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Identification of candidate genes and prognostic value analysis in patients with PDL1-positive and PDL1-negative lung adenocarcinoma

PDL1-positive 和 PDL1-negative 肺腺癌候选基因的筛选及预后价值分析

  • 影响因子:2.50
  • DOI:10.7717/peerj.9362
  • 作者列表:"Xiaoguang Qi","Chunyan Qi","Xindan Kang","Yi Hu","Weidong Han
  • 发表时间:2020-06-20
Abstract

Background Increasing bodies of evidence reveal that targeting a programmed cell death protein 1 (PD-1) monoclonal antibody is a promising immunotherapy for lung adenocarcinoma. Although PD receptor ligand 1 (PDL1) expression is widely recognized as the most powerful predictive biomarker for anti-PD-1 therapy, its regulatory mechanisms in lung adenocarcinoma remain unclear. Therefore, we conducted this study to explore differentially expressed genes (DEGs) and elucidate the regulatory mechanism of PDL1 in lung adenocarcinoma. Methods The GSE99995 data set was obtained from the Gene Expression Omnibus (GEO) database. Patients with and without PDL1 expression were divided into PDL1-positive and PDL1-negative groups, respectively. DEGs were screened using R. The Gene Ontology (GO) database and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed using the Database for Annotation, Visualization and Integrated Discovery. Protein–protein interaction (PPI) networks of DEGs was visualized using Cytoscape, and the MNC algorithm was applied to screen hub genes. A survival analysis involving Gene Expression Profiling Interactive Analysis was used to verify the GEO results. Mutation characteristics of the hub genes were further analyzed in a combined study of five datasets in The Cancer Genome Atlas (TCGA) database. Results In total, 869 DEGs were identified, 387 in the PDL1-positive group and 482 in the PDL1-negative group. GO and KEGG analysis results of the PDL1-positive group mainly exhibited enrichment of biological processes and pathways related to cell adhesion and the peroxisome proliferators-activated receptors (PPAR) signaling pathway, whereas biological process and pathways associated with cell division and repair were mainly enriched in the PDL1-negative group. The top 10 hub genes were screened during the PPI network analysis. Notably, survival analysis revealed BRCA1, mainly involved in cell cycle and DNA damage responses, to be a novel prognostic indicator in lung adenocarcinoma. Moreover, the prognosis of patients with different forms of lung adenocarcinoma was associated with differences in mutations and pathways in potential hub genes. Conclusions PDL1-positive lung adenocarcinoma and PDL1-negative lung adenocarcinoma might be different subtypes of lung adenocarcinoma. The hub genes might play an important role in PDL1 regulatory pathways. Further studies on hub genes are warranted to reveal new mechanisms underlying the regulation of PDL1 expression. These results are crucial for understanding and applying precision immunotherapy for lung adenocarcinoma.

摘要

背景越来越多的证据表明,靶向程序性细胞死亡蛋白 1 (PD-1) 单克隆抗体是一种很有前途的肺腺癌免疫治疗方法。尽管 pd1 受体配体 1 (PDL1) 的表达被广泛认为是 anti-PD-1 治疗最强有力的预测生物标志物,但其在肺腺癌中的调控机制仍不清楚。因此,我们进行这项研究是为了探索差异表达基因 (DEGs),阐明 PDL1 在肺腺癌中的调控机制。方法从 Gene Expression Omnibus (GEO) 数据库中获得 GSE99995 数据集。将 PDL1 表达的患者分为 PDL1-positive 组和 PDL1-negative 组。使用 R 筛选 DEGs。使用该数据库对 Gene Ontology (GO) 数据库和京都基因和基因组百科全书 (KEGG) 进行了分析,用于注释、可视化和整合发现。使用 Cytoscape 可视化 DEGs 的蛋白质-蛋白质相互作用 (PPI) 网络,并应用 MNC 算法筛选枢纽基因。使用涉及基因表达谱交互分析的生存分析来验证 GEO 结果。在癌症基因组图谱 (TCGA) 数据库中 5 个数据集的联合研究中进一步分析了 hub 基因的突变特征。结果共检出 869 例 DEGs,PDL1-positive 组 387 例,PDL1-negative 组 482 例。PDL1-positive 组 GO 和 KEGG 分析结果主要表现为细胞黏附相关的生物学过程和通路的富集以及过氧化物酶体增殖物激活受体 (PPAR) 信号通路,而与细胞分裂和修复相关的生物学过程和途径主要富集在 PDL1-negative 组。PPI 网络分析期间筛选了前 10 个 hub 基因。值得注意的是,生存分析显示 BRCA1 主要参与细胞周期和 DNA 损伤反应,是肺腺癌的一个新的预后指标。此外,不同形式肺腺癌患者的预后与潜在枢纽基因的突变和通路差异相关。结论 PDL1-positive 肺腺癌和 PDL1-negative 肺腺癌可能是肺腺癌的不同亚型。Hub 基因可能在 PDL1 调控通路中发挥重要作用。需要对 hub 基因进行进一步研究,以揭示 PDL1 表达调控的新机制。这些结果对于理解和应用肺腺癌的精准免疫治疗至关重要。

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影响因子:1.84
发表时间:2020-01-01
来源期刊:Oncology letters
DOI:10.3892/ol.2019.11149
作者列表:["Das SK","Huang YY","Li B","Yu XX","Xiao RH","Yang HF"]

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影响因子:8.44
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