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综合分析以鉴定肺腺癌的一种新型诊断标志物及其免疫浸润图谱。

Comprehensive analysis to identify a novel diagnostic marker of lung adenocarcinoma and its immune infiltration landscape.

作者信息

Zhu Ankang, Pei Dongchen, Zong Yan, Fan Yan, Wei Shuai, Xing Zhisong, Song Shuailin, Wang Xin, Gao Xingcai

机构信息

The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China.

Department of Cardiothoracic Surgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China.

出版信息

Front Oncol. 2023 Jun 20;13:1199608. doi: 10.3389/fonc.2023.1199608. eCollection 2023.

DOI:10.3389/fonc.2023.1199608
PMID:37409245
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10319060/
Abstract

BACKGROUND

Lung cancer continues to be a problem faced by all of humanity. It is the cancer with the highest morbidity and mortality in the world, and the most common histological type of lung cancer is lung adenocarcinoma (LUAD), accounting for about 40% of lung malignant tumors. This study was conducted to discuss and explore the immune-related biomarkers and pathways during the development and progression of LUAD and their relationship with immunocyte infiltration.

METHODS

The cohorts of data used in this study were downloaded from the Gene Expression Complex (GEO) database and the Cancer Genome Atlas Program (TCGA) database. Through the analysis of differential expression analysis, weighted gene co-expression network analysis (WGCNA), and least absolute shrinkage and selection operator(LASSO), selecting the module with the highest correlation with LUAD progression, and then the HUB gene was further determined. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were then used to study the function of these genes. Single-sample GSEA (ssGSEA) analysis was used to investigate the penetration of 28 immunocytes and their relationship with HUB genes. Finally, the receiver operating characteristic curve (ROC) was used to evaluate these HUB genes accurately to diagnose LUAD. In addition, additional cohorts were used for external validation. Based on the TCGA database, the effect of the HUB genes on the prognosis of LUAD patients was assessed using the Kaplan-Meier curve. The mRNA levels of some HUB genes in cancer cells and normal cells were analyzed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).

RESULTS

The turquoise module with the highest correlation with LUAD was identified among the seven modules obtained with WGCNA. Three hundred fifty-four differential genes were chosen. After LASSO analysis, 12 HUB genes were chosen as candidate biomarkers for LUAD expression. According to the immune infiltration results, CD4 + T cells, B cells, and NK cells were high in LUAD sample tissue. The ROC curve showed that all 12 HUB genes had a high diagnostic value. Finally, the functional enrichment analysis suggested that the HUB gene is mainly related to inflammatory and immune responses. According to the RT-qPCR study, we found that the expression of DPYSL2, OCIAD2, and FABP4 in A549 was higher than BEAS-2B. The expression content of DPYSL2 was lower in H1299 than in BEAS-2B. However, the expression difference of FABP4 and OCIAD2 genes in H1299 lung cancer cells was insignificant, but both showed a trend of increase.

CONCLUSIONS

The mechanism of LUAD pathogenesis and progression is closely linked to T cells, B cells, and monocytes. 12 HUB genes(ADAMTS8, CD36, DPYSL2, FABP4, FGFR4, HBA2, OCIAD2, PARP1, PLEKHH2, STX11, TCF21, TNNC1) may participate in the progression of LUAD immune-related signaling pathways.

摘要

背景

肺癌仍然是全人类面临的一个问题。它是世界上发病率和死亡率最高的癌症,最常见的肺癌组织学类型是肺腺癌(LUAD),约占肺恶性肿瘤的40%。本研究旨在探讨和探索LUAD发生发展过程中的免疫相关生物标志物和信号通路及其与免疫细胞浸润的关系。

方法

本研究中使用的数据队列从基因表达综合数据库(GEO)和癌症基因组图谱计划(TCGA)数据库下载。通过差异表达分析、加权基因共表达网络分析(WGCNA)和最小绝对收缩和选择算子(LASSO)分析,选择与LUAD进展相关性最高的模块,进而确定核心基因。然后使用基因本体论(GO)、京都基因与基因组百科全书(KEGG)和基因集富集分析(GSEA)来研究这些基因的功能。采用单样本GSEA(ssGSEA)分析来研究28种免疫细胞的浸润情况及其与核心基因的关系。最后,使用受试者工作特征曲线(ROC)准确评估这些核心基因以诊断LUAD。此外,使用额外的数据队列进行外部验证。基于TCGA数据库,使用Kaplan-Meier曲线评估核心基因对LUAD患者预后的影响。通过逆转录定量聚合酶链反应(RT-qPCR)分析癌细胞和正常细胞中一些核心基因的mRNA水平。

结果

在WGCNA获得的七个模块中,鉴定出与LUAD相关性最高的蓝绿色模块。选择了354个差异基因。经过LASSO分析,选择了12个核心基因作为LUAD表达的候选生物标志物。根据免疫浸润结果,LUAD样本组织中CD4 + T细胞、B细胞和NK细胞含量较高。ROC曲线显示,所有12个核心基因都具有较高的诊断价值。最后,功能富集分析表明,核心基因主要与炎症和免疫反应相关。根据RT-qPCR研究,我们发现DPYSL2、OCIAD2和FABP4在A549中的表达高于BEAS-2B。DPYSL2在H1299中的表达含量低于BEAS-2B。然而,FABP4和OCIAD2基因在H1299肺癌细胞中的表达差异不显著,但均呈上升趋势。

结论

LUAD发病机制和进展的机制与T细胞、B细胞和单核细胞密切相关。12个核心基因(ADAMTS8、CD36、DPYSL2、FABP4、FGFR4、HBA2、OCIAD2、PARP1、PLEKHH2、STX11、TCF21、TNNC1)可能参与LUAD免疫相关信号通路的进展。

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