PDF(Pubmed)
Abstract：
UNASSIGNED: This study aimed to explore disulfidptosis-related clusters of triple-negative breast cancer (TNBC) and build a reliable disulfidptosis-related gene signature for forecasting TNBC prognosis.
UNASSIGNED: The disulfidptosis-related clusters of TNBC were identified based on public datasets, and a comparative analysis was conducted to assess their differences in the overall survival (OS) and immune cell infiltration. Morever, the differentially expressed genes (DEGs) between clusters were recognized. Then, the prognostic DEGs were then chosen. A prognostic signature was constructed by the prognostic DEGs, followed by nomogram construction, drug sensitivity, immune correlation, immunotherapy response prediction, and cluster association analyses.
UNASSIGNED: Two disulfidptosis-related clusters of TNBC were identified, which had different OS and macrophage infiltration. Moreover, 235 DEGs were identified between two clusters. A prognostic signature was then constructed by five prognostic DEGs including HLA-DQA2, CCL13, GBP1, LAMP3, and SLC7A11. This signature was highly valuable in predicting prognosis. A nomogram was built by risk score and AJCC stage, which could forecast OS accurately. Moreover, patients with high-risk scores exhibited greater sensitivity to chemotherapy drugs such as lapatinib and had a lower immunotherapy response.
UNASSIGNED: Two TNBC clusters linked to disulfidptosis were identified, with different OS and immune cell infiltration. Moreover, a five-disulfidptosis-related gene signature may be a powerful prognostic biomarker for TNBC.
UNASSIGNED: The disulfidptosis-related clusters of TNBC were identified based on public datasets, and a comparative analysis was conducted to assess their differences in the overall survival (OS) and immune cell infiltration. Morever, the differentially expressed genes (DEGs) between clusters were recognized. Then, the prognostic DEGs were then chosen. A prognostic signature was constructed by the prognostic DEGs, followed by nomogram construction, drug sensitivity, immune correlation, immunotherapy response prediction, and cluster association analyses.
UNASSIGNED: Two disulfidptosis-related clusters of TNBC were identified, which had different OS and macrophage infiltration. Moreover, 235 DEGs were identified between two clusters. A prognostic signature was then constructed by five prognostic DEGs including HLA-DQA2, CCL13, GBP1, LAMP3, and SLC7A11. This signature was highly valuable in predicting prognosis. A nomogram was built by risk score and AJCC stage, which could forecast OS accurately. Moreover, patients with high-risk scores exhibited greater sensitivity to chemotherapy drugs such as lapatinib and had a lower immunotherapy response.
UNASSIGNED: Two TNBC clusters linked to disulfidptosis were identified, with different OS and immune cell infiltration. Moreover, a five-disulfidptosis-related gene signature may be a powerful prognostic biomarker for TNBC.
摘要：
■本研究旨在探索三阴性乳腺癌（TNBC）的双硫功能下垂相关簇，并建立可靠的双硫功能下垂相关基因标记以预测TNBC预后。
■基于公共数据集确定了TNBC的二硫化物沉积相关簇，并进行了比较分析，以评估它们在总生存期（OS）和免疫细胞浸润方面的差异。而且,识别簇之间的差异表达基因(DEGs)。然后，然后选择预后DEGs.通过预后DEGs构建预后特征，其次是列线图构造，药物敏感性,免疫相关性，免疫治疗反应预测，和聚类关联分析。
■确定了两个与二硫化物沉积相关的TNBC簇，有不同的OS和巨噬细胞浸润。此外，在两个集群之间鉴定了235个DEG。然后通过包括HLA-DQA2、CCL13、GBP1、LAMP3和SLC7A11的五个预后性DEGs构建预后特征。该特征在预测预后方面非常有价值。根据风险评分和AJCC阶段建立列线图，可以准确预测操作系统。此外，高风险评分的患者对lapatinib等化疗药物的敏感性更高,免疫治疗反应较低.
■确定了两个与二硫键沉积有关的TNBC簇，具有不同的OS和免疫细胞浸润。此外，5-二硫键下垂相关基因标记可能是TNBC的一个强有力的预后生物标志物.
■基于公共数据集确定了TNBC的二硫化物沉积相关簇，并进行了比较分析，以评估它们在总生存期（OS）和免疫细胞浸润方面的差异。而且,识别簇之间的差异表达基因(DEGs)。然后，然后选择预后DEGs.通过预后DEGs构建预后特征，其次是列线图构造，药物敏感性,免疫相关性，免疫治疗反应预测，和聚类关联分析。
■确定了两个与二硫化物沉积相关的TNBC簇，有不同的OS和巨噬细胞浸润。此外，在两个集群之间鉴定了235个DEG。然后通过包括HLA-DQA2、CCL13、GBP1、LAMP3和SLC7A11的五个预后性DEGs构建预后特征。该特征在预测预后方面非常有价值。根据风险评分和AJCC阶段建立列线图，可以准确预测操作系统。此外，高风险评分的患者对lapatinib等化疗药物的敏感性更高,免疫治疗反应较低.
■确定了两个与二硫键沉积有关的TNBC簇，具有不同的OS和免疫细胞浸润。此外，5-二硫键下垂相关基因标记可能是TNBC的一个强有力的预后生物标志物.
