Li Yuanting, Chen Minghao, Chen Qing, Yuan Min, Zeng Xi, Zeng Yan, He Meibo, Wang Baiqiang, Han Bin
GCP Center/Institute of Drug Clinical Trials, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People's Republic of China.
Institute of Pharmacy, North Sichuan Medical College, Nanchong, 637000, People's Republic of China.
Adv Ther. 2023 Apr;40(4):1456-1473. doi: 10.1007/s12325-023-02428-x. Epub 2023 Jan 24.
The global prevalence of gastric cancer (GC) is increasing, and novel chemotherapeutic targets are needed.
We searched for potential biomarkers for GC in three microarray data sets within the Gene Expression Omnibus (GEO) database. FunRich (v3.1.3) was used to perform Gene Ontology (GO) analyses and STRUN and Cytoscape (v3.6.0) were employed to construct a protein-protein interaction (PPI) network. To explore hub gene expression and survival, we used Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier (KM) plotter. Drugs that were closely related to key genes were screened by the Gene Set Cancer Analysis (GSCA), and relevant correlations were verified experimentally. We validated that the sensitivity of a GC cell line to these drugs was correlated with fibrillin 1 (FBN1) mRNA expression levels.
We identified 83 upregulated and 133 downregulated differentially expressed genes (DEGs) and these were enriched with regards to their cellular component (extracellular and exosomes), molecular function (extracellular matrix structural constituent and catalytic activity), and biological process (cell growth and/or maintenance and metabolism). The biological pathways most prominently involved were epithelial-to-mesenchymal transition (EMT) and β3 integrin cell surface interactions. For the PPI network, we selected 10 hub genes, and 70% of these were significantly connected to poor overall survival (OS) in patients with GC. We found a significant link between the expression of FBN1 and two small molecule drugs (PAC-1 and PHA-793887).
Overall, we suggest that these hub genes can be used as biomarkers and novel targets for GC. FBN1 may be associated with drug resistance in gastric cancer.
全球胃癌（GC）患病率呈上升趋势，需要新的化疗靶点。
我们在基因表达综合数据库（GEO）中的三个微阵列数据集中搜索GC的潜在生物标志物。使用FunRich（v3.1.3）进行基因本体（GO）分析，采用STRING和Cytoscape（v3.6.0）构建蛋白质-蛋白质相互作用（PPI）网络。为了探究枢纽基因的表达和生存情况，我们使用了基因表达谱交互式分析（GEPIA）和Kaplan-Meier（KM）绘图工具。通过基因集癌症分析（GSCA）筛选与关键基因密切相关的药物，并通过实验验证相关相关性。我们验证了GC细胞系对这些药物的敏感性与原纤蛋白1（FBN1）mRNA表达水平相关。
我们鉴定出83个上调和133个下调的差异表达基因（DEG），这些基因在细胞成分（细胞外和外泌体）、分子功能（细胞外基质结构成分和催化活性）和生物学过程（细胞生长和/或维持以及代谢）方面得到富集。最显著涉及的生物学途径是上皮-间质转化（EMT）和β3整合素细胞表面相互作用。对于PPI网络，我们选择了10个枢纽基因，其中70%与GC患者的不良总生存（OS）显著相关。我们发现FBN1的表达与两种小分子药物（PAC-1和PHA-793887）之间存在显著联系。
总体而言，我们认为这些枢纽基因可作为GC的生物标志物和新靶点。FBN1可能与胃癌的耐药性有关。
