| Libo Feng,Liu Yu,Xiaolong Chen. Bioinformatics analysis of potential hub genes associated with biological characteristics and survival in patients with gastric cancer. Oncol Transl Med, 2022, 8: 232-238. |
| 应用生物信息学筛选与胃癌生物学行为和生存相关的潜在枢纽基因 |
| Bioinformatics analysis of potential hub genes associated with biological characteristics and survival in patients with gastric cancer |
| Received:November 16, 2021 Revised:October 19, 2022 |
| DOI：10.1007/s10330-021-0535-5 |
| 中文关键词: 胃癌; 差异表达基因; 富集分析; 生物信息学 |
| 英文关键词: gastric cancer; differentially expressed genes; enrichment analysis; bioinformatics |
| 基金项目:西南医科大学-三附院联合项目 |
| Author Name | Affiliation | Postcode | | Libo Feng | Department of Gastrointestinal Surgery, The Affiliated Hospital of Southwest Medical University | 646000 | | Liu Yu | Department of Gastrointestinal Surgery, The Affiliated Hospital of Southwest Medical University | | | Xiaolong Chen* | Department of Gastrointestinal Surgery, The Affiliated Hospital of Southwest Medical University | 646000 |
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| 中文摘要: |
| 目的：胃癌已成为严重威胁人类健康的疾病。本研究的目的是探讨差异表达基因（DEGs）和确定潜在的与胃癌生物学行为、生存相关的基因。方法：将 GSE79973基因表达谱从 GEO 数据库中下载，提交到 GCBI 在线分析平台上筛选 DEGs。通过基因本体分析、路径分析和网络构建（包括基因信号网络和基因共表达网络）筛选出核心 DEGs。生存分析用于揭示基因与生存时间的关系。结果：983个基因被筛选为 DEGs (p < 0.001; FC > 2) 。GO 分析表明，DEGs 主要参与血管生成、细胞代谢、细胞粘附、氧化还原过程和细胞迁移等过程。细胞色素 p450代谢、 ECM受体相互作用、药物代谢-细胞色素 P450、代谢途径和 PI3K-Akt 信号途径在通路分析中显著丰富。UGT2B15、 HGF、 NID2、 FSTL1、 INHBA 等基因在网络中与其他基因密切相关。生存分析表明 HGF、 NID2、 fstl1和 INHBA 的表达水平与胃癌患者的生存时间呈负相关。结论: HGF、 NID2、 fstl1和 INHBA 可能是胃癌生物学行为和生存的关键基因。 |
| 英文摘要: |
| Objective Gastric cancer (GC) is a serious threat to human health. In this study, we aimed to explore the
differentially expressed genes (DEGs) and identify potential targets for the treatment of GC.
Methods The gene expression profile of GSE79973 which compared tissue samples from gastric cancer
patients and healthy individuals, downloaded from the GEO database, was submitted to the GCBI online
analysis platform to screen for DEGs. Gene ontology (GO) analysis, pathway analysis, and construction
of networks, including gene signal and gene co-expression networks, were performed to identify the core
DEGs. Survival analysis was performed to determine the relationship between these genes and patient
survival time.
Results Nine hundred eighty-three genes were identified as DEGs (P < 0.001; FC > 2). GO analysis
showed that DEGs were primarily involved in processes such as angiogenesis, cell metabolism, cell
adhesion, redox processes, and cell migration. The metabolism of xenobiotics by cytochrome P450, ECM-
receptor interaction, drug metabolism by cytochrome P450, metabolic pathways, and the PI3K-Akt signaling
pathway were significantly enriched in pathway analysis. Genes such as UGT2B15, Hepatocyte growth
factor (HGF), Nidogen-2 (NID2), Follistatin-like protein 1 (FSTL1), and Inhibin beta A chain (INHBA) were
closely linked to other genes in the network. Survival analyses indicated that HGF, NID2, FSTL1, and INHBA
expression levels were inversely correlated with survival time in patients with gastric cancer.
Conclusion HGF, NID2, FSTL1, and INHBA may be potential key genes associated with the biological
characteristics and survival in patients with gastric cancer. |
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