Abstract

Introduction

Lung cancer is considered a terminal illness, with a five-year survival rate of about 11% [1]. It is the most common cause of cancer-related deaths in North America and worldwide [2,3]. Tobacco smoking represents one of the main risk factors of lung cancer, since tobacco contains carcinogens that may induce cell transformation [4]. However, studies have also demonstrated that lung cancer involves immune responses [5], viral infections [6], and other factors that are not related to tobacco [6,7].

Recent studies have reported the identification of potential biomarkers in saliva, including oral bacteria, for cancer detection [8-13]. Particularly, salivary microbiota has been associated with oral squamous cell carcinoma and pancreatic ductal adenocarcinoma [12,13], suggesting that salivary microbiota may serve as an informative source for discovering non-invasive biomarkers of cancer diseases. Earlier studies have also shown serological evidence of an association between Chlamydia pneumoniae infection and lung cancer, and Chlamydia pneumoniae infection may serve as a biomarker for increased risk of lung cancer [14,15]. Most salivary bacteria are derived from the oral cavity, although some may also arise from the esophagus and the upper respiratory tract. Survival and growth of bacteria in the oral cavity are dependent on the oral environment, which can be affected by the composition of the sputum, and habits such as cigarette smoking. These factors are related to lung cancer occurrence and progression.

Based on these considerations, as well as previously reported involvement of bacteria in lung cancer tumorigenesis [14-16], we investigated the global variations of salivary microbiota in lung cancer patients. We quantified bacterial flora composition of saliva samples obtained from lung cancer patients and controls by sequencing V3 and V6 of 16S rDNA, using the Illumina HiSeq 2000 sequencer. This approach can identify more than 500 prevalent human bacterial species, with up to 100,000 bacterial sequences per sample. This high sensitivity and comprehensive analyses provide a new approach to investigating the relationship between lung cancer and bacterial composition.

Non-small cell lung cancer (NSCLC) accounts for more than 80% of lung cancer cases, most of which are either squamous cell carcinoma (SCC, ~30-35%) or adenocarcinoma (AC, ~50%). Therefore, we mainly enrolled patients with SCC or AC for the present study. To discover candidate bacterial biomarkers for SCC or AC, we performed the sequencing analysis of 10 samples from SCC patients, 10 samples from patients with AC and 10 samples from control subjects (n=30), and identified bacteria at the genus level that showed significant differences between both lung cancer groups and the control group. The results were subsequently confirmed using qPCR to quantify the relative abundance of bacteria. Finally, we further validated these potential bacterial biomarkers on new patient/control cohorts including a total of 41 lung cancer patients and 15 contro

Materials and methods

Results

Differential salivary microflora profiles between lung cancer and control subjects

Our deep sequencing analysis indicated that the abundance of salivary bacteria is different between lung cancer and control groups. This can be seen at all taxonomic levels (Figures 1, ​,22 and ​and3,3, Supplemental Figures 1, 2, 3 and 4). At the order-level, the most significantly altered ones included Flavobacteriales, Burkholderiales, Campylobacterales, Spirochaetales (more abundant in lung cancer) and Bacteroidales (less abundant in lung cancer) (Table 3). At the family-level, Veillonellaceae is significantly over-expressed whereas Lachnospiraceae is under-expressed in lung cancer patients (Table 4). More importantly, at the genus level, Capnocytophaga, Selenomonas, and Veillonella were found to be more abundant in both SCC and AC patients whereas Neisseria was less abundant in both SCC and AC patients than the controls (Table 5). On the other hand, the levels of Steptococcus, and Porphyromonas were only significantly lower in patients with SCC and Prevotella was not significantly changed in either cancer groups. All the sequencing results at different taxonomy levels (Phylums, Class, Order, Family and Genus) are shown in Supplemental Figures 1, 2, 3 and 4.

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Figure 1

Relative abundance for a partial list of salivary bacteria at the order level among SCC, AC and control groups (n=10 each group).

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Figure 2

Relative abundance for a partial list of saliva bacteria at the family level among SCC, AC and control groups (n=10 each group).

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Figure 3

Relative abundance for a partial list of saliva bacteria at the genus level among SCC, AC and control groups (n=10 each group).

