鉴定乳腺癌骨转移早期检测的枢纽基因。
Identification of hub genes for early detection of bone metastasis in breast cancer.
机构信息
Department of Geriatrics, Zhabei Central Hospital, Jing'an District, Shanghai, China.
出版信息
Front Endocrinol (Lausanne). 2022 Sep 29;13:1018639. doi: 10.3389/fendo.2022.1018639. eCollection 2022.
BACKGROUND
Globally, among all women, the most frequently detected and diagnosed and the most lethal type of cancer is breast cancer (BC). In particular, bone is one of the most frequent distant metastases 24in breast cancer patients and bone metastasis arises in approximately 80% of advanced patients. Thus, we need to identify and validate early detection markers that can differentiate metastasis from non-metastasis breast cancers.
METHODS
GSE55715, GSE103357, and GSE146661 gene expression profiling data were downloaded from the GEO database. There was 14 breast cancer with bone metastasis samples and 8 breast cancer tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). The volcano plots, Venn diagrams, and annular heatmap were generated by using the ggplot2 package. By using the cluster Profiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, K-M survival and ROC curves were generated to validate hub gene expression.
RESULTS
By GO enrichment analysis, 143 DEGs were enriched in the following GO terms: extracellular structure organization, extracellular matrix organization, leukocyte migration class II protein complex, collagen tridermic protein complex, extracellular matrix structural constituent, growth factor binding, and platelet-derived growth factor binding. In the KEGG pathway enrichment analysis, DEGs were enriched in Staphylococcus aureus infection, Complement and coagulation cascades, and Asthma. By PPI network analysis, we selected the top 10 genes, including SLCO2B1, STAB1, SERPING1, HLA-DOA, AIF1, GIMAP4, C1orf162, HLA-DMB, ADAP2, and HAVCR2. By using TCGA and THPA databases, we validated 2 genes, SERPING1 and GIMAP4, that were related to the early detection of bone metastasis in BC.
CONCLUSIONS
2 abnormally expressed hub genes could play a pivotal role in the breast cancer with bone metastasis by affecting bone homeostasis imbalance in the bone microenvironment.
背景
在全球范围内，所有女性中最常见的检测、诊断和致死类型的癌症是乳腺癌（BC）。特别是，骨骼是乳腺癌患者最常见的远处转移部位之一，约 80%的晚期患者会发生骨转移。因此，我们需要识别和验证可区分转移和非转移乳腺癌的早期检测标志物。
方法
从 GEO 数据库中下载 GSE55715、GSE103357 和 GSE146661 的基因表达谱数据。有 14 例乳腺癌伴骨转移样本和 8 例乳腺癌组织样本。使用 GEO2R 筛选差异表达基因（DEGs）。使用 ggplot2 包生成火山图、Venn 图和环形热图。通过 cluster Profiler R 包对 DEGs 进行 KEGG 和 GO 富集分析。通过 STRING 数据库构建 PPI 网络，使用 cytoHubba 识别关键枢纽基因。最后，通过 K-M 生存和 ROC 曲线验证枢纽基因表达。
结果
通过 GO 富集分析，143 个 DEGs 富集在以下 GO 术语中：细胞外结构组织、细胞外基质组织、白细胞迁移 II 类蛋白复合物、胶原三螺旋蛋白复合物、细胞外基质结构成分、生长因子结合和血小板衍生生长因子结合。在 KEGG 通路富集分析中，DEGs 富集在金黄色葡萄球菌感染、补体和凝血级联以及哮喘中。通过 PPI 网络分析，我们选择了前 10 个基因，包括 SLCO2B1、STAB1、SERPING1、HLA-DOA、AIF1、GIMAP4、C1orf162、HLA-DMB、ADAP2 和 HAVCR2。通过使用 TCGA 和 THPA 数据库，我们验证了与 BC 骨转移早期检测相关的 2 个基因，即 SERPING1 和 GIMAP4。
结论
2 个异常表达的枢纽基因可能通过影响骨微环境中骨稳态失衡在乳腺癌伴骨转移中发挥关键作用。
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