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作 者:时坚 刘雪昂 朱岩[3] 胡冉 马文静 朱毅 SHI Jian;LIU Xue’ang;ZHU Yan;HU Ran;MA Wenjing;ZHU Yi(Pancreas Centre,the First Affiliated Hospital of Nanjing Medical University,Nanjing 210029;Pancreas Institute,Nanjing Medical University,Nanjing 210029;Department of Pathology,the First Affiliated Hospital of Nanjing Medical University,Nanjing 210029,China;Public Laboratory Center,the First Affiliated Hospital of Nanjing Medical University,Nanjing 210029,China)
机构地区:[1]南京医科大学第一附属医院胰腺中心,江苏南京210029 [2]南京医科大学胰腺研究所,江苏南京210029 [3]南京医科大学第一附属医院病理科,江苏南京210029 [4]南京医科大学第一附属医院公共实验中心,江苏南京210029
出 处:《南京医科大学学报(自然科学版)》2023年第7期954-965,共12页Journal of Nanjing Medical University(Natural Sciences)
基 金:江苏省“六大人才高峰”人才项目(WSW⁃032)。
摘 要:目的:基于m1A相关基因在多个数据库中差异表达情况与临床参数建立新的胰腺癌风险评估模型,为胰腺癌治疗和预后分析提供理论依据。方法:通过分析m1A相关基因在TCGA⁃GTEx数据库中的差异表达,利用Cox分析与LASSO回归构建胰腺癌预后风险模型,搭配GEO数据库和本中心胰腺癌病例的基因表达和临床数据验证该模型的准确性与敏感性。结果:筛选出CRLS1与C7orf50两个基因共同构成风险模型,本研究系统验证了该模型有预测胰腺癌预后的显著效能,该模型联合肿瘤突变负荷(tumor mutationburden,TMB)具有更强的预后预测能力。结论:该模型是预测胰腺癌患者预后的新工具。Objective:To establish a new pancreatic cancer risk assessment model based on the differential expression of m1A⁃related genes in multiple databases and clinical parameters,and provide theoretical basis for pancreatic cancer treatment and prognosis analysis.Methods:Differential analysis of m1A⁃related genes was performed in the TCGA⁃GTEx database.Cox analysis and LASSO regression were used to construct a pancreatic cancer prognosis risk model,and the accuracy and sensitivity of the model were verified by gene expression and clinical data from the GEO database and pancreatic cancer cases in our center.Results:CRLS1 and C7orf50 were selected to form the risk model.The study systematically verified that the model had significant efficacy in indicating the prognosis of pancreatic cancer,and the model combined with tumor mutation burden(TMB)had a stronger prognostic indication ability.Conclusion:A new risk model is constructed to indicate the prognosis of pancreatic cancer patients.
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