Wang Yue, Liu Hongbin
Department of Pathology, Affiliated Hospital 2 of Nantong University, Nantong, China.
Medicine (Baltimore). 2025 Aug 29;104(35):e44057. doi: 10.1097/MD.0000000000044057.
The incidence of esophageal adenocarcinoma (EA) has significantly increased in developed Western countries. Despite medical advancements, the prognosis remains poor, with a 5-year survival rate of less than 20%. By 2024, the global incidence is expected to reach 141,300 new cases annually, underscoring the urgent need to elucidate the mechanisms underlying EA pathogenesis to develop effective preventive and therapeutic strategies.
To identify differentially expressed genes (DEGs) linked to EA, microarray datasets sourced from the Gene Expression Omnibus (GEO) database were scrutinized, incorporating 4 datasets that met the defined criteria. Using expression quantitative trait loci and Mendelian randomization (MR) analyses, the contribution of genetic factors to EA development was evaluated. Functional pathways were explored using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis, which revealed enrichment in lipid metabolism. Consequently, Bayesian-weighted MR analysis was performed on 179 plasma lipid subgroups.
We identified 492 DEGs, 211 of which were downregulated and 281 were upregulated. The MR analysis identified 178 genes with significant causal effects on EA. Four co-expressed genes were ultimately determined: FZD2, KRT23, and CES1 were significantly upregulated in EA and positively associated with its occurrence, whereas ALDOC (aldolase, fructose-bisphosphate C) was inversely associated with EA risk. Elevated levels of sphingomyelins, sterol esters, diacylglycerols, and triacylglycerols were linked to a reduced risk of EA, whereas high levels of phosphatidylethanolamine correlated with a heightened risk.
Integration of DEGs, expression quantitative trait loci, and lipidomics data provides robust insights into the molecular mechanisms of EA. These findings provide a promising foundation for the development of novel targeted therapies.
在西方发达国家，食管腺癌（EA）的发病率显著上升。尽管医学取得了进步，但其预后仍然很差，5年生存率不到20%。预计到2024年，全球每年的新发病例将达到141,300例，这凸显了迫切需要阐明EA发病机制以制定有效的预防和治疗策略。
为了识别与EA相关的差异表达基因（DEG），对来自基因表达综合数据库（GEO）的微阵列数据集进行了仔细审查，纳入了4个符合既定标准的数据集。使用表达定量性状位点和孟德尔随机化（MR）分析，评估遗传因素对EA发生发展的贡献。利用基因本体论、京都基因与基因组百科全书以及基因集富集分析来探索功能途径，结果显示脂质代谢存在富集。因此，对179个血浆脂质亚组进行了贝叶斯加权MR分析。
我们鉴定出492个DEG，其中211个下调，281个上调。MR分析确定了178个对EA有显著因果效应的基因。最终确定了4个共表达基因：FZD2、KRT23和CES1在EA中显著上调且与EA的发生呈正相关，而醛缩酶C（ALDOC）与EA风险呈负相关。鞘磷脂、甾醇酯、二酰甘油和三酰甘油水平升高与EA风险降低有关，而磷脂酰乙醇胺水平升高与EA风险增加有关。
整合DEG、表达定量性状位点和脂质组学数据为深入了解EA的分子机制提供了有力的见解。这些发现为开发新型靶向治疗提供了有希望的基础。
