背景:角化是一种新型的介导的细胞死亡,与几种癌症的进展密切相关,并被认为是潜在的治疗靶标。然而,在胆管癌中的作用,对预后的预测,亚组分类,和治疗策略仍然很大程度上未知。
方法:基于独立的mRNA和蛋白质数据集,对146个角化相关基因和临床信息进行系统分析,以阐明角化相关基因的潜在机制和预后预测价值。构建了一个10-角化相关基因预测模型,其对胆管癌预后的影响与患者的低生存率显著相关。此外,我们模型的表达模式包括在几种胆管癌细胞系和正常胆管上皮细胞系中验证的基因.
结果:首先,一个10-cupprotocol相关的基因签名(ADAM9,ADAM17,ALB,AQP1,CDK1,MT2A,PAM,SOD3,STEAP3和TMPRSS6)对胆管癌的总体生存率表现出出色的预测性能。具有转录组和蛋白质组的低角化症组的预后明显优于高角化症组。第二,与高风险和低风险人群相比,两组显示出不同的肿瘤微环境,内皮细胞比例降低,以及基于CIBERSORTx和EPIC分析的癌症相关成纤维细胞水平升高。第三,患者对化疗药物和免疫检查点的敏感性揭示了两组之间的显著差异.最后,在复制10个基因的表达模式时,这些结果与定量实时聚合酶链反应结果验证了目标基因在胆管癌中的异常表达模式。
结论:总的来说,我们建立并验证了一个有效的预后模型,该模型可以根据10个角化相关基因的分子或蛋白质特征将胆管癌患者分为2种异质角化亚型。这些发现可能为揭示分子特征和定义亚组提供潜在益处,可以改善胆管癌患者的早期诊断和个体化治疗。
BACKGROUND: Cuproptosis is a novel type of mediated cell death strongly associated with the progression of several cancers and has been implicated as a potential therapeutic target. However, the role of cuproptosis in cholangiocarcinoma for prognostic prediction, subgroup classification, and therapeutic strategies remains largely unknown.
METHODS: A systematic analysis was conducted among 146 cuproptosis-related genes and clinical information based on independent mRNA and protein datasets to elucidate the potential mechanisms and prognostic prediction value of cuproptosis-related genes. A 10-cuproptosis-related gene prediction model was constructed, and its effects on cholangiocarcinoma prognosis were significantly connected to poor patient survival. Additionally, the expression patterns of our model included genes that were validated with several cholangiocarcinoma cancer cell lines and a normal biliary epithelial cell line.
RESULTS: First, a 10-cuproptosis-related gene signature (ADAM9, ADAM17, ALB, AQP1, CDK1, MT2A, PAM, SOD3, STEAP3, and TMPRSS6) displayed excellent predictive performance for the overall survival of cholangiocarcinoma. The low-cuproptosis group had a significantly better prognosis than the high-cuproptosis group with transcriptome and protein cohorts. Second, compared with the high-risk and low-risk groups, the 2 groups displayed distinct tumor microenvironments, reduced proportions of endothelial cells, and increased levels of cancer-associated fibroblasts based on CIBERSORTx and EPIC analyses. Third, patients\' sensitivities to chemotherapeutic drugs and immune checkpoints revealed distinctive differences between the 2 groups. Finally, in replicating the expression patterns of the 10 genes, these results were validated with quantitative real-time polymerase chain reaction results validating the abnormal expression pattern of the target genes in cholangiocarcinoma.
CONCLUSIONS: Collectively, we established and verified an effective prognostic model that could separate cholangiocarcinoma patients into 2 heterogeneous cuproptosis subtypes based on the molecular or protein characteristics of 10 cuproptosis-related genes. These findings may provide potential benefits for unveiling molecular characteristics and defining subgroups could improve the early diagnosis and individualized treatment of cholangiocarcinoma patients.