Bao Zhaokang, Cheng Jiale, Zhu Jiahao, Ji Shengjun, Gu Ke, Zhao Yutian, Yu Shiyou, Meng You
Department of Oncology Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, People's Republic of China.
Department of Radiotherapy and Oncology, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, People's Republic of China.
Int J Gen Med. 2022 May 14;15:4959-4974. doi: 10.2147/IJGM.S354826. eCollection 2022.
We used bioinformatics analysis to identify potential biomarker genes and their relationship with breast cancer (BC).
We used a weighted gene co-expression network analysis (WGCNA) to create a co-expression network based on the top 25% genes in the GSE24124, GSE33926, and GSE86166 datasets obtained from the Gene Expression Omnibus. We used the DAVID online platform to perform GO and KEGG pathway enrichment analyses and the Cytoscape CytoHubba plug-in to screen the potential genes. Then, we related the genes to prognostic values in BC using the Oncomine, GEPIA, and Kaplan-Meier Plotter databases. Findings were validated by immunohistochemical (IHC) staining in the Human Protein Atlas and the TCGA-BRCA cohort. LinkedOmics identified the interactive expressions of hub genes. We used UALCAN to evaluate the methylation levels of these hub genes. MethSurv and SurvivalMeth were used to assess the multilevel prognostic value. Finally, we assessed hub gene association with immune cell infiltration using TIMER.
The mRNA levels of MKI67, UBE2C, GTSE1, CCNA2, and MND1 were significantly upregulated in BC, whereas ESR1, THSD4, TFF1, AGR2, and FOXA1 were significantly downregulated. The DNA methylation signature analysis showed a better prognosis in the low-risk group. Further subgroup analyses revealed that MND1 might serve as an independent risk factor for unfavorable BC prognosis. Additionally, MND1 expression levels positively correlate with the immune infiltration statuses of CD4+ T cells, CD8+ T cells, B cells, neutrophils, dendritic cells, and macrophages.
Our results indicate that the ten hub genes may be involved in BC's carcinogenesis, development, or metastasis, and MND1 may be a potential biomarker and therapeutic target for BC.
我们运用生物信息学分析来鉴定潜在的生物标志物基因及其与乳腺癌（BC）的关系。
我们使用加权基因共表达网络分析（WGCNA），基于从基因表达综合数据库获取的GSE24124、GSE33926和GSE86166数据集中排名前25%的基因创建共表达网络。我们使用DAVID在线平台进行基因本体（GO）和京都基因与基因组百科全书（KEGG）通路富集分析，并使用Cytoscape的CytoHubba插件筛选潜在基因。然后，我们利用Oncomine、GEPIA和Kaplan-Meier Plotter数据库将这些基因与BC的预后价值相关联。研究结果在人类蛋白质图谱和TCGA-BRCA队列中通过免疫组织化学（IHC）染色进行验证。LinkedOmics确定了枢纽基因的交互表达。我们使用UALCAN评估这些枢纽基因的甲基化水平。MethSurv和SurvivalMeth用于评估多层次的预后价值。最后，我们使用TIMER评估枢纽基因与免疫细胞浸润的关联。
MKI67、UBE2C、GTSE1、CCNA2和MND1的mRNA水平在BC中显著上调；而ESR-1、THSD4、TFF1、AGR2和FOXA1显著下调。DNA甲基化特征分析显示低风险组预后较好。进一步的亚组分析表明，MND1可能是BC不良预后的独立危险因素。此外，MND1表达水平与CD4+T细胞、CD8+T细胞、B细胞、中性粒细胞、树突状细胞和巨噬细胞的免疫浸润状态呈正相关。
我们的结果表明，这十个枢纽基因可能参与BC的致癌、发展或转移过程，且MND1可能是BC的潜在生物标志物和治疗靶点。
