Literature-based discovery of new candidates for drug repurposing

Drug development is an expensive and time-consuming process; these could be reduced if the existing resources could be used to identify candidates for drug repurposing. This study sought to do this by text mining a large-scale literature repository to curate repurposed drug lists for different cancers. We devised a pattern-based relationship extraction method to extract disease-gene and gene-drug direct relationships from the literature. These direct relationships are used to infer indirect relationships using the ABC model. A gene-shared ranking method based on drug target similarity was then proposed to prioritize the indirect relationships. Our method of assessing drug target similarity correlated to existing anatomical therapeutic chemical code-based methods with a Pearson correlation coefficient of 0.9311. The indirect relationships ranking method achieved a significant mean average precision score of top 100 most common diseases. We also confirmed the suitability of candidates identified for repurposing as anticancer drugs by conducting a manual review of the literature and the clinical trials. Eventually, for visualization and enrichment of huge amount of repurposed drug information, a chord diagram was demonstrated to rapidly identify two novel indications for further biological evaluations.

[1]  Jie Li,et al.  Prediction of Polypharmacological Profiles of Drugs by the Integration of Chemical, Side Effect, and Therapeutic Space , 2013, J. Chem. Inf. Model..

[2]  Yi-Ting Huang,et al.  Condensing biomedical journal texts through paragraph ranking , 2011, Bioinform..

[3]  Alessandro Moschitti,et al.  A Study on Dependency Tree Kernels for Automatic Extraction of Protein-Protein Interaction , 2011, BioNLP@ACL.

[4]  Vassilis Virvilis,et al.  Literature mining, ontologies and information visualization for drug repurposing , 2011, Briefings Bioinform..

[5]  S. Grando,et al.  Connections of nicotine to cancer , 2014, Nature Reviews Cancer.

[6]  Yang Song,et al.  Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery , 2011, Nucleic Acids Res..

[7]  Shinya Ohara,et al.  Lymphoepithelioma-like carcinoma of the urinary bladder: a case report and review of the literature , 2014, BMC Research Notes.

[8]  M. Boccadoro,et al.  Thalidomide for treatment of multiple myeloma: 10 years later. , 2008, Blood.

[9]  Chao Wu,et al.  Computational drug repositioning through heterogeneous network clustering , 2013, BMC Systems Biology.

[10]  T F Lue,et al.  Oral sildenafil in the treatment of erectile dysfunction. Sildenafil Study Group. , 1998, The New England journal of medicine.

[11]  Xiaoyan Zhu,et al.  GeneTUKit: a software for document-level gene normalization , 2011, Bioinform..

[12]  T. Ashburn,et al.  Drug repositioning: identifying and developing new uses for existing drugs , 2004, Nature Reviews Drug Discovery.

[13]  Sampo Pyysalo,et al.  Overview of BioNLP’09 Shared Task on Event Extraction , 2009, BioNLP@HLT-NAACL.

[14]  Rong Xu,et al.  Large-scale extraction of accurate drug-disease treatment pairs from biomedical literature for drug repurposing , 2013, BMC Bioinformatics.

[15]  Kong-Peng Lam,et al.  Integrative analysis workflow for the structural and functional classification of C-type lectins , 2011, BMC Bioinformatics.

[16]  D. Swanson.  Fish Oil, Raynaud's Syndrome, and Undiscovered Public Knowledge , 2015, Perspectives in biology and medicine.

[17]  Therese Miller,et al.  Aspirin for the Primary Prevention of Cardiovascular Events: An Update of the Evidence for the U.S. Preventive Services Task Force , 2009, Annals of Internal Medicine.

[18]  Mahitosh Mandal,et al.  Celecoxib alleviates tamoxifen-instigated angiogenic effects by ROS-dependent VEGF/VEGFR2 autocrine signaling , 2013, BMC Cancer.

[19]  Thomas C. Wiegers,et al.  The Comparative Toxicogenomics Database: update 2013 , 2012, Nucleic Acids Res..

[20]  Zhiyong Lu,et al.  DNorm: disease name normalization with pairwise learning to rank , 2013, Bioinform..

[21]  Susumu Goto,et al.  KEGG for integration and interpretation of large-scale molecular data sets , 2011, Nucleic Acids Res..

