Department of Otorhinolaryngology Head and Neck Surgery, the Second Affiliated Hospital of Xi'an Jiaotong University.
Department of Surgical Oncology, the First Affiliated Hospital of Xi'an Jiaotong University.
Medicine (Baltimore). 2021 Mar 26;100(12):e25154. doi: 10.1097/MD.0000000000025154.
During last decade, bioinformatics analysis has provided an effective way to study the relationship between various genes and biological processes. In this study, we aimed to identify potential core candidate genes and underlying mechanisms of progression of lung and gastric carcinomas which both originated from endoderm. The expression profiles, GSE54129 (gastric carcinoma) and GSE27262 (lung carcinoma), were collected from GEO database. One hundred eleven patients with gastric carcinoma and 21 health people were included in this research. Meanwhile, there were 25 lung carcinoma patients. Then, 75 differentially expressed genes were selected via GEO2R online tool and Venn software, including 31 up-regulated genes and 44 down-regulated genes. Next, we used Database for Annotation, Visualization, and Integrated Discovery and Metascpe software to analyze Kyoto Encyclopedia of Gene and Genome pathway and gene ontology. Furthermore, Cytoscape software and MCODE App were performed to construct complex of these differentially expressed genes . Twenty core genes were identified, which mainly enriched in extracellular matrix-receptor interaction, focal adhesion, and PI3K-Akt pathway (P < .01). Finally, the significant difference of gene expression between cancer tissues and normal tissues in both lung and gastric carcinomas was examined by Gene Expression Profiling Interactive Analysis database. Twelve candidate genes with positive statistical significance (P < .01), COMP CTHRC1 COL1A1 SPP1 COL11A1 COL10A1 CXCL13 CLDN3 CLDN1 matrix metalloproteinases 7 ADAM12 PLAU, were picked out to further analysis. The Kaplan-Meier plotter website was applied to examine relationship among these genes and clinical outcomes. We found 4 genes (ADAM12, SPP1, COL1A1, COL11A1) were significantly associated with poor prognosis in both lung and gastric carcinoma patients (P < .05). In conclusion, these candidate genes may be potential therapeutic targets for cancer treatment.
在过去的十年中，生物信息学分析为研究各种基因与生物过程之间的关系提供了一种有效的方法。在这项研究中，我们旨在鉴定肺腺癌和胃腺癌这两种源自内胚层的肿瘤进展的潜在核心候选基因和潜在机制。我们从 GEO 数据库中收集了表达谱数据集 GSE54129（胃腺癌）和 GSE27262（肺腺癌）。该研究共纳入 111 例胃腺癌患者和 21 名健康人，同时纳入 25 例肺腺癌患者。然后，通过 GEO2R 在线工具和 Venn 软件筛选出 75 个差异表达基因，包括 31 个上调基因和 44 个下调基因。接下来，我们使用数据库注释、可视化和综合发现（DAVID）和 Metascpe 软件对京都基因与基因组百科全书（KEGG）通路和基因本体（GO）进行分析。此外，我们使用 Cytoscape 软件和 MCODE App 构建这些差异表达基因的复杂网络。鉴定出 20 个核心基因，这些基因主要富集于细胞外基质-受体相互作用、焦点黏附及 PI3K-Akt 通路（P<0.01）。最后，我们通过基因表达谱交互分析数据库（GEPIA）检验了肺腺癌和胃腺癌组织与正常组织中基因表达的差异。从数据库中筛选出 12 个候选基因，这些基因的表达在肺腺癌和胃腺癌组织中均具有统计学意义（P<0.01），包括 COMP、CTHRC1、COL1A1、SPP1、COL11A1、COL10A1、CXCL13、CLDN3、CLDN1、基质金属蛋白酶 7、ADAM12 和 PLAU。进一步应用 Kaplan-Meier plotter 网站分析这些基因与临床结局的关系。结果发现，在肺腺癌和胃腺癌患者中，有 4 个基因（ADAM12、SPP1、COL1A1、COL11A1）与预后不良显著相关（P<0.05）。总之，这些候选基因可能是癌症治疗的潜在治疗靶点。
