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。

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.