Table 3

Relative abundance of a partial list of salivary bacteria at the order level between SCC and control groups or between AC and control groups based on sequencing analysis (n=10 per group)

Taxonomy/Order	Fold change (SCC vs CTRL)	P value (SCC vs CTRL)	Fold change (AC vs CTRL)	P value (AC vs CTRL)
Bacteroidales	0.63	0.03	0.52	0.006
Flavobacteriales	2.58	0.02	2.81	0.009
Fusobacteriales	1.1	0.39	0.79	0.19
Burkholderiales	9.01	0.02	4.76	0.03
Neisseriales	0.49	0.02	0.76	0.17
Campylobacterales	2.71	0.04	1.32	0.3
Pasteurellales	0.81	0.36	1.16	0.38
Spirochaetales	5.76	0.08	3.88	0.12
Clostridiales	2.41	0.0002	1.66	0.01

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Table 4

Relative abundance of a partial list of salivary bacteria at the family level between SCC and control groups or between AC and control groups based on sequencing analysis (n=10 per group)

Taxonomy/Family	Fold change (SCC vs CTRL)	P value (SCC vs CTRL)	Fold change (AC vs CTRL)	P value (AC vs CTRL)
Actinomycetaceae	0.45	0.08	0.38	0.04
Coriobacteriaceae	0.25	0.07	0.21	0.03
Flavobacteriaceae	1.96	0.11	2.4	0.01
Streptococcaceae	0.36	0.01	0.72	0.16
Lachnospiraceae	0.18	0.05	0.11	0.02
Veillonellaceae	2.46	0.006	1.8	0.02

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Table 5

Relative abundance of a partial list of salivary bacteria at the genus level between SCC and control groups or between AC and control groups based on sequencing analysis (n=10 per group)

Taxonomy/Genus	Fold change (SCC vs CTRL)	P value (SCC vs CTRL)	Fold change (AC vs CTRL)	P value (AC vs CTRL)
Porphyromonas	0.24	0.005	0.46	0.1
Prevotella	0.74	0.2	0.63	0.08
Capnocytophaga	2.22	0.04	2.42	0.03
Neisseria	0.44	0.009	0.63	0.04
Streptococcus	0.36	0.007	0.72	0.16
Selenomonas	34.7	0.01	10.15	0.04
Veillonella	2.24	0.008	1.85	0.02

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qPCR verification of the candidate bacterial biomarkers

To verify the finding from sequencing analysis, we used qPCR to quantify the levels of the identified bacteria genera in the same cancer and control subjects used for sequencing analysis. A common primer pair that can amplify most bacterial 16S rDNA was used for qPCR and subsequently the qPCR results based on the common primer pair were used to normalize the levels of individual bacterial rDNA in each control and cancer samples (Table 2). qPCR analysis showed significantly (p<0.05) higher levels of Capnocytophaga and Veillonella but lower levels of Neisseria in cancer samples than the control samples (Figure 4, Table 6). This confirms the sequencing analysis results and supports the feasibility of using qPCR to quantify the levels of selected bacterial clusters. Due to its very low level, Selenomonas was not detectable by qPCR in some of saliva samples, so it was not included in subsequent qPCR validation studies on independent patient populations. We also verified the alterations of Bacteroidales in SCC and AC patients with qPCR, and the results were similar to those obtained from the deep sequencing analysis (Figure 4, Table 6).

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Figure 4

Verification of three potential biomarkers, Capnocytophaga, Veillonella, and Neisseria, as well as Bacteroidales by qPCR of 16S rDNA (n=10 each group).

Table 6

qPCR verification of three potential salivary bacterial biomarkers, Capnocytophaga, Veillonella, and Neisseria, as well as bacteroidales between lung cancer and control groups (n=10 per group)

	Fold change (SCC vs CTRL)	P value (SCC vs CTRL)	Fold change (AC vs CTRL)	P value (AC vs CTRL)
Neisseria	0.4	0.004	0.55	0.04
Capnocytophaga	3.18	0.04	3.78	0.04
Veillonella	2.94	0.00006	2.39	0.0003
Bacteroidales	0.69	0.09	0.6	0.03

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Validation of potential bacterial biomarkers in new patient cohorts

To validate the three potential bacterial markers (Neisseria, Capnocytophaga and Veillonella), we used qPCR to quantify their levels in a new patient/control cohort, including 41 cancers (13 SCC, 28 AC) and 15 controls. The qPCR results indicated that the levels of Capnocytophaga and Veillonella were significantly higher in both SCC and AC groups, consistent with our qPCR verification analysis of previous 30 samples (Figure 5). However, the validation result of Neisseria was not as promising as those found in the qPCR verification study. Although the levels of Neisseria in the AC patients were significantly lower (p=0.009) than those in the controls, the comparison of SCC with control groups did not show significance difference.

