Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan Province, 610072, China.
TCM Regulating Metabolic Diseases Key Laboratory of Sichuan Province, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan Province, 610072, China.
BMC Microbiol. 2024 Apr 20;24(1):132. doi: 10.1186/s12866-024-03280-x.
Oral microbiota imbalance is associated with the progression of various lung diseases, including lung cancer. Pulmonary nodules (PNs) are often considered a critical stage for the early detection of lung cancer; however, the relationship between oral microbiota and PNs remains unknown.
We conducted a 'Microbiome with pulmonary nodule series study 1' (MCEPN-1) where we compared PN patients and healthy controls (HCs), aiming to identify differences in oral microbiota characteristics and discover potential microbiota biomarkers for non-invasive, radiation-free PNs diagnosis and warning in the future. We performed 16 S rRNA amplicon sequencing on saliva samples from 173 PN patients and 40 HCs to compare the characteristics and functional changes in oral microbiota between the two groups. The random forest algorithm was used to identify PN salivary microbial markers. Biological functions and potential mechanisms of differential genes in saliva samples were preliminarily explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Cluster of Orthologous Groups (COG) analyses.
The diversity of salivary microorganisms was higher in the PN group than in the HC group. Significant differences were noted in community composition and abundance of oral microorganisms between the two groups. Neisseria, Prevotella, Haemophilus and Actinomyces, Porphyromonas, Fusobacterium, 7M7x, Granulicatella and Selenomonas were the main differential genera between the PN and HC groups. Fusobacterium, Porphyromonas, Parvimonas, Peptostreptococcus and Haemophilus constituted the optimal marker sets (area under curve, AUC = 0.80), which can distinguish between patients with PNs and HCs. Further, the salivary microbiota composition was significantly correlated with age, sex, and smoking history (P < 0.001), but not with personal history of cancer (P > 0.05). Bioinformatics analysis of differential genes showed that patients with PN showed significant enrichment in protein/molecular functions related to immune deficiency and energy metabolisms, such as the cytoskeleton protein RodZ, nicotinamide adenine dinucleotide phosphate dehydrogenase (NADPH) dehydrogenase, major facilitator superfamily transporters and AraC family transcription regulators.
Our study provides the first evidence that the salivary microbiota can serve as potential biomarkers for identifying PN. We observed a significant association between changes in the oral microbiota and PNs, indicating the potential of salivary microbiota as a new non-invasive biomarker for PNs.
Clinical trial registration number: ChiCTR2200062140; Date of registration: 07/25/2022.
口腔微生物群落失衡与各种肺部疾病的进展有关,包括肺癌。肺部结节(PNs)常被认为是早期发现肺癌的关键阶段;然而,口腔微生物群与 PNs 之间的关系尚不清楚。
我们进行了一项“肺部结节系列研究 1”(MCEPN-1),比较了 PNs 患者和健康对照者(HCs),旨在确定口腔微生物群落特征的差异,并发现潜在的微生物生物标志物,用于未来非侵入性、无辐射的 PNs 诊断和预警。我们对 173 名 PNs 患者和 40 名 HCs 的唾液样本进行了 16S rRNA 扩增子测序,以比较两组之间口腔微生物群落的特征和功能变化。使用随机森林算法识别 PN 唾液微生物标志物。使用京都基因与基因组百科全书(KEGG)和直系同源群(COG)分析初步探索唾液样本中差异基因的生物学功能和潜在机制。
PN 组的唾液微生物多样性高于 HC 组。两组间口腔微生物群落组成和丰度存在显著差异。PN 和 HC 组之间的主要差异属为Neisseria、Prevotella、Haemophilus 和 Actinomyces、Porphyromonas、Fusobacterium、7M7x、Granulicatella 和 Selenomonas。Fusobacterium、Porphyromonas、Parvimonas、Peptostreptococcus 和 Haemophilus 构成了最佳标志物集(曲线下面积,AUC=0.80),可区分 PNs 患者和 HCs。此外,唾液微生物群落组成与年龄、性别和吸烟史显著相关(P<0.001),但与癌症个人史无关(P>0.05)。差异基因的生物信息学分析表明,PN 患者在与免疫缺陷和能量代谢相关的蛋白质/分子功能中表现出显著的富集,例如细胞骨架蛋白 RodZ、烟酰胺腺嘌呤二核苷酸磷酸脱氢酶(NADPH)脱氢酶、主要易化剂超家族转运蛋白和 AraC 家族转录调节剂。
本研究首次提供了唾液微生物群可作为识别 PN 的潜在生物标志物的证据。我们观察到口腔微生物群的变化与 PNs 之间存在显著关联,表明唾液微生物群作为 PNs 的一种新的非侵入性生物标志物具有潜力。
临床试验注册编号:ChiCTR2200062140;注册日期:2022 年 7 月 25 日。