基于失巢凋亡相关基因的前列腺癌预后风险模型的构建与分析

Construction and analysis of a prognostic risk model of anoikis-related genes for prostate cancer

目的 探索失巢凋亡相关基因(anoikis-related genes, ARGs)在前列腺癌(prostate cancer, PCa)预后的评估作用并建立风险模型。方法 基于TCGA和GeneCards在线数据库,我们鉴定了PCa中相关的ARGs。采用GO和KEGG富集分析了ARGs作用于PCa可能的生物学途径。使用COX回归和Lasso回归方法构建有关PCa的预后ARGs模型,基于风险评分将患者分为低风险组和高风险组,分析风险评分与临床特征及预后的关系。采用CIBERSORT法和ssGSEA算法分析ARGs的临床效力和免疫状态。结果 确定了PCa中82个生化复发(BCR)生存相关的ARGs,从中筛选出3个基因(OGT、PTGS2、GNE)来构建预后模型。结果表明ARGs可以准确区分高低风险的PCa患者,具有稳定的预测性能,并可在一定程度反映PCa的特异性免疫状态。Kaplan-Meier生存分析结果显示:高危组患者预后更差。此外,基于模型风险评分绘制的列线图则可更准确地预测PCa患者三年和五年BCR生存率,更方便临床使用。结论 本研究为前列腺癌患者建立了一个ARGs模型,可作为评价预后的新指标,为PCa个体化治疗提供重要参考。

Objective To explore the role of anoikis-related genes(ARGs)in evaluating the prognosis of prostate cancer(PCa)and establish a risk model.Methods Based on the TCGA and GeneCards databases,we identified the anoikis-related genes on PCa.GO and KEGG enrichment analysis was used to predict the possible biological pathways of ARGs acting on PCa.COX and Lasso regression was used to establish a prognostic ARGs model of PCa.Patients were divided into low-risk and high-risk groups based on the risk score.The relationship between risk score and clinical features and prognosis was analyzed.The CIBERSORT method and ssGSEA algorithm were used to analyze ARGs'clinical efficacy and immune status.Results A total of 82 surviving-related ARGs on PCa were identified.OGT,PTGS2 and GNE were screened out to construct a prognostic model.The results showed that ARGs could accurately classify different risk PCa patients with stable predictive performance,and could reflect the specific immune status of PCa.Kaplan-Meier survival analysis showed that patients in the high-risk group had a worse prognosis.In addition,the nomogram based on risk score can more accurately predict the three-year and five-year BCR survival status of PCa patients,which is more convenient for the clinic.Conclusion This study established a prognostic risk model of ARGs for PCa patients,which can serve as a new prognostic indicator and provide an important reference for PCa individualized treatment.