initials: J
authors.lastname: Klefström
authors.affiliation: Genome Scale Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Helsinki, FI-00014 Finland.
authors.forename: Rainer
authors.initials: R
authors.lastname: Lehtonen
authors.affiliation: Genome Scale Biology Research Program, Research Programs Unit, Faculty of Medicine, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Helsinki, FI-00014 Finland.
authors.forename: Sampsa
authors.initials: S
authors.lastname: Hautaniemi
keywords: Breast cancer; Cancer; Data integration; Drug prioritization; Gene ontology