[22]  P. Rothwell,et al.  Effects of regular aspirin on long-term cancer incidence and metastasis: a systematic comparison of evidence from observational studies versus randomised trials. , 2012, The Lancet. Oncology.

[23]  Sahdeo Prasad,et al.  Cancer drug discovery by repurposing: teaching new tricks to old dogs. , 2013, Trends in pharmacological sciences.

[24]  Ralph Debusmann,et al.  Dependency Grammar: Classification and Exploration , 2011, Resource-Adaptive Cognitive Processes.

[25]  Sanda M. Harabagiu,et al.  Using Predicate-Argument Structures for Information Extraction , 2003, ACL.

[26]  Jie Li,et al.  Rapamycin combined with celecoxib enhanced antitumor effects of mono treatment on chronic myelogenous leukemia cells through downregulating mTOR pathway , 2014, Tumor Biology.

[27]  Goran Nenadic,et al.  Using SVMs with the Command Relation features to identify negated events in biomedical literature , 2010, NeSp-NLP@ACL.

[28]  Susan M Resnick,et al.  Effects of tamoxifen and raloxifene on memory and other cognitive abilities: cognition in the study of tamoxifen and raloxifene. , 2009, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[29]  R. Altman,et al.  Pharmacogenomics Knowledge for Personalized Medicine , 2012, Clinical pharmacology and therapeutics.

[30]  Bo Li,et al.  Simultaneous targeting of EGFR and mTOR inhibits the growth of colorectal carcinoma cells. , 2012, Oncology reports.

[31]  Razvan C. Bunescu,et al.  A Shortest Path Dependency Kernel for Relation Extraction , 2005, HLT.

[32]  J. DiMasi,et al.  Risks in new drug development: Approval success rates for investigational drugs , 2001, Clinical pharmacology and therapeutics.

[33]  A. Fleischer,et al.  Thalidomide: current and potential clinical applications. , 2000, The American journal of medicine.

[34]  Aron Culotta,et al.  Dependency Tree Kernels for Relation Extraction , 2004, ACL.

[35]  D. Swanson.  Migraine and Magnesium: Eleven Neglected Connections , 2015, Perspectives in biology and medicine.

[36]  Jacob de Vlieg,et al.  Literature Mining for the Discovery of Hidden Connections between Drugs, Genes and Diseases , 2010, PLoS Comput. Biol..

[37]  R. Tagliaferri,et al.  Discovery of drug mode of action and drug repositioning from transcriptional responses , 2010, Proceedings of the National Academy of Sciences.

[38]  Van V. Brantner,et al.  Estimating the cost of new drug development: is it really 802 million dollars? , 2006, Health affairs.

[39]  Hung-Yu Kao,et al.  Cross-species gene normalization by species inference , 2011, BMC Bioinformatics.

[40]  Chitta Baral,et al.  Identifying Novel Drug Indications through Automated Reasoning , 2012, PloS one.

[41]  Feng Xu,et al.  Therapeutic target database update 2014: a resource for targeted therapeutics , 2013, Nucleic Acids Res..

[42]  George Hripcsak,et al.  Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study. , 2008, Journal of the American Medical Informatics Association : JAMIA.

[43]  Khaled Greish,et al.  A Novel Role for Raloxifene Nanomicelles in Management of Castrate Resistant Prostate Cancer , 2014, BioMed research international.

[44]  Young Tae Kim,et al.  Synergistic Effect of COX-2 Inhibitor on Paclitaxel-Induced Apoptosis in the Human Ovarian Cancer Cell Line OVCAR-3 , 2014, Cancer research and treatment : official journal of Korean Cancer Association.

[45]  Therese Miller,et al.  Aspirin for the Primary Prevention of Cardiovascular Events , 2009 .

[46]  Manuel J. Maña López,et al.  A machine-learning approach to negation and speculation detection in clinical texts , 2012, J. Assoc. Inf. Sci. Technol..

[47]  I. Goldstein,et al.  Oral sildenafil in the treatment of erectile dysfunction. Sildenafil Study Group. , 1998, The New England journal of medicine.

[48]  Jagruti Patel,et al.  Systematic drug repurposing through text mining. , 2014, Methods in molecular biology.

[49]  Deepika Pandey,et al.  Memory enhancement by Tamoxifen on amyloidosis mouse model , 2016, Hormones and Behavior.