摘要
目的分析m6A调节因子对膀胱癌(bladder cancer,BC)预后的影响,建立预后预测模型。方法从癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库获取397例BC组织的高通量测序数据和对应的临床病理特征数据。在26个m6A调节因子中,采用单因素Cox回归筛选预后相关的m6A调节因子,利用最小绝对值收敛和选择算子(least absolute shrinkage and selection operator,LASSO)Cox回归分析方法构建BC预后预测模型,比较高低风险组总生存期(overall survival,OS)、免疫检查点相关基因和靶向治疗相关基因表达的差异。通过基因集富集分析比较高低风险组中信号通路的富集情况,采用单样本基因富集分析(single sample gene set enrichment analysis,ssGSEA)和估计恶性肿瘤组织中基质和免疫细胞(estimation of stromal and immune cells in malignant tumors using expression data,ESTIMATE)法评估高低风险组免疫细胞浸润水平的差异。结果YTHDC1、IGF2BP3、LRPPRC、FTO和ALKBH3是BC独立的预后因素。利用LASSO Cox回归方法基于5个m6A调节因子建立BC预后预测风险模型,Kaplan-Meier分析结果提示高低风险组间OS存在显著差异(P<0.001),受试者工作特征(receiver operating characteristic,ROC)曲线下面积为0.665。高风险组在趋化因子、NOD样受体、嘌呤代谢、丙酮酸代谢等信号通路富集,具有丰富的免疫细胞浸润特征,PD-L1、CTLA-4、EGFR和KRAS基因表达更高。结论本研究基于m6A调节因子构建的BC预后预测模型准确性较好,有助于临床上预后判断和分层个体化治疗。
Objective To analyze the effect of m6A regulators on the prognosis of bladder cancer(BC),and establish a prognostic prediction model.Methods The high-throughput sequencing data and clinicopathological characteristics from 397 BC tissues were obtained from The Cancer Genome Atlas(TCGA)database.Among the 26 m6A regulators,univariate Cox regression was used to screen for prognostic m6A regulators in BC.Least absolute shrinkage and selection operator(LASSO)Cox regression analysis was used to establish a BC prognosis risk model.The differences in overall survival(OS),and expression of immune checkpoint related gene and targeted therapy related gene between high and low-risk groups were compared.Gene set enrichment analysis was conducted to compare the enrichment of signaling pathways between high and low-risk groups.Single sample gene set enrichment analysis(ssGSEA)and estimation of stromal and immune cells in malignant tumor tissues using expression data(ESTIMATE)methods were used to evaluate the differences in immune cell infiltration levels between high and low-risk groups.Results YTHDC1,IGF2BP3,LRPPRC,FTO,and ALKBH3 were independent prognostic factors for BC.The LASSO Cox regression method was used to establish a prognostic risk model for BC based on these 5 m6A regulators.The Kaplan-Meier analysis showed significant differences in OS between high and low-risk groups(P<0.001),with an area under the receiver operating characteristic(ROC)curve of 0.665.The high-risk group was enriched in signaling pathways such as chemokines,NOD-like receptors,purine metabolism,and pyruvate metabolism,and had rich immune cell infiltration characteristics.The expression of PD-L1,CTLA-4,EGFR,and KRAS genes were higher in the high-risk group.Conclusion The prognosis model constructed based on m6A regulators in this study has good accuracy,which is helpful for clinical prognosis and stratified individualized treatment.
作者
白洋洋
郭依琳
陈瑞廷
潘世杰
孙继建
BAI Yangyang;GUO Yilin;CHEN Ruiting;PAN Shijie;Sun Jijian(Department of Urology,Henan Province Hospital of TCM(The Second Affliated Hospital of Henan University of Chinese Medicine),Zhengzhou 450002,China;Clinical Medical Research Center of Gynecological Tumor,The Second Affiliated Hospital of Zhengzhou University,Zhengzhou 450014,China)
出处
《数理医药学杂志》
CAS
2024年第3期180-189,共10页
Journal of Mathematical Medicine
基金
河南省卫生健康委国家中医临床研究基地科研专项(2022JDZX142)。
关键词
膀胱癌
m6A调节因子
免疫浸润
预后模型
Bladder cancer
m6A regulators
Immune infiltration
Prognostic model
