Cervical intraepithelial neoplasia disease progression is associated with increased vaginal microbiome diversity

A Mitra, D A MacIntyre, Y S Lee, A Smith, J R Marchesi, B Lehne, R Bhatia, D Lyons, E Paraskevaidis, J V Li, E Holmes, J K Nicholson, P R Bennett, M Kyrgiou, A Mitra, D A MacIntyre, Y S Lee, A Smith, J R Marchesi, B Lehne, R Bhatia, D Lyons, E Paraskevaidis, J V Li, E Holmes, J K Nicholson, P R Bennett, M Kyrgiou

Abstract

Persistent infection with oncogenic Human Papillomavirus (HPV) is necessary for cervical carcinogenesis. Although evidence suggests that the vaginal microbiome plays a functional role in the persistence or regression of HPV infections, this has yet to be described in women with cervical intra-epithelial neoplasia (CIN). We hypothesised that increasing microbiome diversity is associated with increasing CIN severity. llumina MiSeq sequencing of 16S rRNA gene amplicons was used to characterise the vaginal microbiota of women with low-grade squamous intra-epithelial lesions (LSIL; n = 52), high-grade (HSIL; n = 92), invasive cervical cancer (ICC; n = 5) and healthy controls (n = 20). Hierarchical clustering analysis revealed an increased prevalence of microbiomes characterised by high-diversity and low levels of Lactobacillus spp. (community state type-CST IV) with increasing disease severity, irrespective of HPV status (Normal = 2/20,10%; LSIL = 11/52,21%; HSIL = 25/92,27%; ICC = 2/5,40%). Increasing disease severity was associated with decreasing relative abundance of Lactobacillus spp. The vaginal microbiome in HSIL was characterised by higher levels of Sneathia sanguinegens (P < 0.01), Anaerococcus tetradius (P < 0.05) and Peptostreptococcus anaerobius (P < 0.05) and lower levels of Lactobacillus jensenii (P < 0.01) compared to LSIL. Our results suggest advancing CIN disease severity is associated with increasing vaginal microbiota diversity and may be involved in regulating viral persistence and disease progression.

