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Article(id=1149776903122412261, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149776900194791454, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2402571, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1712592000000, receivedDateStr=2024-04-09, revisedDate=1730044800000, revisedDateStr=2024-10-28, acceptedDate=null, acceptedDateStr=null, onlineDate=1752057775525, onlineDateStr=2025-07-09, pubDate=1744905600000, pubDateStr=2025-04-18, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752057775525, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752057775525, creator=13701087609, updateTime=1752057775525, updator=13701087609, issue=Issue{id=1149776900194791454, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='11', pageStart='4397', pageEnd='4826', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752057774827, creator=13701087609, updateTime=1768456666677, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1218558837930512931, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149776900194791454, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1218558837930512932, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1149776900194791454, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=4467, endPage=4475, ext={EN=ArticleExt(id=1149776903353098983, articleId=1149776903122412261, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Investigate the Role and Mechanism of Rheumatoid Arthritis-related Pathways in Lung Squamous Cell Carcinoma Based on Bioinformatics Combined with Mendelian Randomization Analysis, columnId=1156262732384031076, journalTitle=Science Technology and Engineering, columnName=Papers·Medicine, runingTitle=null, highlight=null, articleAbstract=

In order to investigate the role of rheumatoid arthritis (RA)-related pathways in lung squamous cell carcinoma (LSCC). By obtaining gene expression data for RA and LSCC from the GEO and TCGA database, differentially expressed genes were screened using GEO2R tool and Rstudio software. GO/KEGG functional enrichment analysis identified key genes in the RA signaling pathway. Combining SNP data from the IEUopenGWAS database, Mendelian randomization analysis was used to assess the causal relationship between the RA signaling pathway and LSCC. The constructed gene-drug and ceRNA networks, along with immune cell infiltration analysis, revealed 188 co-expressed differential genes, mainly enriched in the RA signaling pathway. Mendelian randomization analysis showed that increased activity of the RA signaling pathway is associated with a reduced risk of LSCC. This study provides new insights into the pathogenesis and potential research directions for the treatment of LSCC.

, correspAuthors=Dong-xin TANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Jia-xing DAI, Dong-xin TANG, Yuan-yin LI, Shao-wang ZHANG, Bing YANG), CN=ArticleExt(id=1149776928388898985, articleId=1149776903122412261, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=基于生物信息学联合孟德尔随机化分析探讨类风湿关节炎相关通路在肺鳞癌中的作用与机制, columnId=1156262732526637414, journalTitle=科学技术与工程, columnName=论文·医药、卫生, runingTitle=null, highlight=null, articleAbstract=

为了探究类风湿关节炎(rheumatoid arthritis,RA)相关通路在肺鳞状细胞癌(lung squamous cell carcinoma,LSCC)中的作用,通过GEO、TCGA数据库获取RA和LSCC的基因表达数据,利用GEO2R工具和Rstudio软件筛选差异表达基因。GO/KEGG功能富集分析揭示了RA信号通路中的关键基因。结合IEUopenGWAS数据库的SNP数据,采用孟德尔随机化分析评估RA信号通路与LSCC的因果关系。构建的基因-药物和ceRNA网络,以及免疫细胞浸润分析,发现了188个共表达差异基因,主要富集于RA信号通路。孟德尔随机化分析显示,RA信号通路活跃性增强与LSCC风险降低相关。该研究为理解LSCC的发病机制和治疗提供了新思路。

, correspAuthors=唐东昕, authorNote=null, correspAuthorsNote=
* 唐东昕(1977—),男,土家族,贵州遵义人,博士,主任医师。研究方向:中医药(民族医药)防治肿瘤基础及临床。E-mail:。
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=V4fImG1J6HQLKEIx0aGspg==, magXml=kyDj9Be5/M44+2fum/I0kw==, pdfUrl=null, pdf=WF3PUH8tSRwgaZvrL4phPg==, pdfFileSize=16215478, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=40SQmeJEXgbA6oCHUV+qKw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=iCN/4R3NYmAz1ZOWzE0j0w==, mapNumber=null, authorCompany=null, fund=null, authors=

