Development and validation of a robust immune-related prognostic signature in early-stage lung adenocarcinoma

Abstract

Background The incidence of stage I and stage II lung adenocarcinoma (LUAD) is likely to increase with the introduction of annual screening programs for high-risk individuals. We aimed to identify a reliable prognostic signature with immune-related genes that can predict prognosis and help making individualized management for patients with early-stage LUAD. Methods The public LUAD cohorts were obtained from the large-scale databases including 4 microarray data sets from the Gene Expression Omnibus (GEO) and 1 RNA-seq data set from The Cancer Genome Atlas (TCGA) LUAD cohort. Only early-stage patients with clinical information were included. Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set). The prognostic signature was developed using the overlapped prognostic genes based on a risk score method. Kaplan–Meier curve with log-rank test and time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic value and performance of this signature, respectively. Furthermore, the robustness of this prognostic signature was further validated in TCGA-LUAD and GSE72094 cohorts. Results A prognostic immune signature consisting of 21 immune-related genes was constructed using the training set. The prognostic signature significantly stratified patients into high- and low-risk groups in terms of overall survival (OS) in training data set, including GSE30219 (HR = 4.31, 95% CI 2.29–8.11; P = 6.16E−06), GSE31210 (HR = 11.91, 95% CI 4.15–34.19; P = 4.10E−06), GSE50081 (HR = 3.63, 95% CI 1.90–6.95; P = 9.95E−05), the combined data set (HR = 3.15, 95% CI 1.98–5.02; P = 1.26E−06) and the validation data set, including TCGA-LUAD (HR = 2.16, 95% CI 1.49–3.13; P = 4.54E−05) and GSE72094 (HR = 2.95, 95% CI 1.86–4.70; P = 4.79E−06). Multivariate cox regression analysis demonstrated that the 21-gene signature could serve as an independent prognostic factor for OS after adjusting for other clinical factors. ROC curves revealed that the immune signature achieved good performance in predicting OS for early-stage LUAD. Several biological processes, including regulation of immune effector process, were enriched in the immune signature. Moreover, the combination of the signature with tumor stage showed more precise classification for prognosis prediction and treatment design. Conclusions Our study proposed a robust immune-related prognostic signature for estimating overall survival in early-stage LUAD, which may be contributed to make more accurate survival risk stratification and individualized clinical management for patients with early-stage LUAD.

Characterization of the Different Subtypes of Immune Cell Infiltration to Aid Immunotherapy

“…Consistent with these findings, the patients in gene cluster A exhibit better prognosis than gene cluster B and C. The anti-cancer immune response in gene cluster A is associated with favorable prognosis and we believe that the patients in gene cluster A may benefit from immunotherapy. In order to identify the role of higher immune cell infiltration in improving patient survival, the GSEA analysis was performed, and the results showed that the immunological response-related pathways have been well activated, such as pathways related to positive regulation of cytokine production ( Giles et al, 2018 ; Fisher et al, 2019 ), regulation of immune effector process ( Wu et al, 2020b ), and leukocyte proliferation ( MollicaPoeta et al, 2019 ). And the relative biomarker expression of cytokines also confirmed this result.…”

Characterization of the Different Subtypes of Immune Cells Infiltration to Aid Immunotherapy

“…Consistent with these ndings, the patients in gene cluster A exhibits the better prognosis than gene cluster B and C. The anti-cancer immune response in gene cluster A is associated with favorable prognosis and we believed that the patients in gene cluster A may bene t from the immunotherapy. In order to identify the role of higher immune cell in ltration in improving the patient survival, the GSEA analysis was performed and the results showed that the immunological response-related pathways have been well activated, such as pathway related to positive regulation of cytokine production [33][34] , regulation of immune effector process 35 , leukocyte proliferation 36 etc. And, the relative biomarker expression of cytokines also con rmed this result.…”

Immune landscape and a promising immune prognostic model associated with TP53 in early‐stage lung adenocarcinoma

“…Similarly, in 2020, Liang et al also proposed a promising 21-gene-based prognostic immune prediction model for early-stage LUAD patients in the TCGA cohort. 52 The C-index, a frequently utilized evaluation indicator for survival models, was estimated through "pec" R package utilizing a bootstrap manner under 1000 resampling, thus comparing the predictive performance of the previously published prognostic signatures and our IPM. A higher C-index value indicates the more favorable predictive performance of the model.…”