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作 者:冯洁 蔡勋全 潘勤聪 FENG Jie;CAI Xun-quan;PAN Qin-cong(Department of Gastroenterology shanghai NO.5Hospital affiliated to FuDan University,shanghai 200240,China)
出 处:《肝脏》2024年第3期293-299,共7页Chinese Hepatology
摘 要:目的通过分析TCGA数据库中的肝癌样本联合GTEx数据库中的正常样本,探讨趋化因子受体(CCRs)在肝癌中的重要性。方法收集66个CCRs,筛选差异表达的CCRs,并进行GO功能注释和KEGG通路富集分析,以探索其潜在的生物学功能。使用单因素及多因素Cox回归分析并联合Lasso回归分析,构建了基于四个CCRs(CCR9、CCR7、CCR3和ACKR2)特征的预测评分模型,构建列线图来评估HCC患者的预后并进行免疫分析。结果我们发现风险评分是HCC的独立预后因素。免疫分析提示风险评分与免疫细胞浸润有相关性,表明模型中CCRs可能在HCC免疫微环境中发挥关键作用。结论我们构建了一个预测模型,该模型可用于指导HCC患者的个性化治疗和预后的预测。Objective To explored the importance of chemokine and chemokine receptors(CCRs)in liver cancer by analyzing liver cancer samples in TCGA database and normal samples in GTEx database.Methods We first collected 66 CCRs,then screened the differentially expressed CCRs between the liver cancer and normal liver databases.GO functional annotation and KEGG pathway analysis was performed to explore their potential biological functions.By using univariate Cox regression and multivariate Cox regression analyses combined with Lasso regression analysis,we constructed a prediction model based on four-CCRs(CCR9、CCR7、CCR3 and ACKR2)signature.Next,a nomogram was constructed to assess the prognosis of HCC patients.Results We found that the risk score of this model was an independent prognostic factor of HCC.The correlation between the risk score and immune-cell infiltration as indicated by the four-CCRs signature might play a pivotal role in liver cancer immune microenvironment.Conclusion We constructed a prediction model which might guide personalized treatment and prognosis for liver cancer patients.
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