代家兴(1997—),男,汉族,重庆人,硕士研究生。研究方向:中医药防治恶性肿瘤。E-mail:。

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代家兴(1997—),男,汉族,重庆人,硕士研究生。研究方向:中医药防治恶性肿瘤。E-mail:。

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代家兴(1997—),男,汉族,重庆人,硕士研究生。研究方向:中医药防治恶性肿瘤。E-mail:。

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*表示P<0.001,**表示P<0.01,***表示P<0.05

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基于生物信息学联合孟德尔随机化分析探讨类风湿关节炎相关通路在肺鳞癌中的作用与机制
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代家兴 1, 2 , 唐东昕 1, 2, 3, * , 李沅音 1, 2 , 张少望 1, 2 , 杨兵 1, 2, 3
科学技术与工程 | 论文·医药、卫生 2025,25(11): 4467-4475
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科学技术与工程 | 论文·医药、卫生 2025, 25(11): 4467-4475
基于生物信息学联合孟德尔随机化分析探讨类风湿关节炎相关通路在肺鳞癌中的作用与机制
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代家兴1, 2 , 唐东昕1, 2, 3, * , 李沅音1, 2, 张少望1, 2, 杨兵1, 2, 3
作者信息
  • 1 贵州中医药大学第一临床医学院, 贵阳 550005
  • 2 贵州省中医肿瘤传承与科技创新人才基地,贵阳 550005
  • 3 贵州中医药大学第一附属医院, 贵阳 550001

    • 代家兴(1997—),男,汉族,重庆人,硕士研究生。研究方向:中医药防治恶性肿瘤。E-mail:。

通讯作者:

* 唐东昕(1977—),男,土家族,贵州遵义人,博士,主任医师。研究方向:中医药(民族医药)防治肿瘤基础及临床。E-mail:。
Investigate the Role and Mechanism of Rheumatoid Arthritis-related Pathways in Lung Squamous Cell Carcinoma Based on Bioinformatics Combined with Mendelian Randomization Analysis
Jia-xing DAI1, 2 , Dong-xin TANG1, 2, 3, * , Yuan-yin LI1, 2, Shao-wang ZHANG1, 2, Bing YANG1, 2, 3
Affiliations
  • 1 The First Clinical Medical School, Guizhou University of Chinese Medicine, Guiyang 550005, China
  • 2 Guizhou Provincial Traditional Chinese Medicine Tumor Inheritance and Technological Innovation Talent Base, Guiyang 550005, China
  • 3 The First Affiliated Hospital, Guizhou University of Traditional Chinese Medicine, Guiyang 550001, China
出版时间: 2025-04-18 doi: 10.12404/j.issn.1671-1815.2402571
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摘要
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为了探究类风湿关节炎(rheumatoid arthritis,RA)相关通路在肺鳞状细胞癌(lung squamous cell carcinoma,LSCC)中的作用,通过GEO、TCGA数据库获取RA和LSCC的基因表达数据,利用GEO2R工具和Rstudio软件筛选差异表达基因。GO/KEGG功能富集分析揭示了RA信号通路中的关键基因。结合IEUopenGWAS数据库的SNP数据,采用孟德尔随机化分析评估RA信号通路与LSCC的因果关系。构建的基因-药物和ceRNA网络,以及免疫细胞浸润分析,发现了188个共表达差异基因,主要富集于RA信号通路。孟德尔随机化分析显示,RA信号通路活跃性增强与LSCC风险降低相关。该研究为理解LSCC的发病机制和治疗提供了新思路。

