Caries-associated oral microbiome in head and neck cancer radiation patients: a longitudinal study

Jean-Luc C Mougeot, Craig B Stevens, Kathryn G Almon, Bruce J Paster, Rajesh V Lalla, Michael T Brennan, Farah Bahrani Mougeot, Jean-Luc C Mougeot, Craig B Stevens, Kathryn G Almon, Bruce J Paster, Rajesh V Lalla, Michael T Brennan, Farah Bahrani Mougeot

Abstract

Head and neck cancer (HNC) therapy often leads to caries development. Our goal was to characterize the oral microbiome of HNC patients who underwent radiation therapy (RT) at baseline (T0), and 6 (T6) and 18 (T18) months post-RT, and to determine if there was a relationship with increased caries. HOMINGS was used to determine the relative abundance (RA) of >600 bacterial species in oral samples of 31 HNC patients. The DMFS score was used to define patient groups with tooth decay increase (DMFS[+]) or no increase (DMFS[-]).A change in microbiome beta-diversity was observed at T6 and T18. The Streptococcus mutans RA increased at T6 in both DMFS[+] and DMFS[-] groups. The RA of Prevotella melaninogenica, the species often associated with caries in young children, decreased at T6 in the DMFS[-] group. The RA of the health-associated species, Abiotrophia defective, decreased in the DMFS[+] group. The oral microbiome underwent significant changes in radiation-treated HNC patients, whether they developed caries or not. Caries rates were not associated with a difference in salivary flow reduction between DMFS[+] andDMFS[-] groups. Patients who develop caries might be more susceptible to certain species associated with oral disease or have fewer potentially protective oral species.

Keywords: 16S rRNA; Head and neck cancer; caries; microbiome; next generation sequencing; radiation therapy.

Figures

Figure 1.
Figure 1.
Analytical design for the determination of oral microbiome beta-diversity changes in radiation-treated head and neck cancer patients. Comparisons of beta-diversity were carried out using transformed relative abundances (RA) or standardized RA fraction difference (RA-FD) to determine overall changes following radiation therapy (post-RT), changes occurring in clinically different subgroups, and changes characterizing DMFS[+] and DMFS[-] patients. Pts: HNC patients; T0: baseline time point prior to radiation therapy; Tx: T6 (6-months) or T18 (18-months) post-RT; AB: antibiotics; IC: Induction Chemotherapy; CC: Concurrent Chemotherapy. T0 to Tx corresponds to baseline to 6-months post-RT sampling (T0-T6), or baseline to 18-months post-RT sampling (T0-T18).
Figure 2.
Figure 2.
A significant oral microbiome profile shift occurs between T0 and T6 for all RT-treated HNC patients (a) and patients treated with RT and concurrent chemotherapy only (b). Timepoints: T0-pre-RT baseline sampling, T6-post-RT sampling at 6 months.
Figure 3.
Figure 3.
Non-metric multidimensional scaling (nMDS) of caries-associated species profiles of oral sites for all patients and patients who underwent concurrent chemotherapy (CC) T0 to Tx. a. T0-T6-All Patients (Subset-A; n = 28). b. T0-T18-All Patients (Subset-A; n = 20). c. T0-T6-Patients w/CC (Subset-D; n = 24). d. T0-T18-Patients w/CC (Subset-D; n = 19). A significant shift of caries-associated species profiles occurs between T0 to T6 (a, c), and T0 to T18 (b, d) for RT-treated HNC patients and for patients treated with RT and concurrent chemotherapy. T0 to Tx corresponds to baseline to 6-months post-RT sampling (T0-T6), or baseline to 18-months post-RT sampling (T0-T18).
Figure 4.
Figure 4.
Changes in relative abundance of caries- and health- associated species in DMFS[+] compared to DMFS[-] RT-treated HNC patients (Subset-D, all patients with CC). a. Caries-associated species. b. Health-associated species On the left of each chart, the T0 to T6 relative abundance (RA) change (Chg), i.e., T6 average RA minus T0 average RA by species is shown for the DMFS[+] and DMFS[-] groups of Subset-D, all HNC patients treated with RT and concurrent chemotherapy, for caries- (a) and health- (b) associated species. The difference in the group RA’s shown on the left, i.e., DMFS[+] average RA minus DMFS[-] average RA, by species is presented on the right of the charts. HOMINGS species probes identification 4-character codes are shown. A chi-squared test was used to determine the significance of differences in RA increases/decreases between the DMFS[+] and DMFS[-] groups. *p < 0.05; **p < 0.01; ***p < 0.001.