Figures

Figure 1. Bacterial species diversity in study…
Figure 1. Bacterial species diversity in study cohort and controls.
Principle component analysis (PCA) of vaginal bacterial species data identified 3 major clusters corresponding to samples dominated by three community state types (CSTs): L. iners (CST III), L. crispatus (CST I) and high diversity samples (CST IV). KEY - Cancer: Black; High-grade squamous intra-epithelial lesions (HSIL): Red; Low-grade squamous intra-epithelial lesions (LSIL): Yellow; Normal: Green.
Figure 2. Vaginal microbiome composition according to…
Figure 2. Vaginal microbiome composition according to disease and HPV status.
Hierarchical clustering analysis (HCA) using centroid clustering showed the distribution of CSTs differs in healthy, normal control women (green), compared to those with disease (Disease Severity I). Frequency of CST IV was 2-fold greater in women with LSIL (yellow), 3-fold greater in HSIL (red) and 4-fold greater in women with ICC (black), compared to controls, with a reciprocal decrease in frequency of CST I with increasing disease severity. When HPV/ASCUS (light grey) and LSIL (dark grey) were examined as two separate groups, the stepwise increase in CST IV prevalence was maintained (Disease Severity II). HPV positivity (blue) was associated with increased rates of CST IV, compared to HPV negative women (light grey) who were most likely to have CST I (HPV status). HPV-16 (pink) was most frequently associated with CST IV (HPV genotype). Rates of CST IV were similar in women with normal or LSIL regardless of HPV status (negative = light grey, positive = dark grey), and were substantially higher in women with HSIL and positive for HPV (blue) (Disease severity I & HPV status). DISEASE SEVERITY I - Normal: Green; Low-grade squamous intra-epithelial lesions (LSIL): Yellow; High-grade squamous intra-epithelial lesions (HSIL): Red; Cancer: Black. DISEASE SEVERITY II - Normal: white; ASCUS: light grey; LSIL: dark grey; HSIL: blue; Cancer: pink. HPV STATUS - HPV negative: light grey; HPV positive: blue; Unknown: white. HPV GENOTYPE - HPV negative: light grey; HPV16: pink; HPV18: blue; Other HR-HPV: dark grey; Unknown: white. DISEASE SEVERITY I & HPV STATUS - LSIL/Normal HPV negative: light grey; LSIL/Normal HPV positive: dark grey; HSIL/HPV positive: blue; Cancer: pink; unknown/other: white. KEY - ASCUS: atypical squamous cells of undetermined significance; CST: community state type; HPV: Human Papillomavirus; HR-HPV: high-risk HPV; HSIL: High-grade squamous intra-epithelial lesion; ICC: invasive cervical cancer; LSIL: Low-grade squamous intra-epithelial lesion.
Figure 3. Analysis of richness (A) and…
Figure 3. Analysis of richness (A) and diversity indices (B&C) with attributed CSTs for the patient cohort.
A significantly higher number of species observed in samples classified as CST IV (A) compared to CST I (P < 0.001) and CST III (P < 0.01). Diversity was also significantly higher in CST IV classified samples as assessed by the Inverse Simpson (B) and non-parametric Shannon (C) indices compared to CST I (P < 0.001) and CST III (P < 0.01). Kruskall-Wallis test (Dunn’s post hoc). KEY - CST: Community state type; Sobs: Species observed; ** = P < 0.01; *** = P < 0.001.
Figure 4. Vaginal microbiome richness and diversity…
Figure 4. Vaginal microbiome richness and diversity indices associated with disease status (normal, LSIL, HSIL and cervical cancer patients).
The number of species observed increased with disease severity with lowest richness observed in healthy controls and highest in HSIL and ICC (A). Diversity, as assessed by Inverse Simpson (B) and non-parametric Shannon (C) indices followed the same pattern. KEY - HSIL: High-grade squamous intra-epithelial lesion; ICC: invasive cervical cancer; LSIL: Low-grade squamous intra-epithelial lesion; Sobs: Species observed; ** = P < 0.01; *** = P < 0.001.
Figure 5. Identification of vaginal microbiota biomarkers…
Figure 5. Identification of vaginal microbiota biomarkers of LSIL vs. HSIL by LEfSe analysis.
(A) Cladogram representing taxa with different abundance according to disease severity. Size of circle is proportionate to abundance of taxon. (B) Histogram of the LDA scores computed for features differentially abundant between LSIL and HSIL disease states. Relative abundance counts of Anaerococcus tetradius (C), Peptostreptococcus anaerobis (D) and Sneathia sanguinegens (E), which were found to be significantly over-represented in HSIL whereas Lactobacillus jensenii (F) was enriched in LSIL samples (Welch’s t-test). KEY - HSIL: High-grade squamous intra-epithelial lesion; LDA score: Linear discriminant analysis score; LSIL: Low-grade squamous intra-epithelial lesion.