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Figure 5

Validation of three potential saliva bacterial biomarkers on a new patient/control cohort (n=13 for SCC, n=28 for AC and n=15 for control).

As shown in Figure 6, the ROC analysis was performed to evaluate pre-clinical utility of these potential biomarkers and to assess if combining biomarkers may improve the sensitivity and specificity. The overall performance of the three potential biomarkers in detecting SCC and AC is summarized in Table 7. The ROC values of Veillonella were determined to be 0.81 for SCC and 0.68 for AC, and the ROC values of Capnocytophaga were 0.79 for SCC and 0.81 for AC. ROC value or sensitivity can be improved by combining Veillonella with Capnocytophaga. However, the ROC values significantly decreased when adding the third potential biomarker, Neisseria, for both SCC and AC.

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Figure 6

Receiver operating characteristic (ROC) analysis of the three potential biomarkers (Capnocytophaga, Veillonella, and Neisseria) based on the validation data. The combination of Capnocytophaga with Veillonella (but not Neisseria) improved the ROC value or sensitivity.

Table 7

Performance of salivary bacterial markers for SCC or AC

	p value (SCC vs CTRL)	p value (AC vs CTRL)	ROC value (SCC vs CTRL)	Cut-off (SCC vs CTRL)	Sensitivity (SCC vs CTRL)	Specificity (SCC vs CTRL)	ROC value (AC vs CTRL)	Cut-off (AC vs CTRL)	Sensitivity (AC vs CTRL)	Specificity (AC vs CTRL)
Neisseria	0.260	0.009	0.62	≤1.5%	30.80%	100%	0.78	≤2.1%	57.10%	93.30%
Capnocytophaga	0.020	0.004	0.79	≥0.1%	92.30%	53.30%	0.81	≥0.7%	71.40%	80.00%
Veillonella	0.003	0.030	0.81	≥7.1%	76.90%	86.70%	0.68	≥8.3%	42.90%	93.30%
Capnocytophaga + Veillonella	-	-	0.86	-	84.60%	86.70%	0.80	-	78.60%	80.00%
Capnocytophaga + Veillonella + Neisseria	-	-	0.68	-	53.80%	86.70%	0.54	-	35.70%	86.70%

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Discussion

Our intensive sequencing analysis demonstrated that the salivary microbiota profiles are significant altered in the patients with lung cancer when compared to those from control subjects. Detailed analysis of the deep sequencing results showed that the abundance of salivary bacteria varied between lung cancer and control groups at multiple taxonomic levels. Particularly, at the genus-level, Capnocytophaga, Selenomonas, and Veillonella were found to be more abundant in both SCC and AC patients whereas Neisseria was less abundant in both SCC and AC patients than the controls (Table 5). In addition, the abundance of Steptococcus, and Porphyromonas were both significantly lower in patients with SCC. Based on these results, we performed qPCR verification of Capnocytophaga, Selenomonas, Veillonella, and Neisseria in the same group of SCC and AC patients used for deep sequencing analysis and further validated the significant changes of Capnocytophaga, Veillonella and Neisseria in an independent patient/control cohort.

Based on ROC analysis, Veillonella and Capnocytophaga are more valuable biomarkers than Neisseria because they exhibit higher sensitivity/specificity and their levels are significantly higher in both cancer types than the control subjects (instead of being lower in cancer groups). In fact, if we combine Veillonella with Capnocytophaga, the ROC value reached 0.86 for SCC with a sensitivity of 84.6% and a specificity of 86.7%. Although the ROC value (0.80) became slightly lower than Capnocytophaga itself when combining these two biomarkers for AC, the sensitivity was improved (78.6%) and specificity reached 80%.

The intrinsic relationship between salivary microbiota and lung cancer is currently under investigation. Indeed, previous studies have provided critical insights on how bacteria may be related to abnormal growth of mammalian cells. Bacterium-produced toxins can disturb the cell cycle, resulting in altered cell growth [15,24,25]. This is caused by alterations to the genes that control normal cell division and apoptosis [26,27]. It is well known that gut microbiota is involved in the pathogenesis of inflammatory bowel disease due to the disruption of immune tolerance [28]. Similarly, salivary microbiota may also affect lung cells by inducing long-term immune response.

