Development of an immune-related gene pairs signature for predicting clinical outcome in lung adenocarcinoma

Abstract

Background Lung adenocarcinoma (LUAD) is the main pathological subtype of Non-small cell lung cancer. The aim of this study was to establish an immune-related gene pairs (IRGPs) signature for predicting the prognosis of LUAD patients.Methods We downloaded the gene expression profile and immune-related gene set from TCGA and ImmPort database, respectively, to establish IRGPs. Then, IRGPs subjected to univariate Cox regression analysis, LASSO regression analysis and multivariable Cox regression analysis to screen and develop a IRGPs signature. The receiver operating characteristic curve (ROC) was applied for evaluating the predicting accuracy of this signature by calculating the area under ROC (AUC) and data from GEO was used to validate this signature.Results A IRGPs signature with 8 IRGPs was constructed. The AUC for 1- and 3-year overall survival in TCGA set was 0.867 and 0.870, respectively. Similar result was observed in the AUC of GEO set and Total set (GEO set [1-year: 0.819; 3-years: 0.803]; Total set [1-year: 0.845; 3-years: 0.801]). Survival analysis of three sets demonstrated high-risk LUAD patients exhibited poorer prognosis. The multivariable Cox regression indicated that risk score was independent prognostic factors.Conclusions We developed a novel IRGPs signature for predicting prognosis of LUAD.

An Immune-Related Gene Pairs Signature Predicts Overall Survival in Melanoma

“…This method has been reported to have reliable results in many studies, including molecular classi cation of cancer. [12][13][14] In the present study, we identi ed an immune-related gene pair signature to predict overall survival for melanoma patients. The prognostic signature consists of 25 immune-related gene pairs (IRGPs) containing 41 unique IRGs.…”

“…[11] In recent years, a new method based on relative ranking of gene expression level has been proposed to eliminate the shortcomings of data normalization and scaling in gene expression data processing, and reliable results have been obtained in various researches. [12][13][14] There is growing evidence that the immune system plays a key role in the development and progression of melanoma. [15] In 2014, nivolumab and pembrolizumab, two checkpoint inhibitors binding to PD-1, were approved for the treatment of metastatic melanoma.…”