References

    1. Munoz N. Human papillomavirus and cancer: the epidemiological evidence. J. Clin. Virol. 19, 1–5 (2000).
    1. Myers E. R., McCrory D. C., Nanda K., Bastian L. & Matchar D. B. Mathematical model for the natural history of human papillomavirus infection and cervical carcinogenesis. Am. J. Epidemiol. 151, 1158–1171 (2000).
    1. Richardson H. et al.. The natural history of type-specific human papillomavirus infections in female university students. Cancer Epidemiol. Biomarkers Prev. 12, 485–490 (2003).
    1. Martin D. H. The microbiota of the vagina and its influence on women’s health and disease. Am. J. Med. Sci. 343, 2–9, doi: 10.1097/MAJ.0b013e31823ea228 (2012).
    1. Boskey E. R., Cone R. A., Whaley K. J. & Moench T. R. Origins of vaginal acidity: high D/L lactate ratio is consistent with bacteria being the primary source. Hum. Reprod. 16, 1809–1813 (2001).
    1. McMillan A. et al.. Disruption of urogenital biofilms by lactobacilli. Colloids Surf B Biointerfaces 86, 58–64, doi: 10.1016/j.colsurfb.2011.03.016 (2011).
    1. Boris S. & Barbes C. Role played by lactobacilli in controlling the population of vaginal pathogens. Microbes Infect 2, 543–546 (2000).
    1. Aroutcheva A. et al.. Defense factors of vaginal lactobacilli. Am. J. Obstet. Gynecol. 185, 375–379, doi: 10.1067/mob.2001.115867 (2001).
    1. Ocana V. S., Pesce De Ruiz Holgado A. A. & Nader-Macias M. E. Characterization of a bacteriocin-like substance produced by a vaginal Lactobacillus salivarius strain. Appl. Environ. Microbiol. 65, 5631–5635 (1999).
    1. Ravel J. et al.. Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci USA 108 Suppl 1, 4680–4687, doi: 10.1073/pnas.1002611107 (2011).
    1. Gajer P. et al.. Temporal dynamics of the human vaginal microbiota. Sci. Transl. Med. 4, 132ra152, doi: 10.1126/scitranslmed.3003605 (2012).
    1. MacIntyre D. A. et al.. The vaginal microbiome during pregnancy and the postpartum period in a European population. Sci. Rep. 5, 8988, doi: 10.1038/srep08988 (2015).
    1. Romero R. et al.. The composition and stability of the vaginal microbiota of normal pregnant women is different from that of non-pregnant women. Microbiome 2, 4, doi: 10.1186/2049-2618-2-4 (2014).
    1. Brotman R. M. et al.. Bacterial vaginosis assessed by gram stain and diminished colonization resistance to incident gonococcal, chlamydial, and trichomonal genital infection. J. Infect. Dis. 202, 1907–1915, doi: 10.1086/657320 (2010).
    1. Atashili J., Poole C., Ndumbe P. M., Adimora A. A. & Smith J. S. Bacterial vaginosis and HIV acquisition: a meta-analysis of published studies. AIDS 22, 1493–1501, doi: 10.1097/QAD.0b013e3283021a37 (2008).
    1. Racicot K. et al.. Viral infection of the pregnant cervix predisposes to ascending bacterial infection. J. Immunol. 191, 934–941, doi: 10.4049/jimmunol.1300661 (2013).
    1. Guo Y., You K., Qiao J., Zhao Y. & Geng L. Bacterial vaginosis is conducive to the persistence of HPV infection. Int. J. STD AIDS 23, 581–584 (2012).
    1. King C. C. et al.. Bacterial vaginosis and the natural history of human papillomavirus. Infect. Dis. Obstet. Gynecol. 2011, 319460, doi: 10.1155/2011/319460 (2011).
    1. Gillet E. et al.. Bacterial vaginosis is associated with uterine cervical human papillomavirus infection: a meta-analysis. BMC Infect. Dis. 11, 10, doi: 10.1186/1471-2334-11-10 (2011).
    1. Gillet E. et al.. Association between bacterial vaginosis and cervical intraepithelial neoplasia: systematic review and meta-analysis. PLoS One 7, e45201, doi: 10.1371/journal.pone.0045201 (2012).
    1. Lee J. E. et al.. Association of the vaginal microbiota with human papillomavirus infection in a Korean twin cohort. PLoS One 8, e63514, doi: 10.1371/journal.pone.0063514 (2013).
    1. Brotman R. M. et al.. Interplay Between the Temporal Dynamics of the Vaginal Microbiota and Human Papillomavirus Detection. J. Infect. Dis. doi: 10.1093/infdis/jiu330 (2014).
