G-DOC: a systems medicine platform for personalized oncology.

Currently, cancer therapy remains limited by a "one-size-fits-all" approach, whereby treatment decisions are based mainly on the clinical stage of disease, yet fail to reference the individual's underlying biology and its role driving malignancy. Identifying better personalized therapies for cancer treatment is hindered by the lack of high-quality "omics" data of sufficient size to produce meaningful results and the ability to integrate biomedical data from disparate technologies. Resolving these issues will help translation of therapies from research to clinic by helping clinicians develop patient-specific treatments based on the unique signatures of patient's tumor. Here we describe the Georgetown Database of Cancer (G-DOC), a Web platform that enables basic and clinical research by integrating patient characteristics and clinical outcome data with a variety of high-throughput research data in a unified environment. While several rich data repositories for high-dimensional research data exist in the public domain, most focus on a single-data type and do not support integration across multiple technologies. Currently, G-DOC contains data from more than 2500 breast cancer patients and 800 gastrointestinal cancer patients, G-DOC includes a broad collection of bioinformatics and systems biology tools for analysis and visualization of four major "omics" types: DNA, mRNA, microRNA, and metabolites. We believe that G-DOC will help facilitate systems medicine by providing identification of trends and patterns in integrated data sets and hence facilitate the use of better targeted therapies for cancer. A set of representative usage scenarios is provided to highlight the technical capabilities of this resource.

[1]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[2]  Leroy Hood,et al.  Systems biology, proteomics, and the future of health care: toward predictive, preventative, and personalized medicine. , 2004, Journal of proteome research.

[3]  Elizabeth M. Smigielski,et al.  dbSNP: the NCBI database of genetic variation , 2001, Nucleic Acids Res..

[4]  Chris F. Taylor,et al.  A common open representation of mass spectrometry data and its application to proteomics research , 2004, Nature Biotechnology.

[5]  Scott L. Zeger,et al.  The Analysis of Gene Expression Data: Methods and Software , 2013 .

[6]  D. Lancet,et al.  GeneCards: integrating information about genes, proteins and diseases. , 1997, Trends in genetics : TIG.

[7]  C. Burge,et al.  Most mammalian mRNAs are conserved targets of microRNAs. , 2008, Genome research.

[8]  Dennis B. Troup,et al.  NCBI GEO: mining millions of expression profiles—database and tools , 2004, Nucleic Acids Res..

[9]  Yue Joseph Wang,et al.  Analyzing DNA Copy Number Changes Using Fused Margin Regression , 2009, 2009 IEEE International Conference on Bioinformatics and Biomedicine.

[10]  Joshua M. Stuart,et al.  MICROARRAY EXPERIMENTS : APPLICATION TO SPORULATION TIME SERIES , 1999 .

[11]  L. Hood,et al.  Systems medicine: the future of medical genomics and healthcare , 2009, Genome Medicine.

[12]  B. McEwen,et al.  Characterization of the vulnerability to repeated stress in Fischer 344 rats: possible involvement of microRNA‐mediated down‐regulation of the glucocorticoid receptor , 2008, The European journal of neuroscience.

[13]  L. O’Driscoll,et al.  Molecular medicine of microRNAs: structure, function and implications for diabetes , 2008, Expert Reviews in Molecular Medicine.

[14]  D. Valle,et al.  Online Mendelian Inheritance In Man (OMIM) , 2000, Human mutation.

[15]  L. Stein,et al.  JBrowse: a next-generation genome browser. , 2009, Genome research.

[16]  M. J. van de Vijver,et al.  Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. , 2006, Journal of the National Cancer Institute.

[17]  Terence P. Speed,et al.  A comparison of normalization methods for high density oligonucleotide array data based on variance and bias , 2003, Bioinform..

[18]  D. Roukos.  Systems medicine: a real approach for future personalized oncology? , 2010, Pharmacogenomics.

[19]  E. Kaplan,et al.  Nonparametric Estimation from Incomplete Observations , 1958 .

