Characterization of lung adenocarcinoma based on immunophenotyping and constructing an immune scoring model to predict prognosis

Mengfeng Liu; Qifan Xiao; Xiran Yu; Yujie Zhao; Changfa Qu

doi:10.3389/fphar.2022.1081244

Characterization of lung adenocarcinoma based on immunophenotyping and constructing an immune scoring model to predict prognosis

Front Pharmacol. 2022 Dec 19:13:1081244. doi: 10.3389/fphar.2022.1081244. eCollection 2022.

Authors

Mengfeng Liu¹, Qifan Xiao¹, Xiran Yu¹, Yujie Zhao², Changfa Qu¹

Affiliations

¹ Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin Medical Sciences University, Harbin, China.
² Regional Marketing Department, YuceBio Technology Co., Shenzhen, China.

Abstract

Background: Lung cancer poses great threat to human health, and lung adenocarcinoma (LUAD) is the main subtype. Immunotherapy has become first line therapy for LUAD. However, the pathogenic mechanism of LUAD is still unclear. Methods: We scored immune-related pathways in LUAD patients using single sample gene set enrichment analysis (ssGSEA) algorithm, and further identified distinct immune-related subtypes through consistent clustering analysis. Next, immune signatures, Kaplan-Meier survival analysis, copy number variation (CNV) analysis, gene methylation analysis, mutational analysis were used to reveal differences between subtypes. pRRophetic method was used to predict the response to chemotherapeutic drugs (half maximal inhibitory concentration). Then, weighted gene co-expression network analysis (WGCNA) was performed to screen hub genes. Significantly, we built an immune score (IMscore) model to predict prognosis of LUAD. Results: Consensus clustering analysis identified three LUAD subtypes, namely immune-Enrich subtype (Immune-E), stromal-Enrich subtype (Stromal-E) and immune-Deprived subtype (Immune-D). Stromal-E subtype had a better prognosis, as shown by Kaplan-Meier survival analysis. Higher tumor purity and lower immune cell scores were found in the Immune-D subtype. CNV analysis showed that homologous recombination deficiency was lower in Stromal-E and higher in Immune-D. Likewise, mutational analysis found that the Stromal-E subtype had a lower mutation frequency in TP53 mutations. Difference in gene methylation (ZEB2, TWIST1, CDH2, CDH1 and CLDN1) among three subtypes was also observed. Moreover, Immune-E was more sensitive to traditional chemotherapy drugs Cisplatin, Sunitinib, Crizotinib, Dasatinib, Bortezomib, and Midostaurin in both the TCGA and GSE cohorts. Furthermore, a 6-gene signature was constructed to predicting prognosis, which performed better than TIDE score. The performance of IMscore model was successfully validated in three independent datasets and pan-cancer.

Keywords: LUAD; immune; immune scoring model; immunophenotyping; prognosis.