DocumentCode :
140149
Title :
Biomarkers from biosimulations: Transcriptome-to-reactome™ Technology for individualized medicine
Author :
Phelix, Clyde F. ; Villareal, Greg ; LeBaron, Richard G. ; Roberson, Dawnlee J.
Author_Institution :
Univ. of Texas at San Antonio, San Antonio, TX, USA
fYear :
2014
fDate :
26-30 Aug. 2014
Firstpage :
3452
Lastpage :
3455
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.
Keywords :
RNA; biomembranes; cancer; mammography; molecular biophysics; probability; sensitivity analysis; tumours; Fagan nomogram; TGF-β signaling pathway; benign tumor; biomarkers; biosimulations; clinical sensitivity; clinical specificity; derivative properties; diagnostic decision making; gene expression profiles; individualized medicine; malignant breast cancer; membrane signaling marker; nuclear transcription factor marker; patent-pending technique; positive mammogram probability; sensitivity analyses; transcriptome-to-reactome technology; treatment decision making; Analytical models; Biological system modeling; Biomarkers; Cancer; Gene expression; Mathematical model; Sensitivity; diagnostic sensitivity; diagnostic specificity; individualized medicine; simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
ISSN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2014.6944365
Filename :
6944365
Link To Document :
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