title: Creation of a Human Secretome: A Novel Composite Library of Human Secreted Proteins: Validation Using Ovarian Cancer Gene Expression Data and a Virtual Secretome Array.
abstract: OBJECTIVE
  To generate a comprehensive "Secretome" of proteins potentially found in the blood and derive a virtual Affymetrix array. To validate the utility of this database for the discovery of novel serum-based biomarkers using ovarian cancer transcriptomic data.
  
  
  METHODS
  The secretome was constructed by aggregating the data from databases of known secreted proteins, transmembrane or membrane proteins, signal peptides, G-protein coupled receptors, or proteins existing in the extracellular region, and the virtual array was generated by mapping them to Affymetrix probeset identifiers. Whole-genome microarray data from ovarian cancer, normal ovarian surface epithelium, and fallopian tube epithelium were used to identify transcripts upregulated in ovarian cancer.
  
  
  RESULTS
  We established the secretome from eight public databases and a virtual array consisting of 16,521 Affymetrix U133 Plus 2.0 probesets. Using ovarian cancer transcriptomic data, we identified candidate blood-based biomarkers for ovarian cancer and performed bioinformatic validation by demonstrating rediscovery of known biomarkers including CA125 and HE4. Two novel top biomarkers (FGF18 and GPR172A) were validated in serum samples from an independent patient cohort.
  
  
  CONCLUSIONS
  We present the secretome, comprising the most comprehensive resource available for protein products that are potentially found in the blood. The associated virtual array can be used to translate gene-expression data into cancer biomarker discovery. A list of blood-based biomarkers for ovarian cancer detection is reported and includes CA125 and HE4. FGF18 and GPR172A were identified and validated by ELISA as being differentially expressed in the serum of ovarian cancer patients compared with controls.
authors.affiliation: Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts. Harvard Medical School, Boston, Massachusetts.
authors.forename: Vinod
authors.initials: V
authors.lastname: Vathipadiekal
authors.affiliation: Harvard Medical School, Boston, Massachusetts. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
authors.forename: Victoria
authors.initials: V
authors.lastname: Wang
authors.affiliation: Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts. Harvard Medical School, Boston, Massachusetts.
authors.forename: Wei
authors.initials: W
authors.lastname: Wei
authors.affiliation: Harvard Medical School, Boston, Massachusetts. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts. City University of New York, New York, New York.
authors.forename: Levi
authors.initials: L
authors.lastname: Waldron
authors.affiliation: Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.
authors.forename: Ronny
authors.initials: R
authors.lastname: Drapkin
authors.affiliation: Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts. Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
authors.forename: Michael
authors.initials: M
authors.lastname: Gillette
authors.affiliation: Harvard Medical School, Boston, Massachusetts. Biostatistics Unit, Massachusetts General Hospital, Boston, Massachusetts.
authors.forename: Steven
authors.initials: S
authors.lastname: Skates
authors.affiliation: Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts. Harvard Medical School, Boston, Massachusetts. MBIRRER@mgh.harvard.edu.
authors.forename: Michael
authors.initials: M
authors.lastname: Birrer
mesh_terms: D014408:Biomarkers, Tumor; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D030541:Databases, Genetic; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D015723:Gene Library; D006801:Humans; D010051:Ovarian Neoplasms / Q000235:genetics / Q000378:metabolism*; D020543:Proteome / Q000378:metabolism*; D040901:Proteomics / Q000379:methods; D015203:Reproducibility of Results; D015398:Signal Transduction; D059467:Transcriptome
chemical_list: D014408:Biomarkers, Tumor; D020543:Proteome