References

    1. Atlanta: U.S. Department of Health and Human Services CfDCaPaNCI. USA Cancer Statistics: 1999-2014 Incidence and Mortality Web-based Report. US Cancer Statistics Working Group; 2017,
    1. Fitzmaurice C, Allen C, Barber RM, et al. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 32 cancer groups, 1990 to 2015: A systematic analysis for the global burden of disease study. JAMA Oncol. 2017;3(4):524–13.
    1. Vigneswaran N, Williams MD.. Epidemiologic trends in head and neck cancer and aids in diagnosis. Oral Maxillofac Surg Clin North Am. 2014;26(2):123–141.
    1. Shaw R, Beasley N. Aetiology and risk factors for head and neck cancer: UK national multidisciplinary guidelines. J Laryngol Otol. 2016;130(S2):S9–S12.
    1. Chi AC, Day TA, Neville BW. Oral cavity and oropharyngeal squamous cell carcinoma–an update. CA Cancer J Clin. 2015;65(5):401–421.
    1. Buglione M, Cavagnini R, Di Rosario F, et al. Oral toxicity management in head and neck cancer patients treated with chemotherapy and radiation: dental pathologies and osteoradionecrosis (Part 1) literature review and consensus statement. Crit Rev Oncol Hematol. 2016;97:131–142.
    1. Buglione M, Cavagnini R, Di Rosario F, et al. Oral toxicity management in head and neck cancer patients treated with chemotherapy and radiation: xerostomia and trismus (Part 2). Literature review and consensus statement. Crit Rev Oncol Hematol. 2016;102:47–54.
    1. Tezal M, Scannapieco FA, Wactawski-Wende J, et al. Dental caries and head and neck cancers. JAMA Otolaryngol Head Neck Surg. 2013;139(10):1054–1060.
    1. Duarte VM, Liu YF, Rafizadeh S, et al. Comparison of dental health of patients with head and neck cancer receiving IMRT vs conventional radiation. Otolaryngol Head Neck Surg. 2014;150(1):81–86.
    1. Bueno AC, Ferreira RC, Barbosa FI, et al. Periodontal care in patients undergoing radiotherapy for head and neck cancer. Support Care Cancer. 2013;21(4):969–975.
    1. Ammajan RR, Joseph R, Rajeev R, et al. Assessment of periodontal changes in patients undergoing radiotherapy for head and neck malignancy: a hospital-based study. J Cancer Res Ther. 2013;9(4):630–637.
    1. Monroe AT, Flesher-Bratt D, Morris CG, et al. Prospectively-collected, tooth-specific dosimetry correlated with adverse dental outcomes. Oral Surg Oral Med Oral Pathol Oral Radiol. 2016;122(2):158–163.
    1. Hong CH, Napenas JJ, Hodgson BD, et al. A systematic review of dental disease in patients undergoing cancer therapy. Support Care Cancer. 2010;18(8):1007–1021.
    1. Gupta N, Pal M, Rawat S, et al. Radiation-induced dental caries, prevention and treatment - A systematic review. Natl J Maxillofac Surg. 2015;6(2):160–166.
    1. Featherstone JD. Dental caries: a dynamic disease process. Aust Dent J. 2008;53(3):286–291.
    1. Walker MP, Wichman B, Cheng AL, et al. Impact of radiotherapy dose on dentition breakdown in head and neck cancer patients. Pract Radiat Oncol. 2011;1(3):142–148.
    1. Schuurhuis JM, Stokman MA, Witjes MJ, et al. Head and neck intensity modulated radiation therapy leads to an increase of opportunistic oral pathogens. Oral Oncol. 2016;58:32–40.
    1. Galvao-Moreira LV, Da Cruz MC. Dental demineralization, radiation caries and oral microbiota in patients with head and neck cancer. Oral Oncol. 2015;51(12):e89–90.
    1. Schmidt BL, Kuczynski J, Bhattacharya A, et al. Changes in abundance of oral microbiota associated with oral cancer. PLoS One. 2014;9(6):e98741.
    1. Hu YJ, Shao ZY, Wang Q, et al. Exploring the dynamic core microbiome of plaque microbiota during head-and-neck radiotherapy using pyrosequencing. PLoS One. 2013;8(2):e56343.
    1. Zhang J, Liu H, Liang X, et al. Investigation of salivary function and oral microbiota of radiation caries-free people with nasopharyngeal carcinoma. PLoS One. 2015;10(4):e0123137.
    1. Gomes BP, Berber VB, Kokaras AS, et al. Microbiomes of endodontic-periodontal lesions before and after chemomechanical preparation. J Endod. 2015;41(12):1975–1984.
