Prognostic biomarkers for lung adenocarcinoma based on Mendelian randomization analysis.

BackgroundLung adenocarcinoma is a multifaceted disease with diverse locations and timings of gene mutations, histology, and molecular pathogenesis. Thus, identifying therapeutic target genes for lung adenocarcinoma has become a major challenge.MethodWe downloaded the gene expression profiles of 220 patients with lung adenocarcinoma from the Gene Expression Omnibus database and identified the differentially expressed genes between noncancer tissue and cancer tissue groups. Mendelian randomization analysis was performed using the exposure gene expression quantitative trait locus dataset and outcome dataset (ieu-a-965) to obtain genome-wide association studies summary data. Sensitivity analysis was used to assess the presence of pleiotropy and heterogeneity in the instrumental variables. Additionally, we performed Mendelian randomization analysis to explore the potential intersecting genes between differentially expressed and specific genes. Moreover, gene set enrichment and overall survival analyses were performed on the intersection gene.ResultsWe combined Gene Expression Omnibus and genome-wide association studies data to identify one upregulated and two downregulated genes associated with lung adenocarcinoma risk using inverse variance weight analysis as the primary analytical method. We observed that survival was significantly higher in the groups with high expressions of