生物信息学  /  孟德尔随机化  /  类风湿关节炎  /  肺鳞癌  /  通路基因

In order to investigate the role of rheumatoid arthritis (RA)-related pathways in lung squamous cell carcinoma (LSCC). By obtaining gene expression data for RA and LSCC from the GEO and TCGA database, differentially expressed genes were screened using GEO2R tool and Rstudio software. GO/KEGG functional enrichment analysis identified key genes in the RA signaling pathway. Combining SNP data from the IEUopenGWAS database, Mendelian randomization analysis was used to assess the causal relationship between the RA signaling pathway and LSCC. The constructed gene-drug and ceRNA networks, along with immune cell infiltration analysis, revealed 188 co-expressed differential genes, mainly enriched in the RA signaling pathway. Mendelian randomization analysis showed that increased activity of the RA signaling pathway is associated with a reduced risk of LSCC. This study provides new insights into the pathogenesis and potential research directions for the treatment of LSCC.

bioinformatics  /  Mendelian randomization  /  rheumatoid arthritis  /  lung squamous cell carcinoma  /  pathway genes
代家兴, 唐东昕, 李沅音, 张少望, 杨兵. 基于生物信息学联合孟德尔随机化分析探讨类风湿关节炎相关通路在肺鳞癌中的作用与机制. 科学技术与工程, 2025 , 25 (11) : 4467 -4475 . DOI: 10.12404/j.issn.1671-1815.2402571
Jia-xing DAI, Dong-xin TANG, Yuan-yin LI, Shao-wang ZHANG, Bing YANG. Investigate the Role and Mechanism of Rheumatoid Arthritis-related Pathways in Lung Squamous Cell Carcinoma Based on Bioinformatics Combined with Mendelian Randomization Analysis[J]. Science Technology and Engineering, 2025 , 25 (11) : 4467 -4475 . DOI: 10.12404/j.issn.1671-1815.2402571
正文
