Dysbiosis of the Salivary Microbiome Is Associated With Non-smoking Female Lung Cancer and Correlated With lmmunocytochemistry Markers
Dysbiosis of the Salivary Microbiome Is Associated With Non-smoking Female Lung Cancer and Correlated With lmmunocytochemistry Markers
复制标题
唾液微生物群失调与非吸烟女性肺癌相关，并与免疫细胞化学标记物相关
DOI：
10.3389/fonc.2018.00520
复制
发表时间：
2018-11-20
影响因子：
4.7
通讯作者：
Zhang, Lei
中科院分区：
文献类型：
--
作者：
Yang, Junjie;Mu, Xiaofeng;Zhang, Lei
背景资料：口腔细菌与肺癌风险增加之间的关联在以前的几项研究中已有报道，然而，尚未评估唾液微生物组与非吸烟女性肺癌之间的潜在关联。免疫细胞化学标记物与唾液微生物群之间的关系也未见报道。方法：在这项研究中，我们使用16 S rRNA基因扩增子测序评估了75名非吸烟女性肺癌患者和172名匹配的健康个体的唾液微生物组。我们还计算了唾液微生物群与三种免疫组织化学标记物（TTF-1、Napsin A和CK 7）之间的斯皮尔曼等级相关系数。结果：我们分析了247名受试者的唾液微生物群，发现非吸烟女性肺癌患者表现出口腔微生物生态失调。肺癌组微生物多样性和丰富度均显著低于对照组（Shannon指数，P < 0.01; Ace指数，P < 0.0001）。基于相似性分析，肺癌患者的微生物群组成也不同于对照组（r = 0.454，P < 0.001，未加权UniFrac; r = 0.113，P < 0.01，加权UniFrac）。非吸烟女性肺癌患者中鞘氨醇单胞菌属（P < 0.05）和芽生单胞菌属（P < 0.0001）相对较高，而对照组中不动杆菌属（P < 0.001）和链球菌属（P < 0.01）相对较高。经斯皮尔曼相关分析，CK 7与肠杆菌科细菌之间存在显著正相关（r = 0.223，P < 0.05）。同时，Napsin A与芽生单胞菌属呈正相关（r = 0.251，P < 0.05）。TTF-1与肠杆菌科细菌呈显著正相关（r = 0.262，P < 0.05）。从推断的宏基因组的功能分析表明，非吸烟女性肺癌患者的口腔微生物组与癌症途径，p53信号通路，细胞凋亡和结核病有关。结论：该研究确定了非吸烟女性肺癌患者不同的唾液微生物组特征，揭示了唾液微生物组与临床诊断中使用的免疫细胞化学标志物之间的潜在相关性，并证明唾液微生物群可以成为发现非侵入性肺癌生物标志物的信息来源。
Background: Association between oral bacteria and increased risk of lung cancer have been reported in several previous studies, however, the potential association between salivary microbiome and lung cancer in non-smoking women have not been evaluated. There is also no report on the relationship between immunocytochemistry markers and salivary microbiota. Method: In this study, we assessed the salivary microbiome of 75 non-smoking female lung cancer patients and 172 matched healthy individuals using 16S rRNA gene amplicon sequencing. We also calculated the Spearman's rank correlation coefficient between salivary microbiota and three immunohistochemical markers (TTF-1, Napsin A and CK7). Result: We analyzed the salivary microbiota of 247 subjects and found that non-smoking female lung cancer patients exhibited oral microbial dysbiosis. There was significantly lower microbial diversity and richness in lung cancer patients when compared to the control group (Shannon index, P < 0.01; Ace index, P < 0.0001). Based on the analysis of similarities, the composition of the microbiota in lung cancer patients also differed from that of the control group (r = 0.454, P < 0.001, unweighted UniFrac; r = 0.113, P < 0.01, weighted UniFrac). The bacterial genera Sphingomonas (P < 0.05) and Blastomonas (P < 0.0001) were relatively higher in non-smoking female lung cancer patients, whereas Acinetobacter (P < 0.001) and Streptococcus (P < 0.01) were higher in controls. Based on Spearman's correlation analysis, a significantly positive correlation can be observed between CK7 and Enterobacteriaceae (r = 0.223, P < 0.05). At the same time, Napsin A was positively associated with genera Blastomonas (r = 0.251, P < 0.05). TTF-1 exhibited a significantly positive correlation with Enterobacteriaceae (r = 0.262, P < 0.05). Functional analysis from inferred metagenomes indicated that oral microbiome in non-smoking female lung cancer patients were related to cancer pathways, p53 signaling pathway, apoptosis and tuberculosis. Conclusions: The study identified distinct salivary microbiome profiles in non-smoking female lung cancer patients, revealed potential correlations between salivary microbiome and immunocytochemistry markers used in clinical diagnostics, and provided proof that salivary microbiota can be an informative source for discovering non-invasive lung cancer biomarkers.