title: A novel network model identified a 13-gene lung cancer prognostic signature.
abstract: This study presents a novel network methodology to identify prognostic gene signatures. Implication networks based on prediction logic are used to construct genome-wide coexpression networks for different disease states. From the differential components associated with specific disease states, candidate genes that are co-expressed with major disease signal hallmarks are selected. From these candidate genes, top genes that are the most predictive of clinical outcome are identified using univariate Cox model and Relief algorithm. Using this approach, a 13-gene lung cancer prognosis signature was identified, which generated significant prognostic stratifications (log-rank P < 0.05) in Director's Challenge Study (n = 442).
authors.affiliation: Mary Babb Randolph Cancer Centre, Department of Community Medicine, West Virginia University, Morgantown, WV 26506-9300, USA. lguo@hsc.wvu.edu
authors.forename: Nancy Lan
authors.initials: NL
authors.lastname: Guo
authors.forename: Ying-Wooi
authors.initials: YW
authors.lastname: Wan
authors.forename: Swetha
authors.initials: S
authors.lastname: Bose
authors.forename: James
authors.initials: J
authors.lastname: Denvir
authors.forename: Michael L
authors.initials: ML
authors.lastname: Kashon
authors.forename: Michael E
authors.initials: ME
authors.lastname: Andrew
mesh_terms: D000230:Adenocarcinoma / Q000235:genetics / Q000378:metabolism / Q000473:pathology; D000077192:Adenocarcinoma of Lung; D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D055106:Genome-Wide Association Study; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D008297:Male; D008957:Models, Genetic; D009367:Neoplasm Staging; D011379:Prognosis; D016016:Proportional Hazards Models; D015398:Signal Transduction