In our study, although more research is needed to establish the relationship of Neisseria, Steptococcus, and Porphyromonas to lung cancer, our findings clearly show that there is significant association of salivary Capnocytophaga and Veillonella with lung cancer (both SCC and AC). In fact, there have been increasing interests in studying the link between oral bacteria and respiratory infection [29-33]. An association between oral conditions such as periodontal disease and several respiratory conditions has been reported previously [33]. Oral periodontopathic bacteria can be aspirated into the lung to cause aspiration pneumonia. The teeth may also serve as a reservoir for respiratory pathogen colonization and subsequent nosocomial pneumonia. Once established in the mouth, these pathogens may cause lung infection with the following possible mechanisms: 1. aspiration of oral pathogens into the lung to cause infection; 2. periodontal disease-associated enzymes in saliva may modify mucosal surfaces to promote adhesion and colonization by respiratory pathogens, which are then aspirated into the lung; 3. periodontal disease-associated enzymes may destroy salivary pellicles on pathogenic bacteria to hinder their clearance from the mucosal surface; and 4. cytokines originating from periodontal tissues may alter respiratory epithelium to promote infection by respiratory pathogens [33]. In patients with Cystic fibrosis (CF), there is a high prevalence of oropharyngeal anaerobic bacteria in sputum. Recently, Rivas Caldas et al. demonstrated that the same Pseudomonas aeruginosa clonal types were present in both saliva and sputum samples of CF patients. This suggest that the oral cavity is a possible reservoir for lung infection [32]. Haemophilus pittmaniae (H. pittmaniae), a member of the human saliva microbiota, was identified by mass spectrometry and 16S rRNA gene sequencing in the sputum specimen collected from a patient with a massive fibrotic form of siderosis. H. pittmaniae was found to be responsible for the worsening of the patient’s chronic respiratory failure, and the patient’s condition rapidly improved when he was treated with oral amoxicillin, an antibiotic therapy guided by the in vitro susceptibility pattern of the H. pittmaniae isolate. These results suggest that H. pittmaniae is a possible new pathogen responsible for respiratory tract infection in patients with chronic lung diseases [30]. In addition, post-operative pulmonary infection often appears to result from aspiration of pathogens colonizing the oral cavity. In order to investigate if impaired periodontal status and pathogenic oral bacteria significantly contribute to development of aspiration pneumonia following neurosurgical operations, Bagyi et al. compared a matched cohort of 18 patients without postoperative lung complications to a cohort of 5 patients who developed pneumonia within 48 hours after brain surgery. They found that the number and severity of coexisting periodontal diseases were significantly greater in patients with postoperative pneumonia in comparison to the control group. Therefore, dental examination of the salivary microbiota may be needed in order to identify patients at high risk of developing postoperative respiratory infections [29].

Although Capnocytophaga and Veillonella are significantly associated with both SCC and AC, Veillonella appears to be a better biomarker for SCC whereas Capnocytophaga serves as a better biomarker for AC (Table 7). Veillonella was previously isolated from the lower airways of lung cancer patients, suggesting that Veillonella species may be related to lung cancer [34]. Normally found in the oropharyngeal tract, Capnocytophaga species have been reported to be involved in lung cancer, as they have been shown to be involved in the formation of lung abscesses [35] and lower respiratory tract infections [36]. These findings, including ours, seem to suggest that either these bacteria induce long-term immune response/infection to the organ or cancer growth environment favors the growth of these bacteria in the airway or oropharyngeal tracts. As discussed earlier, Neisseria was found at significantly lower levels in both SCC and AC patients than control subjects. It should be noted that similar results were also reported in pancreatic cancer saliva samples [12], suggesting that Neisseria may be related to inhibited growth of cancer cells.

As a summary, our studies have provided insights on the potential role of oral cavity as a reservoir of bacterial pathogens in lung cancer, and the discovery of potential bacterial biomarkers may lead to a non-invasive method for helping detect/classify the disease. Nevertheless, the exact role of these salivary bacteria in lung cancer occurrence and progression is largely unknown and certainly warrants further investigation.

Acknowledgements

References