Background: Breast cancer (BC) is the leading cause of tumor-related death in women worldwide, but its pathogenesis is not clear. The efficient screening of new therapeutic targets for BC through bioinformatics and biological experimental techniques has become a hot topic in BC research. Methods:The bioinformatics method was used to analyze the gene chips and obtain the hub genes, playing an important role in the development of BC. The biological processes (BP) involved in the hub genes were analyzed by Bingo, and the impact of each hub gene on disease-free survival (DFS) and overall survival (OS) in BC patients was evaluated in the Kaplan-Meier Plotter database. The expression of DNAJB4, the hub gene with the greatest degree and having an effect on the prognosis of BC patients, was detected in BC cell lines and clinicopathological specimens. And DNAJB4 was selected for further biological experiments and clinical prognosis verification.Results: Ten hub genes including DNAJB4, the greatest degree genes, were found by bioinformatics analysis of BC gene chips. DNAJB4 expressions in both BC cell lines and clinicopathological specimens were detected and the results showed that DNAJB4 was significantly down-regulated in BC cell lines and tissues.After interfering with the expression of DNAJB4, it was found that the invasion and migration ability of MDA-MB-231 cell line was significantly enhanced in vitro. The clinical survival data of BC patients showed that patients with high DNAJB4 expression had longer DFS.Conclusions: DNAJB4 may be a tumor suppressor gene in BC as it could regulate invasion and migration of BC cells and its expression level is related to the prognosis of BC patients. Nevertheless, further researches are still necessary to verify its role in BC so as to provide evidences for clinical guidance regarding diagnosis and treatment.
BackgroundThe commonest malignancy in women is known as breast cancer (BC). Numerous studies demonstrated that apoptosis appears to be critical to the management and clinical outcome of BC patients. The purpose of this study is to explore the potential connection between apoptosis and BC and establish the apoptosis-associated gene signature in BC.MethodsThe data of BC patient transcripts and related clinical information comes from the Cancer Genome Atlas Database (TCGA), and the genes related to apoptosis come from the Molecular Characterization Database (MSigDB). We identified the abnormally expressed apoptosis-related genes in BC samples. The optimal apoptosis-related genes screened by Cox regression analysis were designed to construct a prognostic model for predicting BC patients. Using the Nom Chart to Predict 1-Year, 3-Year, and 5-Year overall survival for BC patients. The gene signature-related functional pathways were explored by gene set enrichment analysis (GSEA).ResultsThree genes [alpha subunit of the interleukin 3 receptor (IL3RA), apoptosis-inducing factor mitochondrial-associated 1 (AIFM1), and phosphatidylinositol-3 kinase catalytic alpha (PIK3CA)] correlated with apoptosis were shown to be strongly linked to the overall survival of BC. Survival analysis shows that the risk score is directly proportional to the poor prognosis of BC patients. Risk assessment based on three genetic characteristics (age, pathological stage N, and pathological stage M) can independently predict the prognosis of patients with BC. The Nom chart is most suitable for assessing the long-term survival rate of BC patients. The results of GSEA demonstrated that numerous cell cycle-related pathways were abundant in the high-risk group.ConclusionWe constructed an apoptosis-associated gene signature in BC, which had a potential clinical application prospect for BC patients.
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