Development and validation of the immune signature for LUAD

The cases from the TCGA database were used as the training set to develop the immune signature. Univariate analysis and logRank test were used to identify immune related genes with prognostic ability. For the genes with prognostic ability, Cox proportional hazards model (iteration = 1000) with an lasso penalty was used to find the best gene model utilizing a R package called “glmnet” [16]. The best gene model was used to establish the immune signature. Then, the concordance (c)-index proposed by Harrell et al. [17] was applied to validate the predictive ability of the signature in all of the five datasets, by using the “survcomp” R package [18]. The larger c-index indicated the more accurate predictive ability of the model.