A novel network model identified a 13-gene lung cancer prognostic signature

摘要: This study presents a novel network methodology to identify prognostic gene signatures. Implication networks based on prediction logic are used construct genome-wide coexpression for different disease states. From the differential components associated with specific states, candidate genes that co-expressed major signal hallmarks selected. these genes, top most predictive of clinical outcome identified using univariate Cox model and Relief algorithm. Using this approach, 13-gene lung cancer prognosis signature was identified, which generated significant stratifications (log-rank P < 0.05) in Director's Challenge Study (n = 442).