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

IF 1.9 4区医学 Q3 RESPIRATORY SYSTEM Clinical Respiratory Journal Pub Date : 2024-05-17 DOI:10.1111/crj.13755

Yidan Sun, Qianqian Ma, Yixun Chen, Dongying Liao, Fanming Kong

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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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肺腺癌预后免疫细胞稳态特征的识别与分析

背景肺腺癌（LUAD）是呼吸系统中侵袭性最强的恶性肿瘤之一。它也是导致肺腺癌患者死亡的常见病理类型。维持免疫细胞的平衡是抗肿瘤免疫疗法的重要途径。然而，维持免疫平衡的生物学意义和免疫治疗效果尚未得到很好的研究。方法我们根据 B 细胞和 T 细胞平衡相关基因构建了一个 LUAD 诊断和预后模型。采用最小绝对收缩和选择算子（LASSO）分析和多变量 Cox 回归确定预后基因特征。根据LUAD患者的总生存时间和生存状态，随后从The Cancer Genome Atlas (TCGA)-LUAD中确定了由ABL1、BAK1、IKBKB、PPP2R3C、CCNB2、CORO1A、FADD、P2RX7、TNFSF14和ZC3H8组成的10个基因预后模型作为预后标志物，从而建立了预后特征。本研究根据基因表达谱构建了基因预后模型，并通过生存分析以及1年、3年和5年ROC曲线分析获得了相应的生存信息。富集分析试图揭示预后基因的潜在作用机制和分子途径。CIBERSORT 算法计算了每个样本中 22 个免疫细胞的浸润程度，并比较了高危组和低危组免疫细胞浸润的差异。在细胞层面，利用 PCR 和 CKK8 实验分别验证了所构建的 10 基因模型的表达差异及其对细胞活力的影响。实验结果支持了该分子模型在肺癌预后中的重要生物学意义和潜在应用价值。富集分析表明，这些基因主要与淋巴细胞稳态有关。结论我们发现了一种新的免疫细胞稳态预后特征。以这些免疫细胞平衡预后基因为靶点可能是治疗肺癌的一种选择。预测模型的可靠性在生物信息学水平、细胞水平和基因水平上都得到了证实。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinical Respiratory Journal 医学-呼吸系统

CiteScore

3.70

自引率

0.00%

发文量

104

审稿时长

>12 weeks

期刊介绍： Overview Effective with the 2016 volume, this journal will be published in an online-only format. Aims and Scope The Clinical Respiratory Journal (CRJ) provides a forum for clinical research in all areas of respiratory medicine from clinical lung disease to basic research relevant to the clinic. We publish original research, review articles, case studies, editorials and book reviews in all areas of clinical lung disease including: Asthma Allergy COPD Non-invasive ventilation Sleep related breathing disorders Interstitial lung diseases Lung cancer Clinical genetics Rhinitis Airway and lung infection Epidemiology Pediatrics CRJ provides a fast-track service for selected Phase II and Phase III trial studies. Keywords Clinical Respiratory Journal, respiratory, pulmonary, medicine, clinical, lung disease, Abstracting and Indexing Information Academic Search (EBSCO Publishing) Academic Search Alumni Edition (EBSCO Publishing) Embase (Elsevier) Health & Medical Collection (ProQuest) Health Research Premium Collection (ProQuest) HEED: Health Economic Evaluations Database (Wiley-Blackwell) Hospital Premium Collection (ProQuest) Journal Citation Reports/Science Edition (Clarivate Analytics) MEDLINE/PubMed (NLM) ProQuest Central (ProQuest) Science Citation Index Expanded (Clarivate Analytics) SCOPUS (Elsevier)