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类风湿关节炎(rheumatoid arthritis, RA)是一种慢性、进展性的自身免疫性疾病,其特征为关节炎症,导致肿胀、疼痛、僵硬和功能障碍,严重降低患者的生活质量[1]。肺鳞状细胞癌(lung squamous cell carcinoma,LSCC)是非小细胞肺癌(non-small cell lung cancer, NSCLC)的重要组织学亚型,约占全球肺癌发病总数的25%,起源于肺部上皮细胞,其命名基于细胞的鳞状形态特征[2]。生物信息学在近年来的研究中,得益于高通量检测和分析技术的快速进步,越来越多地被应用于探索肿瘤的潜在机制[3]。近期研究揭示了RA与某些类型癌症风险之间的潜在联系,提示RA患者中癌症的发病率可能略有上升[4]。孟德尔随机化(Mendelian randomization, MR)是一种基于遗传流行病学原理的因果推断方法,其核心机制通过工具变量(instrumental variables, IVs)实现[5]。为了探讨RA相关的信号通路在肺鳞癌中的作用及其潜在机制,揭示肺鳞癌的新致病机制,采用整合多组织学分析策略与孟德尔随机化(MR)的方式,系统筛选TCGA和GEO数据库中RA-LSCC共表达差异基因,揭示关键通路与靶向治疗候选分子。通过分析这些基因所富集的信号通路,并运用MR评估这些通路与肺鳞癌的因果关联,从而深入理解RA相关通路在肺鳞癌中的角色和机制。
1 材料与方法
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1.1 数据获取
检索基因表达综合数据库(https://www.ncbi.nlm.nih.gov/geo/)获取类风湿关节炎数据(GSE1919),该数据集包括了5例类风湿关节炎样本与5例正常样本;再利用Rstudio软件的“TCGAbiolinnks”包下载了癌症基因组图谱(https://portal.gdc.cancer.gov/)肺鳞癌的547例样本的基因表达谱数据以及临床信息,其中包括了496例肺鳞癌组织基因表达数据与51例癌旁组织基因表达数据。
1.2 差异表达基因筛选
利用基因表达综合数据库官方网站分析工具“GEO2R”,设置阈值P<0.05,log2FC(log2FoldChange)>1为筛选条件,将正常组与类风湿关节炎组进行对比以筛选差异基因。肺鳞癌基因表达谱数据下载完成以后,通过Rstudio软件中“DEseq2”和“limma”包对基因表达谱数据进行了标准化与归一化处理,并以同样的P<0.05,log2FC>1为筛选条件进行差异基因的筛选,利用ggplot2包绘制了类风湿关节炎和肺鳞癌差异基因的火山图,如图1、图2所示。最后,利用在线韦恩图制作网站对类风湿关节炎与肺鳞癌差异基因进行取交集获得共表达差异基因。
1.3 功能富集分析
利用基因本体论分析(gene ontology, GO)对共表达差异基因进行注释,是生物信息学分析中常用的方法。通过基因本体论富集分析的系统性注释,本研究可实现生物学过程、细胞成分和分子功能三个维度的多层次解析。另外,基因百科全书数据库(kyoto encyclopedia of gene and genomes, KEGG)用于进行通路富集分析,以发现共表达差异基因所富集的重要信号通路。这些分析通过使用Rstudio软件中的“ClusterProfiler”“enrichplot”“org.Hs.eg.db”包来完成。在进行GO/KEGG功能富集分析时,P和调整后P=0.05作为阈值。最后,利用Rstudio软件中的“ggplot2”“circlize”“RColorBrewer”“dplyr”和“ComplexHeatmap”等软件包绘制了相应的功能富集结果,如图3所示。
1.4 孟德尔随机化分析
以类风湿关节炎信号通路为暴露数据,肺鳞癌为结局数据,采用两样本孟德尔随机化分析的设计方法,探讨两者因果联系。类风湿关节炎信号通路的遗传数据来自于IEUopenGWAS(https://gwas.mrcieu.ac.uk/)数据库中的独立欧洲人群的汇总数据。该数据集包含80 799个样本,其中19 234个样本为类风湿关节炎患者,61 565个样本为对照组。在该数据集中共包含9 739 304个单核苷酸多态性(single nucleotide polymorphism,SNPs)。肺鳞癌相关数据也来自于IEUopenGWAS数据库中独立欧洲人群的汇总数据。该数据集包含62 467个样本,其中包括7 704例肺鳞癌患者和54 763例对照组数据。在该数据集中共包含10 341 529个SNPs。类风湿关节炎信号通路的SNP筛选条件是设置P阈值为5×10-8进行筛选,共筛选出49个SNPs作为工具变量(instrumental variables,IVs), 在排除连锁不平衡和删除等位基因后,共纳入49个SNPs进行后续分析。利用Rstudio软件中的“TwoSampleMR”包进行MR分析包括Egger检验、加权中位数、逆方差加权、简单模型与加权模型此5种分析方法,以此判断类风湿关节炎信号通路与肺鳞癌之间的因果关系,如图4所示。
