Mo Shufen, Zhong Haiming, Dai Weiping, Li Yuanyuan, Qi Bin, Li Taidong, Cai Yongguang
Medical Oncology, Central Hospital of Guangdong Provincial Nongken, Zhanjiang, Guangdong, China.
Pathology, Central Hospital of Guangdong Provincial Nongken, Zhanjiang, Guangdong, China.
BMC Genom Data. 2025 Jan 10;26(1):2. doi: 10.1186/s12863-024-01292-0.
HER2-positive breast cancer (BC) is a subtype of breast cancer. Increased ERBB3 expression has been implicated as a potential cause of resistance to other HER-targeted therapies. Our study aimed to screen and validate prognostic markers associated with ERBB3 expression by bioinformatics and affecting the prognosis of HER2 staging.
Analyzing differences in ERBB3-related groups. ERBB3 expression-related differentially expressed genes (DEGs) were identified and intersected with survival status-related DEGs to obtain intersected genes. Three algorithms, LASSO, RandomForest and XGBoost were combined to identify the signature genes. we construct risk models and generate ROC curves for prediction. Furthermore, we delve into the immunological traits, correlations, and expression patterns of signature genes by conducting a comprehensive analysis that encompasses immune infiltration analysis, correlation analysis, and differential expression analysis.
Significant variability in ERBB3 expression and prognosis in high and low ERBB3 expression groups. Twenty-five candidate DEGs were identified by intersecting ERBB3-related DEGs with survival-related DEGs. Utilizing three distinct machine learning algorithms, we identified three signature genes-PBX1, IGHM, and CXCL13-that exhibited significant diagnostic value within the diagnostic model. In addition, the risk model had better prognostic and predictive effects, and the immune infiltration analysis showed that IGHM, CXCL13 might affect the proliferation of BC cells through immune cells. Functional studies demonstrated that interference with PBX1 inhibited the proliferation, migration, and epithelial-mesenchymal transition process of HER2-positive BC cells.
PBX1, IGHM and CXCL13 are associated with the expression level of the ERBB3 and are prognostic markers for HER2-positive in BC, which may play an important role in the development and progression of BC.
人表皮生长因子受体2（HER2）阳性乳腺癌（BC）是乳腺癌的一种亚型。ERBB3表达增加被认为是对其他HER靶向治疗耐药的潜在原因。我们的研究旨在通过生物信息学筛选和验证与ERBB3表达相关的预后标志物，并影响HER2分期的预后。
分析ERBB3相关组的差异。鉴定ERBB3表达相关的差异表达基因（DEG），并与生存状态相关的DEG进行交集分析以获得交集基因。结合套索（LASSO）、随机森林和极端梯度提升（XGBoost）三种算法来识别特征基因。我们构建风险模型并生成预测的ROC曲线。此外，我们通过进行包括免疫浸润分析、相关性分析和差异表达分析在内的综合分析，深入研究特征基因的免疫特征、相关性和表达模式。
高、低ERBB3表达组中ERBB3表达和预后存在显著差异。通过将ERBB3相关的DEG与生存相关的DEG进行交集分析，鉴定出25个候选DEG。利用三种不同的机器学习算法，我们鉴定出三个特征基因——PBX1、免疫球蛋白M（IGHM）和CXC趋化因子配体13（CXCL13）——它们在诊断模型中表现出显著的诊断价值。此外，风险模型具有更好的预后和预测效果，免疫浸润分析表明IGHM、CXCL13可能通过免疫细胞影响BC细胞的增殖。功能研究表明，干扰PBX1可抑制HER2阳性BC细胞的增殖、迁移和上皮-间质转化过程。
PBX1、IGHM和CXCL13与ERBB3的表达水平相关，是BC中HER2阳性的预后标志物，可能在BC的发生和发展中起重要作用。