    1. Brennan MT, Treister NS, Sollecito TP, et al. Dental disease before radiotherapy in patients with head and neck cancer: clinical registry of dental outcomes in head and neck cancer patients. J Am Dent Assoc. 2017;148(12):868–877.
    1. Lalla RV, Treister N, Sollecito T, et al. Oral complications at 6 months after radiation therapy for head and neck cancer. Oral Dis. 2017;23(8):1134–1143.
    1. Lalla RV, Long-Simpson L, Hodges JS, et al. Clinical registry of dental outcomes in head and neck cancer patients (OraRad): rationale, methods, and recruitment considerations. BMC Oral Health. 2017;17(1):59.
    1. Bandyopadhyay D. From mouth-level to tooth-level DMFS: conceptualizing a theoretical framework. J Dent Oral Craniofac Epidemiol. 2013;1(1):3–8.
    1. Bahrani-Mougeot FK, Paster BJ, Coleman S, et al. Molecular analysis of oral and respiratory bacterial species associated with ventilator-associated pneumonia. J Clin Microbiol. 2007;45(5):1588–1593.
    1. Caporaso JG, Lauber CL, Walters WA, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci U S A. 2011;108(Suppl 1):4516–4522.
    1. Tanner AC, Kressirer CA, Faller LL. Understanding caries from the oral microbiome perspective. J Calif Dent Assoc. 2016;44(7):437–446.
    1. Kaul A, Mandal S, Davidov O, et al Analysis of microbiome data in the presence of excess zeros. Front Microbiol. 2017;8:2114.
    1. Chen L, Reeve J, Zhang L, et al. GMPR: A robust normalization method for zero-inflated count data with application to microbiome sequencing data. Peer J. 2018;6:e4600.
    1. R_Core_Team: R. A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2017.
    1. Ayyala DN, Lin S. GrammR: graphical representation and modeling of count data with application in metagenomics. Bioinformatics. 2015;31(10):1648–1654.
    1. Weiss S, Xu ZZ, Peddada S, et al. Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome. 2017;5(1):27.
    1. Dhariwal A, Chong J, Habib S, et al. MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Res. 2017;45(W1):W180–W188.
    1. Tanner AC, Mathney JM, Kent RL, et al. Cultivable anaerobic microbiota of severe early childhood caries. J Clin Microbiol. 2011;49(4):1464–1474.
    1. Agnello M, Marques J, Cen L, et al. Microbiome associated with severe caries in Canadian First Nations Children. J Dent Res. 2017;96(12):1378–1385.
    1. Agnello M, Marques J, Cen L, et al. Microbiome associated with severe caries in Canadian First Nations Children. American Dental Association - Symposium on Early Childhood Caries in American Indian and Alaska Native Children, 2016 Mar, Los Angeles, CA, USA.
    1. Colak H, Dulgergil CT, Dalli M, et al. Early childhood caries update: A review of causes, diagnoses, and treatments. J Nat Sci Biol Med. 2013;4(1):29–38.
    1. Starr JR, Huang Y, Lee KH, et al. Oral microbiota in youth with perinatally acquired HIV infection. Microbiome. 2018;6(1):100.
    1. Chen EZ, Li H. A two-part mixed-effects model for analyzing longitudinal microbiome compositional data. Bioinformatics. 2016;32(17):2611–2617.
    1. Costea PI, Munch R, Coelho LP, et al. metaSNV: A tool for metagenomic strain level analysis. PLoS One. 2017;12(7):e0182392.
    1. Albanese D, Donati C. Strain profiling and epidemiology of bacterial species from metagenomic sequencing. Nat Commun. 2017;8(1):2260.
    1. Lozupone CA. Unraveling interactions between the microbiome and the host iImmune system to decipher mechanisms of disease. mSystems. 2018;3:2.
    1. Nowicki EM, Shroff R, Singleton JA, et al. Microbiota and metatranscriptome changes accompanying the onset of gingivitis. MBio. 2018;9:2.
    1. Komatsuzawa H, Ouhara K, Kawai T, et al. Susceptibility of periodontopathogenic and cariogenic bacteria to defensins and potential therapeutic use of defensins in oral diseases. Curr Pharm. 2007;13(30):3084–3095.
    1. Simon-Soro A, Sherriff A, Sadique S, et al. Combined analysis of the salivary microbiome and host defence peptides predicts dental disease. Sci Rep. 2018;8(1):1484.

Source: PubMed

3
Abonnere