1.5 基因-药物网络
药物基因相互作用数据库(drug gene interaction database, DGIdb)是一个用于药物基因相互作用信息的数据库,它提供了关于药物与基因之间相互作用的详细信息。根据KEGG通路富集结果,选择类风湿关节炎信号通路中的11个通路基因输入DGIdb数据库(https://dgidb.genome.wustl.edu/)后下载基因对应的抗肿瘤药物文件,使用Perl软件得到基因-药物调控网络文件后,最终利用Cytoscape3.10.1软件绘制出基因-药物调控网络图,具体如图5所示。
1.6 ceRNA网络构建
通过运用miRanda数据库,miRDB数据库,miRWalk数据库,TargetScan数据库得到miRNA相关数据,并通过Perl软件预测11个通路基因结合的miRNA,通过spongeScan数据库得到lncRNA数据,通过Perl软件构建miRNA结合lncRNA,最终通过Cytoscape3.10.1软件构建ceRNA调控网络图,具体如图6所示。
1.7 免疫浸润分析
通过Rstudio软件中的“CIBERSORT”包,选择得出的11个类风湿关节炎信号通路基因,进行免疫浸润分析,分析这11个基因表达在各个免疫细胞中的占比,具体如图7所示。
1.8 验证分析
根据筛选出11个类风湿关节炎信号通路基因在TCGA数据库肺鳞癌中的基因表达值,并将TCGA中肺鳞癌数据分为肺鳞癌组和正常组进行T检验,利用Rstudio 软件绘制出箱线图,具体如图8所示。
2 结果
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2.1 差异基因分析结果
通过GEO数据库中的工具GEO2R对类风湿关节炎芯片数据(GSE1919)进行筛选,以P<0.05,log2FC>1为筛选标准,进行差异基因的筛选,一共获得类风湿关节炎的389个差异基因。以同样筛选标准,对TCGA数据库中肺鳞癌表达数据谱进行筛选得到了7 200个差异基因。随后,通过取共表达基因获取了类风湿关节炎和肺鳞共表达基因188个。
2.2 功能富集分析结果
对188个类风湿关节炎和肺鳞癌共表达差异基因,利用Rstudio软件进行了功能富集分析。GO功能富集结果显示,共表达差异基因在生物过程上主要富集于细胞黏附的正向调节、细胞活化的正向调节、对皮质类固醇的反应等;在细胞成分上主要富集于质膜外侧、含胶原蛋白的细胞外基质、褶皱膜等;在分子功能上主要富集于趋化因子活性、趋化因子受体结合、细胞因子受体活性等。在KEGG功能富集结果中,发现差异基因主要参与类风湿关节炎信号通路等,该通路主要包括了11个共表达基因MMP1、MMP3、TNFSF11、IL23A、HLA-DMA、HLA-DOA、ITGAL、ITGB2、HLA-DMB、CXCL6、CD86。
2.3 孟德尔随机化分析结果
在EUopenGWAS数据库中,与肺鳞癌相关的工具变量共计59个。经过排除连续不平衡和删除不相容等位基因后,最终选取了49个与肺鳞癌相关的工具变量进行分析。研究使用了Rstudio软件中的“TwoSampleMR”包进行了5种MR分析方法。结果显示:Egger检验(P=0.790 8)、加权中位数(P=0.112 3)、逆方差加权(P=0.036 3)、简单模型(P=0.759 9)和加权模型(P=0.489 3)。根据逆方差加权法的P<0.05,得出阳性结果,并认为类风湿关节炎通路与肺鳞癌存在因果关系。MR分析显示显著异质性(IVW P=0.025 8;MR-Egger P=0.019 5)。水平多效性检验使用Egger截断法,P=0.129 9,说明工具变量影响结局的途径除了暴露外并不显著。留一法敏感性分析结果表明稳定。
2.4 基因-药物网络分析结果
