乳腺癌（BC）是一种多方面的恶性肿瘤，发病率和死亡率逐年上升。化疗是治疗乳腺癌不可或缺的方法，但耐药性带来了巨大的挑战。通过转录组数据分析，我们确定了两组在这种情况下表现出差异表达的基因。此外，我们还证实了这些基因与外泌体相关基因之间的重叠，随后在细胞系中进行了验证。该研究筛选了已识别的基因以确定 BC 的预后标记，并利用它们制定预后模型。使用测试数据集验证了高风险组和低风险组之间的预后和免疫力的差异。我们根据 BC 样本中预后基因的表达水平辨别了不同的 BC 亚型。研究了不同亚型之间预后、免疫力和药物敏感性的差异。利用单细胞测序和预后基因表达的数据，AUCell 算法用于对单个细胞簇进行评分并分析高分组中涉及的通路。随后使用 RT-qPCR 验证预后基因（CCT4、CXCL13、MTDH、PSMD2 和 RAB27A）。因此，我们建立了一个预测乳腺癌预后的模型，该模型取决于耐药性和 ERG。此外，我们还评估了该模型的预后价值。被确定为预后标记的基因现在可以作为精确治疗这种疾病的参考。© 2024。作者。

Breast cancer (BC) represents a multifaceted malignancy, with escalating incidence and mortality rates annually. Chemotherapy stands as an indispensable approach for treating breast cancer, yet drug resistance poses a formidable challenge. Through transcriptome data analysis, we have identified two sets of genes exhibiting differential expression in this context. Furthermore, we have confirmed the overlap between these genes and those associated with exosomes, which were subsequently validated in cell lines. The investigation screened the identified genes to determine prognostic markers for BC and utilized them to formulate a prognostic model. The disparities in prognosis and immunity between the high- and low-risk groups were validated using the test dataset. We have discerned different BC subtypes based on the expression levels of prognostic genes in BC samples. Variations in prognosis, immunity, and drug sensitivity among distinct subtypes were examined. Leveraging data from single-cell sequencing and prognostic gene expression, the AUCell algorithm was employed to score individual cell clusters and analyze the pathways implicated in high-scoring groups. Prognostic genes (CCT4, CXCL13, MTDH, PSMD2, and RAB27A) were subsewoquently validated using RT-qPCR. Consequently, we have established a model for predicting prognosis in breast cancer that hinges on drug resistance and ERGs. Furthermore, we have evaluated the prognostic value of this model. The genes identified as prognostic markers can now serve as a reference for precise treatment of this condition.© 2024. The Author(s).