摘要
The high risk of postoperative mortality in lung adenocarcinoma(LUAD)patients is principally driven by cancer recurrence and low response rates to adjuvant treatment.Here,A combined cohort containing 1,026 stageⅠ-Ⅲpatients was divided into the learning(n Z 678)and validation datasets(n Z 348).The former was used to establish a 16-mRNA risk signature for recurrence prediction with multiple statistical algorithms,which was verified in the valida-tion set.Univariate and multivariate analyses confirmed it as an independent indicator for both recurrence-free survival(RFS)and overall survival(OS).Distinct molecular characteristics between the two groups including genomic alterations,and hallmark pathways were compre-hensively analyzed.Remarkably,the classifier was tightly linked to immune infiltrations,high-lighting the critical role of immune surveillance in prolonging survival for LUAD.Moreover,the classifier was a valuable predictor for therapeutic responses in patients,and the low-risk group was more likely to yield clinical benefits from immunotherapy.A transcription factor regulato-ry proteineprotein interaction network(TF-PPI-network)was constructed via weighted gene co-expression network analysis(WGCNA)concerning the hub genes of the signature.The con-structed multidimensional nomogram dramatically increased the predictive accuracy.There-fore,our signature provides a forceful basis for individualized LUAD management with promising potential implications.