[20]  Jian Zhang,et al.  The Protein Information Resource: an integrated public resource of functional annotation of proteins , 2002, Nucleic Acids Res..

[21]  Joe W. Gray,et al.  Translating insights from the cancer genome into clinical practice , 2008, Nature.

[22]  Keith W. Boone,et al.  Pediatric palliative care and eHealth opportunities for patient-centered care. , 2011, American journal of preventive medicine.

[23]  Gianluca Bontempi,et al.  Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen , 2008, BMC Genomics.

[24]  Ana Kozomara,et al.  miRBase: integrating microRNA annotation and deep-sequencing data , 2010, Nucleic Acids Res..

[25]  Zhaohui Huang,et al.  Plasma microRNAs are promising novel biomarkers for early detection of colorectal cancer , 2010, International journal of cancer.

[26]  Richard Simon,et al.  A random variance model for detection of differential gene expression in small microarray experiments , 2003, Bioinform..

[27]  Cheng Li,et al.  DNA-Chip Analyzer (dChip) , 2003 .

[28]  Lucila Ohno-Machado,et al.  Translational bioinformatics: linking knowledge across biological and clinical realms , 2011, J. Am. Medical Informatics Assoc..

[29]  Daniel Birnbaum,et al.  Genome profiling of ERBB2-amplified breast cancers , 2010, BMC Cancer.

[30]  M. Castellano,et al.  The human A-myb protein is a strong activator of transcription. , 1994, Oncogene.

[31]  I. Shih,et al.  Analysis of DNA copy number alterations in ovarian serous tumors identifies new molecular genetic changes in low-grade and high-grade carcinomas. , 2009, Cancer research.

[32]  C. Croce,et al.  MicroRNA signatures in human cancers , 2006, Nature Reviews Cancer.

[33]  Sergio Contrino,et al.  ArrayExpress—a public repository for microarray gene expression data at the EBI , 2004, Nucleic Acids Res..

[34]  T. Speed,et al.  Summaries of Affymetrix GeneChip probe level data. , 2003, Nucleic acids research.

[35]  David Botstein,et al.  The Stanford Microarray Database , 2001, Nucleic Acids Res..

[36]  C. Croce,et al.  MicroRNA signatures in human ovarian cancer. , 2007, Cancer research.

[37]  Alok J. Saldanha,et al.  Java Treeview - extensible visualization of microarray data , 2004, Bioinform..

[38]  Damian Szklarczyk,et al.  The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored , 2010, Nucleic Acids Res..

[39]  Stijn van Dongen,et al.  miRBase: microRNA sequences, targets and gene nomenclature , 2005, Nucleic Acids Res..

[40]  T. Callis,et al.  Taking microRNAs to heart. , 2008, Trends in molecular medicine.

[41]  Thomas D. Schmittgen,et al.  Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. , 2001, Methods.

[42]  W. Schlegel,et al.  Proteomics in cancer. , 2007, Advances in clinical chemistry.

[43]  Holger Sültmann,et al.  Serum microRNAs as non-invasive biomarkers for cancer , 2010, Molecular Cancer.

[44]  T. Barrette,et al.  ONCOMINE: a cancer microarray database and integrated data-mining platform. , 2004, Neoplasia.

[45]  T. Ideker,et al.  Network-based classification of breast cancer metastasis , 2007, Molecular systems biology.

[46]  Subha Madhavan,et al.  Rembrandt: Helping Personalized Medicine Become a Reality through Integrative Translational Research , 2009, Molecular Cancer Research.

[47]  Thomas D. Schmittgen,et al.  Real-time PCR quantification of precursor and mature microRNA. , 2008, Methods.

[48]  Mark A. Dente,et al.  Pediatric Palliative Care in the Age of eHealth: Opportunities for Advances in HIT to Improve Patient-Centered Communication , 2013 .

[49]  Jean YH Yang,et al.  Bioconductor: open software development for computational biology and bioinformatics , 2004, Genome Biology.