Dysbiosis of the Salivary Microbiome Is Associated With Non-smoking Female Lung Cancer and Correlated With Immunocytochemistry Markers

Abstract

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.

The salivary microbiota in health and disease

“…Finally, two cross-sectional studies have compared SM in patients with lung cancer to healthy controls. The main findings were higher levels of Streptococcus and Veillonella species in saliva from patients with non-small cell lung cancer [85], and lower salivary levels of Streptococcus species in combination with low bacterial diversity in female non-smokers with lung cancer as compared to matched healthy controls [86].…”

The Influence of Lung Microbiota on Lung Carcinogenesis, Immunity, and Immunotherapy

“…Thus, the principles of respiratory microbiology are being studied again, starting with the lung sterility myth [10]. For example, the association between oral microbiota and risk of lung cancer has been reported [11]. Lung cancer is currently one of the most common causes of cancer death worldwide in both men and women.…”

Salivary biomarkers for diagnosis of systemic diseases and malignant tumors. A systematic review

“…All the reported molecules showed a good statistical association with diagnosis of lung carcinomas at different stages of developement. The "good" quality studies on salivary biomarkers and lung cancer are those demonstrating an association with EGFR, the 5 mRNA, microbiota and cytokines (8)(9)(10)(11) (45). Similarly, pancreatic carcinoma is insidious, very aggressive and in most cases diagnosed at a very late stage, being associated to a very poor prognosis (46).…”

“…Molecules most frequently investigated were proteins and RNA. Twelve studies (23.5%) were scored as "good" and 11 of these reported statistically significant associations between molecules searched and pathology (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17).…”