Identification and analysis of prognostic immune cell homeostasis characteristics in lung adenocarcinoma

免疫系统 生物 生存分析 比例危险模型 腺癌 肿瘤科 免疫疗法 基因 癌症研究 免疫学 癌症 内科学 医学 遗传学
作者
Yidan Sun,Qianqian Ma,Yixun Chen,Dongying Liao,Fanming Kong
出处
期刊:Clinical Respiratory Journal [Wiley]
卷期号:18 (5)
标识
DOI:10.1111/crj.13755
摘要

Abstract Background Lung adenocarcinoma (LUAD) is one of the most invasive malignant tumor of the respiratory system. It is also the common pathological type leading to the death of LUAD. Maintaining the homeostasis of immune cells is an important way for anti‐tumor immunotherapy. However, the biological significance of maintaining immune homeostasis and immune therapeutic effect has not been well studied. Methods We constructed a diagnostic and prognostic model for LUAD based on B and T cells homeostasis‐related genes. Minimum absolute contraction and selection operator (LASSO) analysis and multivariate Cox regression are used to identify the prognostic gene signatures. Based on the overall survival time and survival status of LUAD patients, a 10‐gene prognostic model composed of ABL1, BAK1, IKBKB, PPP2R3C, CCNB2, CORO1A, FADD, P2RX7, TNFSF14, and ZC3H8 was subsequently identified as prognostic markers from The Cancer Genome Atlas (TCGA)‐LUAD to develop a prognostic signature. This study constructed a gene prognosis model based on gene expression profiles and corresponding survival information through survival analysis, as well as 1‐year, 3‐year, and 5‐year ROC curve analysis. Enrichment analysis attempted to reveal the potential mechanism of action and molecular pathway of prognostic genes. The CIBERSORT algorithm calculated the infiltration degree of 22 immune cells in each sample and compared the difference of immune cell infiltration between high‐risk group and low‐risk group. At the cellular level, PCR and CKK8 experiments were used to verify the differences in the expression of the constructed 10‐gene model and its effects on cell viability, respectively. The experimental results supported the significant biological significance and potential application value of the molecular model in the prognosis of lung cancer. Enrichment analyses showed that these genes were mainly related to lymphocyte homeostasis. Conclusion We identified a novel immune cell homeostasis prognostic signature. Targeting these immune cell homeostasis prognostic genes may be an alternative for LUAD treatment. The reliability of the prediction model was confirmed at bioinformatics level, cellular level, and gene level.

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