Using Weighted Gene Co-Expression Network Analysis to Identify Increased MND1 Expression as a Predictor of Poor Breast Cancer Survival

Abstract

Zhaokang Bao,1,* Jiale Cheng,1,* Jiahao Zhu,2,* Shengjun Ji,3 Ke Gu,2 Yutian Zhao,2 Shiyou Yu,1 You Meng1 1Department of Oncology Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, People’s Republic of China; 2Department of Radiotherapy and Oncology, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, People’s Republic of China; 3Department of Radiotherapy and Oncology, The affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: You Meng, Department of Oncology Surgery, The affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, 16 West Baita Road, Suzhou, Jiangsu, People’s Republic of China, Email [email protected]: We used bioinformatics analysis to identify potential biomarker genes and their relationship with breast cancer (BC).Materials and Methods: 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.Results: 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.Conclusion: 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.Keywords: breast neoplasms, immunohistochemistry, polymerase chain reaction, biomarker

Keywords

• breast neoplasms
• immunohistochemistry
• polymerase chain reaction
• biomarker