Multiple Data Sets to Explore the Key Molecules and Mechanism of Lymph Node Metastasis in Gastric Cancer.

Yijun Zheng, Yawu Zhang,Zheyuan Wang,Xiaohu Guo,Lingyi Zhang,Youcheng Zhang

Discover Oncology（2025）

Lanzhou University Second Clinical Medical School

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Abstract

To explore the key molecules and regulatory mechanisms of lymph node metastasis in gastric cancer. The differential genes and key genes of lymph node metastasis in gastric cancer were analyzed by utilizing multiple data sets. The key genes were analyzed by GSEA analysis, transcription factor analysis, nomogram prediction model construction, immune infiltration analysis, GSVA analysis, drug sensitive analysis and single cell data analysis. Abnormal expression of key genes including CDRT15P1, DENND3, F2R, FNDC3B, IRAK3, MS4A2, PDK4, PKIA and activation of related signaling pathways might be the result of ultraviolet radiation-induced DNA damage, which was closely related to lymph node metastasis in gastric cancer. The key genes were regulated by a variety of transcription factors, which were strongly connected with the invasion of immune cells and the sensitivity of a variety of drugs. The nomogram prediction model, which is based on the key genes associated with lymph node metastasis and the TNM of gastric cancer, demonstrated a high level of predictive efficiency. CDRT15P1, DENND3, F2R, FNDC3B, IRAK3, MS4A2, PDK4 and PKIA may be the key genes affecting lymph node metastasis in gastric cancer, and F2R has higher biological importance.

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Key words

Lymph node metastasis in gastric cancer,Bioinformatics analysis,Nomogram prediction model,Mendelian randomization

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【要点】：本文通过多数据集分析探索了胃癌淋巴结转移的关键分子及其调控机制，发现CDRT15P1、DENND3等基因可能与淋巴结转移密切相关。

【方法】：采用差异基因分析、GSEA分析、转录因子分析、诺模图预测模型构建、免疫浸润分析、GSVA分析、药物敏感性分析以及单细胞数据分析等方法。

【实验】：使用多个数据集进行实验，包括基因表达数据集，并构建了基于关键基因与胃癌TNM分期的诺模图预测模型，该模型展现出高预测效率。