基于生物信息学分析揭示肺腺癌核糖体生物发生相关潜在治疗靶点

Abstract

Ribosome biogenesis (RiboSis) serves as an important foundation for the malignant progression of tumors. In this study, bioinformatics was employed to evaluate the association between RiboSis and lung adenocarcinoma (LUAD) and to preliminarily uncover potential therapeutic targets. Analysis of DepMap CRISPR/RNAi data revealed that 73% of RiboSis genes are essential for cancer cell survival. RNA-seq analysis demonstrated that RiboSis remains continuously active in multiple types of tumors and is closely related to unfavorable clinical outcomes. Through Cox and LASSO-Cox regression analyses, DDX56, XRCC5, and FAM207A were identified as risk genes associated with LUAD. We further examined their co-mutation patterns with the top 10 most frequently mutated genes in LUAD. The results revealed a significant co-occurrence phenomenon among these three genes. Enrichment analysis linked these genes to the p53 pathway, cell cycle regulation, and immune cell infiltration. The CellMiner database revealed that these three genes are associated with resistance to multiple anticancer drugs. Subsequently, LUAD cell lines with knockdown of DDX56, XRCC5, and FAM207A, respectively, were constructed. The impacts of these three risk genes on the migration and invasion abilities of tumor cells were evaluated using CCK-8, Transwell, and cell scratch assays. The results showed that the knockdown of these genes could significantly inhibit tumor migration and invasion. In summary, this study preliminarily indicates that DDX56, XRCC5, and FAM207A may be potential therapeutic targets for LUAD, providing new strategies for the clinical treatment of LUAD.