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Abstract：
Metastatic gastric cancer (GC) presents significant clinical challenges due to its poor prognosis and limited treatment options. To address this, we conducted a targeted protein biomarker discovery study to identify markers predictive of metastasis in advanced GC (AGC). Serum samples from 176 AGC patients (T stage 3 or higher) were analyzed using the Olink Proteomics Target panels. Patients were retrospectively categorized into nonmetastatic, metastatic, and recurrence groups, and differential protein expression was assessed. Machine learning and gene set enrichment analysis (GSEA) methods were applied to discover biomarkers and predict prognosis. Four proteins (MUC16, CAIX, 5\'-NT, and CD8A) were significantly elevated in metastatic GC patients compared to the control group. Additionally, GSEA indicated that the response to interleukin-4 and hypoxia-related pathways were enriched in metastatic patients. Random forest classification and decision-tree modeling showed that MUC16 could be a predictive marker for metastasis in GC patients. Additionally, ELISA validation confirmed elevated MUC16 levels in metastatic patients. Notably, high MUC16 levels were independently associated with metastatic progression in T3 or higher GC. These findings suggest the potential of MUC16 as a clinically relevant biomarker for identifying GC patients at high risk of metastasis.
摘要：
转移性胃癌（GC）由于其预后差和有限的治疗选择而提出了重大的临床挑战。为了解决这个问题，我们进行了一项靶向蛋白质生物标志物发现研究,以鉴定晚期GC(AGC)转移的预测标志物.使用Olink蛋白质组学靶标组分析来自176名AGC患者(T阶段3或更高)的血清样品。患者被回顾性地分类为非转移性，转移性，和复发组，并评估差异蛋白表达。应用机器学习和基因集富集分析(GSEA)方法发现生物标志物并预测预后。四种蛋白质（MUC16，CAIX，5\'-NT，与对照组相比，转移性GC患者的CD8A）显着升高。此外,GSEA表明，转移性患者对白细胞介素4和缺氧相关途径的反应丰富。随机森林分类和决策树模型显示MUC16可能是GC患者转移的预测标志物。此外,ELISA验证证实转移性患者中MUC16水平升高。值得注意的是,高MUC16水平与T3或更高GC的转移进展独立相关.这些发现表明MUC16作为临床相关的生物标志物用于鉴定具有高转移风险的GC患者的潜力。