将获取的11个类风湿关节炎通路基因输入 https://dgidb.genome.wustl.edu/得到药物文件,通过Perl软件得到基因-药物调控网络文件。分别获取了基因MMP1、MMP3、TNFSF11、IL23A、ITGB2、IL23A、ITGB2、CD86对应的靶向药物。
2.5 ceRNA网络构建
利用miRanda数据库,miRDB数据库,miRWalk数据库,TargetScan数据库得到miRNA相关数据,通过Perl预测通路基因结合的miRNA,通过spongeScan数据库得到lncRNA数据,通过perl构建miRNA结合lncRNA,构建ceRNA网络。其中与11个类风湿关节炎通路结合的mRNA有58个,与mRNA结合的lncRNA一共有124个。最终利用Cytoscape软件绘制出ceRNA调控网络。
2.6 免疫浸润分析
为了进一步证实11个基因表达与免疫微环境的相关性,使用 CIBERSORT 算法分析了肿瘤浸润免疫亚群的比例,并构建了 22种LSCC样本的免疫细胞图谱(图7),免疫细胞如中性粒细胞、静息肥大细胞、激活肥大细胞等,图7中显示通路基因CXCL6与免疫细胞Mast cells resting存在正相关,且由线条宽度可以看出二者相关性最大。
2.7 验证分析
根据 TCGA 数据集将肺鳞癌临床样本数据分为两组:正常组和肺鳞癌组。通过观察这11个基因在两组中的表达情况,发现这11个基因在正常组和肺鳞癌中的表达均有显著差异。
3 讨论
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肺癌是全球癌症相关死亡的主要原因。早期发现肺癌对于提高治疗成功率和患者生存率至关重要。然而,目前缺乏有效的早期生物标志物,导致许多肺鳞癌患者在确诊时已处于中晚期[6-7]。2020年,全球新发肺癌病例约220.7万,死亡病例约179.6万,分别占所有恶性肿瘤新发和死亡病例的11.4%和18.0%[8]。肺鳞癌约占所有非小细胞肺癌的30%,其发病与吸烟密切相关,且诊断具有挑战性。本研究旨在探讨类风湿关节炎相关信号通路在肺鳞癌中的潜在作用,研究发现,RA与肺鳞癌共有的差异基因主要富集在RA相关的信号通路中。通过孟德尔随机化分析,发现RA信号通路与肺鳞癌之间存在显著的因果关系。本研究重点探析RA信号通路中的11个基因,包括MMP1、TNFSF11、IL23A、HLA-DMA、ITGB2和CXCL6等。基质金属蛋白酶(MMPs)家族成员MMP1和MMP3在肺鳞癌的发展中扮演着关键角色。MMP1能够降解细胞外基质(ECM),促进肿瘤细胞的侵袭和转移。MMP3也参与了肿瘤的侵袭和转移过程,并与肿瘤预后密切相关[9]。此外,MEK1/2抑制剂Selumetinib能够抑制含有TRA2B-DNAH5融合基因的肺鳞癌的恶性进展[10]。MMP1在多种癌症中的异常高表达与不良预后密切相关[11-12]。研究表明,ETV4可以激活MMP基因的表达,而MMPs是癌症进展的关键介质[13-15]。MMP1是ETV4的关键下游靶点,敲除MMP1显著抑制了ETV4诱导的细胞增殖和迁移,表明MMP1在ETV4致瘤活性中的重要性[14]。TNFSF11(RANKL)是一种II型跨膜蛋白,其表达与肺癌患者的不良预后相关[16-17]。RANKL/RANK通路的激活通过依赖于线粒体呼吸的机制调节肺癌干细胞样细胞的扩张[18]。TNFSF11通过与RANK结合激活NF-κB信号通路,促进肿瘤进展,并参与肿瘤相关炎症反应和骨破坏过程。这些过程在肺鳞癌的发展中起着重要作用[19]。HLA-DMA在抗原呈递过程中起关键作用,能够帮助调整和优化抗原肽与MHC II类分子的结合,影响T细胞对抗原的识别和免疫反应的激活[20]。HLA-DMA在癌症RNAseq表达谱中的富集涉及抗原加工和呈递途径的激活[21]。作为一种肽处理器,HLA-DMA催化经典MHCII蛋白上的肽转化,并保护空的MHCII类分子在有效呈现蛋白抗原时免受功能失活,参与了癌症进展和耐药性[22-23]。IL-23通过与肿瘤相关巨噬细胞(TAMs)和调节性T细胞(Treg cells)的相互作用,促进肿瘤的发生和发展。IL-23通过稳定效应Treg细胞的程序,增强免疫抑制,从而降低抗肿瘤免疫反应[24]。研究发现,IL-23在NSCLC中的表达可受到化疗药物和表观遗传学治疗的动态调控,可诱导NSCLC细胞系增殖[25]。ITGB2(CD18)是整合素的亚基之一,具有促进白细胞黏附和外渗的功能[26]。