Qian Kai, Deng Yi, Krimsky William S, Feng Yong-Geng, Peng Jun, Tai Yong-Hang, Peng Hao, Jiang Li-Hong
Department of Thoracic Surgery, The First People's Hospital of Yunnan Province, Kunming, China.
The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.
Front Oncol. 2022 Apr 12;12:811279. doi: 10.3389/fonc.2022.811279. eCollection 2022.
Microbes and microbiota dysbiosis are correlated with the development of lung cancer; however, the airway taxa characteristics and bacterial topography in synchronous multiple primary lung cancer (sMPLC) are not fully understood. The present study aimed to investigate the microbiota taxa distribution and characteristics in the airways of patients with sMPLC and clarify specimen acquisition modalities in these patients. Using the precise positioning of electromagnetic navigation bronchoscopy (ENB), we analyzed the characteristics of the respiratory microbiome, which were collected from different sites and using different sampling methods. Microbiome predictor variables were bacterial DNA burden and bacterial community composition based on 16sRNA. Eight non-smoking patients with sMPLC in the same pulmonary lobe were included in this study. Compared with other sampling methods, bacterial burden and diversity were higher in surface areas sampled by bronchoalveolar lavage (BAL). Bacterial topography data revealed that the segment with sMPLC lesions provided evidence of specific colonizing bacteria in segments with lesions. After taxonomic annotation, we identified 4863 phylotypes belonging to 185 genera and 10 different phyla. The four most abundant specific bacterial community members detected in the airway containing sMPLC lesions were , and , which all peaked at the segments with sMPLC lesions. This study begins to define the bacterial topography of the respiratory tract in patients with sMPLC and provides an approach to specimen acquisition for sMPLC, namely BAL fluid obtained from segments where lesions are located.
微生物与微生物群失调与肺癌的发生发展相关;然而,同步性多原发性肺癌(sMPLC)中的气道分类群特征和细菌分布情况尚未完全明确。本研究旨在调查sMPLC患者气道中的微生物分类群分布及特征,并阐明这些患者的标本采集方式。利用电磁导航支气管镜(ENB)的精确定位,我们分析了从不同部位并采用不同采样方法收集的呼吸道微生物组的特征。微生物组预测变量为基于16sRNA的细菌DNA负荷和细菌群落组成。本研究纳入了8例同一肺叶内的非吸烟sMPLC患者。与其他采样方法相比,支气管肺泡灌洗(BAL)采样的表面区域细菌负荷和多样性更高。细菌分布数据显示,有sMPLC病变的节段存在病变节段特异性定植细菌的证据。经过分类注释后,我们鉴定出属于185个属和10个不同门的4863个系统发育型。在含有sMPLC病变的气道中检测到的四种最丰富的特异性细菌群落成员为 、 和 ,它们在有sMPLC病变的节段均达到峰值。本研究开始明确sMPLC患者呼吸道的细菌分布情况,并提供了一种sMPLC标本采集方法,即从病变所在节段获取的BAL液。