Li Pengyu, Zhang Hanyu, Gao Xingyu, Chen Lixin, Chen Haomin, Yuan Shuai, Chen Weijie, Dai Menghua
Department of General Surgery, Peking Union Medical College Hospital (PUMCH), Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
BMC Microbiol. 2024 Dec 19;24(1):527. doi: 10.1186/s12866-024-03687-6.
Significant gaps exist in understanding the gastrointestinal microbiota in patients with pancreatic cancer (PCA) versus benign or low-grade malignant pancreatic tumors (NPCA). This study aimed to analyze these microbiota characteristics and explore their potential use in distinguishing malignant pancreatic lesions.
Between September 2020 and May 2024, fecal and oral samples were collected from 121 patients undergoing surgical resection or diagnostic biopsy of pancreatic lesions, including 75 patients with PCA and 46 patients with NPCA, and 16s rRNA sequencing was performed. Random forest models based using fecal and oral microbiota data were developed to diagnose PCA and NPCA, with performance assessed using the leave-one-out cross validation method.
The Shannon index and PCoA analysis revealed significant differences in oral microbiota composition between PCA and NPCA (p < 0.001 and p = 0.001, respectively). Fecal microbiome richness differed significantly (p = 0.02), though composition similarity was noted (p = 0.238). LEfSe identified 16 and 23 genera with significant differences in fecal and oral microbiomes, respectively. Random forest classifiers based on fecal and oral microbiota achieved areas under the curves (AUCs) of 89.4% and 96.3%, respectively, for distinguishing PCA and NPCA. In the mucinous tumor cohort, oral and fecal microbiome classifiers outperformed CA19-9, yielding AUCs of 83.0% and 85.2%, respectively.
Fecal and oral microbiota compositions were significantly different between PCA and NPCA patients. Random forest classifiers utilizing fecal and oral microbiota data effectively distinguish between benign or low-grade malignant and malignant pancreatic lesions.
在理解胰腺癌（PCA）患者与良性或低度恶性胰腺肿瘤（NPCA）患者的胃肠道微生物群方面存在显著差距。本研究旨在分析这些微生物群特征，并探索其在区分恶性胰腺病变中的潜在用途。
2020年9月至2024年5月期间，收集了121例接受胰腺病变手术切除或诊断性活检患者的粪便和口腔样本，其中包括75例PCA患者和46例NPCA患者，并进行了16s rRNA测序。基于粪便和口腔微生物群数据开发了随机森林模型来诊断PCA和NPCA，并使用留一法交叉验证方法评估其性能。
香农指数和主坐标分析显示，PCA和NPCA患者的口腔微生物群组成存在显著差异（分别为p < 0.001和p = 0.001）。粪便微生物群丰富度存在显著差异（p = 0.02），不过在组成相似性方面也有发现（p = 0.238）。线性判别分析效应大小（LEfSe）分别在粪便和口腔微生物群中鉴定出16个和23个具有显著差异的属。基于粪便和口腔微生物群的随机森林分类器在区分PCA和NPCA时，曲线下面积（AUC）分别达到89.4%和96.3%。在黏液性肿瘤队列中，口腔和粪便微生物群分类器的表现优于糖类抗原19-9（CA19-9），AUC分别为83.0%和85.2%。
PCA和NPCA患者的粪便和口腔微生物群组成存在显著差异。利用粪便和口腔微生物群数据的随机森林分类器能有效区分良性或低度恶性与恶性胰腺病变。
