title: Biomarkers from biosimulations: Transcriptome-To-Reactome™ Technology for individualized medicine.
abstract: We validated a model of the TGF-β signaling pathway using reactions from Reactome. Using a patentpending technique, gene expression profiles from individual patients are used to determine model parameters. Gene expression profiles from 45 women, normal, or benign tumor and malignant breast cancer were used as training and validating sets for assessing clinical sensitivity and specificity. Biomarkers were identified from the biosimulation results using sensitivity analyses and derivative properties from the model. A membrane signaling marker had sensitivity of 80% and specificity of 60%; while a nuclear transcription factor marker had sensitivity of 80% and specificity of 90% to predict malignancy. Use of Fagan's nomogram increased probability from 7.5% for positive mammogram to 39% with positive results of the biosimulation for the nuclear marker. Our technology will allow researchers to identify and develop biomarkers and assist clinicians in diagnostic and treatment decision making.
authors.forename: Clyde F
authors.initials: CF
authors.lastname: Phelix
authors.forename: Greg
authors.initials: G
authors.lastname: Villareal
authors.forename: Richard G
authors.initials: RG
authors.lastname: LeBaron
authors.forename: Dawnlee J
authors.initials: DJ
authors.lastname: Roberson
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism*; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics; D003198:Computer Simulation; D005260:Female; D006801:Humans; D057285:Precision Medicine; D015203:Reproducibility of Results; D015398:Signal Transduction / Q000235:genetics; D013997:Time Factors; D059467:Transcriptome; D016212:Transforming Growth Factor beta / Q000378:metabolism
chemical_list: D014408:Biomarkers, Tumor; D016212:Transforming Growth Factor beta