摘要
目的探讨肠道微生物组联合临床特征对术前肝细胞癌(hepatocellular carcinoma,HCC)微血管侵犯(microvascular invasion,MVI)的预测价值。方法收集2023年1月至2024年8月在宁波市第二医院行HCC根治术的71例患者临床资料及粪便样本,其中41例作为训练集,30例作为验证集。通过16S rRNA测序分析肠道菌群,采用冗余分析(RDA)评估临床特征对菌群的影响。分析MVI阴性组和阳性组患者的肠道菌群α、β多样性,Wilcoxon检验、LEfSe分析两组差异菌属,随机森林模型及Logistic回归分析筛选关键差异菌属,并进行ROC分析,对AUC值高的菌属进行验证集分析。结果RDA显示MVI是影响菌群的关键因素。随机森林模型(AUC=0.925)联合Logistic回归分析筛选出4个菌属:食酸菌属(Acidovorax,OR=0.618)、泰氏菌属(Tissierella,OR=1.293)、噬几丁质菌属(Chitinophaga,OR=4.596)、杆状孢囊菌属(Virgisporangium,OR=0.960),以及2个临床特征:肿瘤直径(OR=0.668)、肝硬化(OR=14.011)为独立危险因素。ROC分析显示:训练集中噬几丁质菌属(Chitinophaga,AUC=0.71)与肿瘤直径(AUC=0.75)的组合诊断效能最佳(AUC=0.87);验证集中杆状孢囊菌属(Virgisporangium,AUC=0.80)与肿瘤直径(AUC=0.79)的组合诊断效能最佳(AUC=0.87)。结论基于肠道微生物组联合临床特征构建的基因组学模型在治疗前无创评估HCC患者MVI状态具有一定的预测价值。
Objective To explore the value of combining gut microbiota and clinical features for preoperative microvascular invasion(MVI)prediction in hepatocellular carcinoma(HCC).Methods Clinical data and fecal samples were collected from 71 HCC patients who underwent curative resection at Ningbo Second Hospital between Jan 2023 and Aug 2024.Among them,41 patients were assigned to the training set and 30 to the validation set.Gut microbiota composition was analyzed using 16S rRNA sequencing.Redundancy analysis(RDA)was used to evaluate the influence of clinical features on the microbiota.Differences in alpha and beta diversity between the MVI-negative and MVI-positive groups were assessed.Differential genera were identified using the Wilcoxon test and LEfSe analysis.A random forest model and Logistic regression were employed to screen key differential genera,followed by ROC analysis.Genera with high ROC values were further validated in the validation set.Results RDA indicated that MVI was a key factor influencing gut microbiota composition.The random forest model(AUC=0.925),combined with Logistic regression analysis,identified four genera:Acidovorax(OR=0.618),Tissierella(OR=1.293),Chitinophaga(OR=4.596),and Virgisporangium(OR=0.960),as well as two clinical features:tumor diameter(OR=0.668)and liver cirrhosis(OR=14.011),as independent risk factors.ROC analysis showed that in the training set,the combination of Chitinophaga(AUC=0.71)and tumor diameter(AUC=0.75)had the best diagnostic performance(AUC=0.87).In the validation set,the combination of Virgisporangium(AUC=0.80)and tumor diameter(AUC=0.79)yielded the highest diagnostic performance(AUC=0.87).Conclusions A genomics-based model combining gut microbiota and clinical features shows promising predictive value for noninvasive preoperative assessment of MVI status in HCC patients.
作者
闻人湖滨
李博文
汪之越
张堃彧
刘洋
魏云巍
Wenren Hubin;Li Bowen;Wang Zhiyue;Zhang Kunyu;Liu Yang;Wei Yunwei(Department of Hepatobiliary and Pancreatic Surgery Division,Ningbo No.2 Hospital,Ningbo 315010,China;Key Laboratory of Intestinal Microecology and Major Human Diseases in Ningbo,Ningbo 315010,China)
出处
《中华普通外科杂志》
北大核心
2025年第9期706-713,共8页
Chinese Journal of General Surgery
基金
国家自然科学基金(U23A20458,82300631)
浙江省自然科学基金重点项目(LHDMZ25H160004)
宁波市医疗卫生高端团队重大攻坚项目(2022010101)
宁波市肠道微生态与人类重大疾病重点实验室资助项目(2023016)。
关键词
癌
肝细胞
微生物组
微血管侵犯
16S
rRNA基因测序
临床特征
Carcinoma,hepatocellular
Microbiome
Microvascular invasion
16S rRNA gene sequencing
Clinical features