    1. Marchesi J. R. et al.. Towards the human colorectal cancer microbiome. PLoS One 6, e20447, doi: 10.1371/journal.pone.0020447 (2011).
    1. Kostic A. D. et al.. Fusobacterium nucleatum potentiates intestinal tumorigenesis and modulates the tumor-immune microenvironment. Cell Host Microbe 14, 207–215, doi: 10.1016/j.chom.2013.07.007 (2013).
    1. Kostic A. D. et al.. Genomic analysis identifies association of Fusobacterium with colorectal carcinoma. Genome Res. 22, 292–298, doi: 10.1101/gr.126573.111 (2012).
    1. Viaud S. et al.. The intestinal microbiota modulates the anticancer immune effects of cyclophosphamide. Science 342, 971–976, doi: 10.1126/science.1240537 (2013).
    1. Hillier S. L. & Lau R. J. Vaginal microflora in postmenopausal women who have not received estrogen replacement therapy. Clin. Infect. Dis. 25 Suppl 2, S123–126 (1997).
    1. Woodworth C. D. HPV innate immunity. Front. Biosci. 7, d2058–2071 (2002).
    1. Garcea G., Dennison A. R., Steward W. P. & Berry D. P. Role of inflammation in pancreatic carcinogenesis and the implications for future therapy. Pancreatology 5, 514–529, doi: 10.1159/000087493 (2005).
    1. Coussens L. M. & Werb Z. Inflammation and cancer. Nature 420, 860–867, doi: 10.1038/nature01322 (2002).
    1. Scott M., Stites D. P. & Moscicki A. B. Th1 cytokine patterns in cervical human papillomavirus infection. Clin. Diagn. Lab. Immunol. 6, 751–755 (1999).
    1. Klebanoff S. J. & Coombs R. W. Viricidal effect of Lactobacillus acidophilus on human immunodeficiency virus type 1: possible role in heterosexual transmission. J. Exp. Med. 174, 289–292 (1991).
    1. Klebanoff S. J., Hillier S. L., Eschenbach D. A. & Waltersdorph A. M. Control of the microbial flora of the vagina by H2O2-generating lactobacilli. J. Infect. Dis. 164, 94–100 (1991).
    1. Clark R. A. & Klebanoff S. J. Role of the myeloperoxidase-H2O2-halide system in concanavalin A-induced tumor cell killing by human neutrophils. J. Immunol. 122, 2605–2610 (1979).
    1. Motevaseli E. et al.. Normal and tumour cervical cells respond differently to vaginal lactobacilli, independent of pH and lactate. J. Med. Microbiol. 62, 1065–1072, doi: 10.1099/jmm.0.057521-0 (2013).
    1. Brotman R. M. et al.. Association between cigarette smoking and the vaginal microbiota: a pilot study. BMC Infect. Dis. 14, 471, doi: 10.1186/1471-2334-14-471 (2014).
    1. Kyrgiou M. et al.. Obstetric outcomes after conservative treatment for intraepithelial or early invasive cervical lesions: systematic review and meta-analysis. Lancet 367, 489–498, doi: 10.1016/S0140-6736(06)68181-6 (2006).
    1. Kyrgiou M. et al.. Fertility and early pregnancy outcomes after treatment for cervical intraepithelial neoplasia: systematic review and meta-analysis. BMJ 349, g6192, doi: 10.1136/bmj.g6192 (2014).
    1. Vujic G., Jajac Knez A., Despot Stefanovic V. & Kuzmic Vrbanovic V. Efficacy of orally applied probiotic capsules for bacterial vaginosis and other vaginal infections: a double-blind, randomized, placebo-controlled study. Eur. J. Obstet. Gynecol. Reprod. Biol. 168, 75–79, doi: 10.1016/j.ejogrb.2012.12.031 (2013).
    1. Hesselink A. T. et al.. Clinical validation of the Abbott RealTime High Risk HPV assay according to the guidelines for human papillomavirus DNA test requirements for cervical screening. J. Clin. Microbiol. 51, 2409–2410, doi: 10.1128/JCM.00633-13 (2013).
    1. Kozich J. J., Westcott S. L., Baxter N. T., Highlander S. K. & Schloss P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 79, 5112–5120, doi: 10.1128/AEM.01043-13 (2013).
    1. Wang Q., Garrity G. M., Tiedje J. M. & Cole J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267, doi: 10.1128/AEM.00062-07 (2007).
    1. Edgar R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461, doi: 10.1093/bioinformatics/btq461 (2010).
    1. Parks D. H. & Beiko R. G. Identifying biologically relevant differences between metagenomic communities. Bioinformatics 26, 715–721, doi: 10.1093/bioinformatics/btq041 (2010).

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