Jiang Guowei, Wang Ye
Department of Breast, Haining Maternity and Child Health Care Hospital, Haining, Zhejieng, China.
Medicine (Baltimore). 2025 Jan 10;104(2):e41230. doi: 10.1097/MD.0000000000041230.
Endosomes play a pivotal role in cellular biology, orchestrating processes such as endocytosis, molecular trafficking, signal transduction, and recycling of cellular materials. This study aims to construct an endosome-related gene (ERG)-derived risk signature for breast cancer prognosis. Transcriptomic and clinical data were retrieved from The Cancer Genome Atlas and the University of California Santa Cruz databases to build and validate the model. A Lasso Cox regression model was employed for risk signature construction. The immune landscape was assessed using CIBERSORT and ESTIMATE algorithms, while drug sensitivity was evaluated via the pRRophetic algorithm. Gene set enrichment analysis and gene set variation analysis were applied to evaluate gene expression patterns. A nomogram was constructed and validated for predicting breast cancer outcomes. The expression of ERGs in breast cancer cells and tissues was further validated. Sixty-one ERGs associated with breast cancer prognosis were identified, with 23 selected for constructing the risk signature. This signature stratified breast cancer patients into high- and low-risk groups, where the low-risk group exhibited significantly better prognosis. Notably, younger patients tended to have lower risk scores compared to older ones. The low-risk group exhibited enhanced sensitivity to the majority of the drugs tested, accompanied by increased infiltration of T cells and M1 macrophages. Additionally, cell cycle pathways were suppressed in the low-risk group, whereas antigen binding functions were significantly activated. Ultimately, risk score and age were identified as independent prognostic factors for breast cancer, and these factors were incorporated into a nomogram that demonstrated excellent performance in prognosis assessment. Finally, external cohort validated the dysregulation of the risk score-associated ERGs in breast cancer cells and tissues. This study successfully established an ERG-derived breast cancer risk signature and nomogram, elucidating their potential value in prognosis prediction and evaluation of therapeutic response.
内涵体在细胞生物学中发挥着关键作用，协调诸如内吞作用、分子运输、信号转导以及细胞物质循环等过程。本研究旨在构建一种基于内涵体相关基因（ERG）的风险特征模型，用于预测乳腺癌预后。从癌症基因组图谱和加利福尼亚大学圣克鲁兹分校数据库中检索转录组学和临床数据，以构建和验证该模型。采用套索Cox回归模型构建风险特征。使用CIBERSORT和ESTIMATE算法评估免疫格局，通过pRRophetic算法评估药物敏感性。应用基因集富集分析和基因集变异分析评估基因表达模式。构建并验证了用于预测乳腺癌预后的列线图。进一步验证了ERG在乳腺癌细胞和组织中的表达。确定了61个与乳腺癌预后相关的ERG，其中23个用于构建风险特征。该特征将乳腺癌患者分为高风险和低风险组，低风险组的预后明显更好。值得注意的是，年轻患者的风险评分往往低于老年患者。低风险组对大多数测试药物表现出更高的敏感性，同时T细胞和M1巨噬细胞的浸润增加。此外，低风险组的细胞周期途径受到抑制，而抗原结合功能则显著激活。最终，风险评分和年龄被确定为乳腺癌的独立预后因素，并将这些因素纳入列线图，该列线图在预后评估中表现出色。最后，外部队列验证了乳腺癌细胞和组织中与风险评分相关的ERG的失调情况。本研究成功建立了基于ERG的乳腺癌风险特征和列线图，阐明了它们在预后预测和治疗反应评估中的潜在价值。
