A Comprehensive Study Employing Computational Analysis and Mendelian Randomization Has Revealed the Impact of Key...

Background and Aims: In this research, we sought to enhance our comprehension of liver cancer's genetic architecture by employing Mendelian randomization (MR) techniques to establish causative relationships between particular genetic variations and liver cancer susceptibility. Methods: We integrated data from the public databases with MR analysis to identify differentially expressed genes (DEGs) associated with Hepatocellular Carcinoma (HCC). We conducted functional enrichment analyses to determine the biological processes and signaling cascades associated with the identified DEGs. We also used the CIBERSORT deconvolution method to evaluate immune cell composition in HCC tissues, followed by correlation studies examining relationships between our key genes of interest and various immune cell populations. Additionally, we validated our findings using a rat model of HCC and clinical HCC samples. Results: We obtained two key genes, EHD4 and PPARGC1A, which co-regulated M0 macrophages, suggesting their role in macrophage polarization and tumor progression. In addition, PPARGC1A is associated with resting and activated mast cells, suggesting its involvement in regulating the tumor microenvironment. Detection of rat and clinical samples further confirmed the upregulation of these genes in HCC, supporting their potential as therapeutic targets. Conclusions: Our findings emphasize the significant involvement of EHD4 and PPARGC1A in HCC, specifically regarding their influence on tumor-associated macrophage polarization and broader immune microenvironment modulation. These findings offer new insights into the molecular mechanisms driving HCC and suggest that targeting these genes may provide novel strategies for personalized treatment.