ITGB2的表达与肺鳞癌的临床特征相关,其表达降低与患者较短的总生存时间相关联[27]。ITGB2可以通过调节癌相关成纤维细胞间接促进口腔鳞状细胞癌的增殖[28],并介导yap诱导的乳腺癌细胞跨内皮侵袭[29]。过表达ITGB2可以提高其表达水平在H1792细胞中,ITGB2可以降低N-cadherin、Vimentin、Slug、Snail和Twist的表达水平,说明ITGB2可以通过抑制EMT途径影响非小细胞肺癌细胞的生长[30]。类风湿关节炎与多种炎症介质有关,这些介质的水平变化与疾病的严重程度密切相关。RA的发病机制涉及多种信号转导通路,包括JAK/STAT、NF-κB、MAPK等[31]。RA患者的免疫细胞浸润模式与健康人群不同,特别是单核细胞和T细胞的浸润水平增加,这可能与RA的炎症过程有关[32]。一些观察性研究表明RA可能与肺癌风险有关,但这种关联并不一致。在涉及183 888名患者的11项队列研究的荟萃分析中,观察到RA患者发生肺癌的风险增加[33]。
4 结论
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当前,类风湿关节炎与肺鳞癌之间的关系研究面临诸多挑战,包括复杂性、多样性和因果关系的确立等。这些难点使得在探索两者之间的潜在联系时,需要采用更为精细和多层次的方法。通过整合基因表达分析、功能富集分析和孟德尔随机化等多种生物信息学工具,从不同角度深入探讨了这一关系。具体来说,分析了类风湿关节炎相关的信号通路,发现其活性变化可能与肺鳞癌的发病风险密切相关。通过对基因表达数据的综合分析,验证了这些通路在肺鳞癌中的重要作用,尤其是在调节肿瘤微环境和细胞增殖方面。研究结果表明,类风湿关节炎的信号通路活性增加可能有助于降低肺鳞癌的发病风险。这一发现不仅为理解肺鳞癌的发生机制提供了新的视角,也为临床提供了潜在的治疗策略。具体而言,调节或抑制类风湿关节炎相关通路,可能为肺鳞癌的防治提供新的方向。研究结果类风湿关节炎与肺鳞癌之间的关系提供了新的理论基础,揭示了疾病间的复杂交互作用,也为个性化医学的发展奠定了基础。未来的研究可进一步探讨这些通路的具体机制,以期为临床应用提供更多实证支持。
基金
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  • 贵州省高等学校中医药民族医药防治肿瘤医学转化工程研究中心项目(黔教技[2023]037号)
  • 贵州省中医肿瘤传承与科技创新人才基地项目(黔人领发[2018]3号)
  • 贵州省中医肿瘤传承与科技创新人才团队项目(黔科合人才[2020]5013)
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2025年第25卷第11期
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doi: 10.12404/j.issn.1671-1815.2402571
  • 接收时间：2024-04-09
  • 首发时间：2025-07-09
  • 出版时间：2025-04-18
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  • 收稿日期：2024-04-09
  • 修回日期：2024-10-28
基金
贵州省高等学校中医药民族医药防治肿瘤医学转化工程研究中心项目(黔教技[2023]037号)
贵州省中医肿瘤传承与科技创新人才基地项目(黔人领发[2018]3号)
贵州省中医肿瘤传承与科技创新人才团队项目(黔科合人才[2020]5013)
作者信息
    1 贵州中医药大学第一临床医学院, 贵阳 550005
    2 贵州省中医肿瘤传承与科技创新人才基地,贵阳 550005
    3 贵州中医药大学第一附属医院, 贵阳 550001

通讯作者:

* 唐东昕(1977—),男,土家族,贵州遵义人,博士,主任医师。研究方向:中医药(民族医药)防治肿瘤基础及临床。E-mail:。
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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