PDF(Pubmed)
Abstract：
UNASSIGNED: The human microbiota plays a key role in cancer diagnosis, pathogenesis, and treatment. However, osteosarcoma-associated oral microbiota alterations have not yet been unraveled. The aim of this study was to explore the characteristics of oral microbiota in osteosarcoma patients compared to healthy controls, and to identify potential microbiota as a diagnostic tool for osteosarcoma.
UNASSIGNED: The oral microbiota was analyzed in osteosarcoma patients (n = 45) and matched healthy controls (n = 90) using 16S rRNA MiSeq sequencing technology.
UNASSIGNED: The microbial richness and diversity of the tongue coat were increased in osteosarcoma patients as estimated by the abundance-based coverage estimator indices, the Chao, and observed operational taxonomy units (OTUs). Principal component analysis delineated that the oral microbial community was significant differences between osteosarcoma patients and healthy controls. 14 genera including Rothia, Halomonas, Rhodococcus, and Granulicatella were remarkably reduced, whereas Alloprevotella, Prevotella, Selenomonas, and Campylobacter were enriched in osteosarcoma. Eventually, the optimal four OTUs were identified to construct a microbial classifier by the random forest model via a fivefold cross-validation, which achieved an area under the curve of 99.44% in the training group (30 osteosarcoma patients versus 60 healthy controls) and 87.33% in the test group (15 osteosarcoma patients versus 30 healthy controls), respectively. Notably, oral microbial markers validated strong diagnostic potential distinguishing osteosarcoma patients from healthy controls.
UNASSIGNED: This study comprehensively characterizes the oral microbiota in osteosarcoma and reveals the potential efficacy of oral microbiota-targeted biomarkers as a noninvasive biological diagnostic tool for osteosarcoma.
UNASSIGNED: The oral microbiota was analyzed in osteosarcoma patients (n = 45) and matched healthy controls (n = 90) using 16S rRNA MiSeq sequencing technology.
UNASSIGNED: The microbial richness and diversity of the tongue coat were increased in osteosarcoma patients as estimated by the abundance-based coverage estimator indices, the Chao, and observed operational taxonomy units (OTUs). Principal component analysis delineated that the oral microbial community was significant differences between osteosarcoma patients and healthy controls. 14 genera including Rothia, Halomonas, Rhodococcus, and Granulicatella were remarkably reduced, whereas Alloprevotella, Prevotella, Selenomonas, and Campylobacter were enriched in osteosarcoma. Eventually, the optimal four OTUs were identified to construct a microbial classifier by the random forest model via a fivefold cross-validation, which achieved an area under the curve of 99.44% in the training group (30 osteosarcoma patients versus 60 healthy controls) and 87.33% in the test group (15 osteosarcoma patients versus 30 healthy controls), respectively. Notably, oral microbial markers validated strong diagnostic potential distinguishing osteosarcoma patients from healthy controls.
UNASSIGNED: This study comprehensively characterizes the oral microbiota in osteosarcoma and reveals the potential efficacy of oral microbiota-targeted biomarkers as a noninvasive biological diagnostic tool for osteosarcoma.
摘要：
■人类微生物群在癌症诊断中起着关键作用，发病机制，和治疗。然而,骨肉瘤相关的口腔微生物群改变尚未被揭开。这项研究的目的是探讨与健康对照组相比，骨肉瘤患者口腔微生物群的特征。并确定潜在的微生物群作为骨肉瘤的诊断工具。
■使用16SrRNAMiSeq测序技术分析了骨肉瘤患者（n=45）和匹配的健康对照（n=90）的口腔微生物群。
■根据基于丰度的覆盖率估计指数估计，骨肉瘤患者舌衣的微生物丰度和多样性增加，朝,并观察到操作分类单位(OTU)。主成分分析表明，口腔微生物群落在骨肉瘤患者和健康对照组之间存在显着差异。14属，包括Rothia，Halomonas,红球菌,颗粒菌明显减少，而Alloprevotella,普雷沃氏菌,硒单胞菌,和弯曲杆菌在骨肉瘤中富集。最终,通过五次交叉验证，通过随机森林模型确定了最优的四个OTU来构建微生物分类器，训练组（30例骨肉瘤患者与60例健康对照）和试验组（15例骨肉瘤患者与30例健康对照）的曲线下面积分别为99.44％和87.33％，分别。值得注意的是,口腔微生物标记物验证了将骨肉瘤患者与健康对照区分开来的强大诊断潜力.
■这项研究全面表征了骨肉瘤中口腔微生物群，并揭示了口腔微生物群靶向生物标志物作为骨肉瘤非侵入性生物诊断工具的潜在功效。
■使用16SrRNAMiSeq测序技术分析了骨肉瘤患者（n=45）和匹配的健康对照（n=90）的口腔微生物群。
■根据基于丰度的覆盖率估计指数估计，骨肉瘤患者舌衣的微生物丰度和多样性增加，朝,并观察到操作分类单位(OTU)。主成分分析表明，口腔微生物群落在骨肉瘤患者和健康对照组之间存在显着差异。14属，包括Rothia，Halomonas,红球菌,颗粒菌明显减少，而Alloprevotella,普雷沃氏菌,硒单胞菌,和弯曲杆菌在骨肉瘤中富集。最终,通过五次交叉验证，通过随机森林模型确定了最优的四个OTU来构建微生物分类器，训练组（30例骨肉瘤患者与60例健康对照）和试验组（15例骨肉瘤患者与30例健康对照）的曲线下面积分别为99.44％和87.33％，分别。值得注意的是,口腔微生物标记物验证了将骨肉瘤患者与健康对照区分开来的强大诊断潜力.
■这项研究全面表征了骨肉瘤中口腔微生物群，并揭示了口腔微生物群靶向生物标志物作为骨肉瘤非侵入性生物诊断工具的潜在功效。
