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Background and Objectives: This study aims to identify novel genetic targets in thyroid cancer (TC) by conducting a comprehensive analysis of microarray datasets and investigating the genetic factors that drive TC development. By uncovering these factors, we provide valuable insights for future research and treatment.   Methods: We performed a meta-analysis of three TC datasets from the GEO database, including data from 100 healthy controls and 220 TC samples. These datasets were processed using R, fol-lowed by batch correction and differential expression analysis. We then conducted DEG, eQTL, MR, GSEA, GO, and KEGG analyses to identify gene-disease associations.   Results: Validation of the target genes confirmed their significant roles in TC pathogenesis and pro-gression. Specifically, gene expression analysis revealed 42 upregulated genes and 42 downregulated genes in TC samples. To explore the role of these genes further, we applied Mendelian randomization (MR) analysis, which identified four co-expressed genes—LAMP5, MTSS1, CEACAM1, and PRDX6—that were strongly associated with TC. These genes are involved in various biological processes, including macrophage activation and neural system modulation. Additionally, cell type-specific analysis revealed a unique immune cell landscape in TC, emphasizing the critical role of immune responses in disease progression. Notably, the MR findings were validated by variance analysis in the validation cohort, further strengthening the reliability of our results.   Conclusion: This evidence not only validates our methodological approach but also reveals new mecha-nisms underlying TC pathogenesis, paving the way for targeted therapeutic interventions. Our findings offer significant insights into the molecular mechanisms of TC and highlight the potential for targeted therapies.