Article Text

Download PDFPDF
Original research
Variation in oral microbiome is associated with future risk of lung cancer among never-smokers
  1. H Dean Hosgood1,
  2. Qiuyin Cai2,
  3. Xing Hua3,
  4. Jirong Long2,
  5. Jianxin Shi3,
  6. Yunhu Wan3,
  7. Yaohua Yang2,
  8. Christian Abnet3,
  9. Bryan A Bassig3,
  10. Wei Hu3,
  11. Bu-Tian Ji3,
  12. Madelyn Klugman1,
  13. Yongbing Xiang4,
  14. Yu-Tang Gao4,
  15. Jason YY Wong3,
  16. Wei Zheng2,
  17. Nathaniel Rothman3,
  18. Xiao-Ou Shu2,
  19. Qing Lan3
  1. 1 Albert Einstein College of Medicine, Bronx, New York, USA
  2. 2 Vanderbilt University, Nashville, Tennessee, USA
  3. 3 National Cancer Institute, Bethesda, Maryland, USA
  4. 4 Shanghai Cancer Institute, Shanghai, China
  1. Correspondence to Dr H Dean Hosgood, Albert Einstein College of Medicine, Bronx, NY 10461, USA; dean.hosgood{at}


Objective To prospectively investigate whether diversity in oral microbiota is associated with risk of lung cancer among never-smokers.

Design and setting A nested case–control study within two prospective cohort studies, the Shanghai Women’s Health Study (n=74 941) and the Shanghai Men’s Health Study (n=61 480).

Participants Lifetime never-smokers who had no cancer at baseline. Cases were subjects who were diagnosed with incident lung cancer (n=114) and were matched 1:1 with controls on sex, age (≤2 years), date (≤30 days) and time (morning/afternoon) of sample collection, antibiotic use during the week before sample collection (yes/no) and menopausal status (for women).

Main outcomes and measures Metagenomic shotgun sequencing was used to measure the community structure and abundance of the oral microbiome in pre-diagnostic oral rinse samples of each case and control. Multivariable logistic regression models were used to estimate the association of lung cancer risk with alpha diversity metrics and relative abundance of taxa. The Microbiome Regression-Based Kernel Association Test (MiRKAT) evaluated the association between risk and the microbiome beta diversity.

Results Subjects with lower microbiota alpha diversity had an increased risk of lung cancer compared with those with higher microbial alpha diversity (Shannon: ptrend=0.05; Simpson: ptrend=0.04; Observed Species: ptrend=0.64). No case–control differences were apparent for beta diversity (pMiRKAT=0.30). After accounting for multiple comparisons, a greater abundance of Spirochaetia (ORlow 1.00 (reference), ORmedium 0.61 (95% CI 0.32 to 1.18), ORhigh 0.42 (95% CI 0.21 to 0.85)) and Bacteroidetes (ORlow 1.00 (reference), ORmedium 0.66 (95% CI 0.35 to 1.25), ORhigh 0.31 (95% CI 0.15 to 0.64)) was associated with a decreased risk of lung cancer, while a greater abundance of the Bacilli class (ORlow 1.00 (reference), ORmedium 1.49 (95% CI 0.73 to 3.08), ORhigh 2.40 (95% CI 1.18 to 4.87)) and Lactobacillales order (ORlow 1.00 (reference), ORmedium 2.15 (95% CI 1.03 to 4.47), ORhigh 3.26 (95% CI 1.58 to 6.70)) was associated with an increased risk of lung cancer.

Conclusions Our prospective study of never-smokers suggests that lower alpha diversity was associated with a greater risk of lung cancer and the abundance of certain specific taxa was associated with altered risk, providing further insight into the aetiology of lung cancer in the absence of active tobacco smoking.

  • lung cancer
  • non-small cell lung cancer

Statistics from

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.


  • HDH, QC and XH contributed equally.

  • NR, X-OS and QL contributed equally.

  • Contributors QL, QC, WZ, X-OS and NR conceived and designed the study. YX, Y-TG, YY and B-TJ performed sample collection and data harmonisation. XH, JL, JS and YW conducted the data analysis. HDH, QC, MK and QL drafted the initial manuscript. All authors contributed to the interpretation of the results and manuscript preparation.

  • Funding Part of this work was funded by UM1CA182910, UM1CA173640 and R01CA207466. Sample preparation was performed at the Survey and Biospecimen Shared Resource, which is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA068485). The microbiome data processing analyses were conducted using the Advanced Computing Center for Research and Education (ACCRE) at Vanderbilt University.

  • Disclaimer The funding sources had no involvement in the study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the article for publication. The researchers confirm independence from the funders and that authors had access to the data and can take responsibility for the integrity of the data and the accuracy of the data analysis.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available upon reasonable request. A limited dataset may be available upon reasonable request.

Linked Articles