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, 9 (1), 19213

Postmenopause as a Key Factor in the Composition of the Endometrial Cancer Microbiome (ECbiome)

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Postmenopause as a Key Factor in the Composition of the Endometrial Cancer Microbiome (ECbiome)

Dana M Walsh et al. Sci Rep.

Abstract

Incidence rates for endometrial cancer (EC) are rising, particularly in postmenopausal and obese women. Previously, we showed that the uterine and vaginal microbiome distinguishes patients with EC from those without. Here, we sought to examine the impact of patient factors (such as menopause status, body mass index, and vaginal pH) in the microbiome in the absence of EC and how these might contribute to the microbiome signature in EC. We find that each factor independently alters the microbiome and identified postmenopausal status as the main driver of a polymicrobial network associated with EC (ECbiome). We identified Porphyromas somerae presence as the most predictive microbial marker of EC and we confirm this using targeted qPCR, which could be of use in detecting EC in high-risk, asymptomatic women. Given the established pathogenic behavior of P. somerae and accompanying network in tissue infections and ulcers, future investigation into their role in EC is warranted.

Conflict of interest statement

The authors declare the following competing interests: The Mayo Foundation for Medical Education and Research (inventors Andrea Mariani, Nicholas Chia and Marina Walther-Antonio) applied for a patent application “Methods and Materials for Treating Endometrial Cancer”, US 2017/0260571 A1 (published September 14th, 2017). The use of Porphyrmonas somerae and accompanying microbiota as biomarkers for the detection of endometrial cancer is covered in the patent. Marina Walther-Antonio is a member of the scientific advisory board of LUCA Biologics, Inc. on research related to urinary tract infections, preterm birth, and reproductive medicine. These activities do not overlap with the research presented here.

Figures

Figure 1
Figure 1
Influence of patient factors on bacterial community diversity among patients without EC. Both α- (Shannon index) and β-diversity measures were compared. For α-diversity a Wald statistical test was performed. For β-diversity, omnibus p values are reported combining the evidence across the Bray-Curtis, unweighted, weighted, and generalized UniFrac distance metrics. The most significant metric is shown in each ordination plot. Lower tract (cervix and vagina). (A) Pre vs post-menopause α-diversity p = 0.002. (B) Pre vs post-menopause β-diversity unweighted UniFrac (omnibus p = 0.007), uterus. (C) Pre vs post-menopause α-diversity p = 0.024. (D) Pre vs post-menopause β-diversity weighted UniFrac (omnibus p = 0.221), lower tract. (E) Obese vs normal BMI α-diversity p = 0.019. (F) Obese vs normal BMI β-diversity unweighted UniFrac (omnibus p = 0.09), uterus. (G) Obese vs normal BMI α-diversity p = 0.47. (H) Obese vs normal BMI β-diversity unweighted UniFrac (omnibus p = 0.514), lower tract. (I) Normal vs high vaginal pH α-diversity p = 2.871E−5. (J) Normal vs high vaginal pH β-diversity generalized UniFrac (omnibus p = 0.001) and uterus. (K) Normal vs high vaginal pH α-diversity p = 0.112. (L) Normal vs high vaginal pH β-diversity weighted UniFrac (omnibus p = 0.062). Uterus premenopause N = 11, postmenopause N = 7; Lower tract premenopause N = 49, postmenopause N = 14. Uterus normal BMI N = 7, obese BMI N = 11; Lower tract normal BMI N = 38, obese BMI N = 26. Uterus normal pH N = 5 and high pH N = 13; Lower tract normal pH N = 24, high pH N = 39. For each primary comparison, the PERMANOVA tests were adjusted for the two remaining factors (menopause status, pH, obesity). *Groups are significantly different.
Figure 2
Figure 2
Specific bacterial OTUs differentially enriched among the lower tract of patients without EC by menopause status. (A) Proportion of OTUs significantly enriched among post-menopause patients. (B) Effect plot of the enriched OTUs. Differential abundance analysis was adjusted for vaginal pH and obesity. Wald statistical test with Q value cutoff = 0.1.
Figure 3
Figure 3
Bacterial community α- and β-diversity among patients with and without EC. Both α- (Shannon index) and β-diversity measures were compared. For α-diversity a Wald statistical test was performed. For β-diversity, omnibus p values are reported combining the evidence across the Bray-Curtis, unweighted, weighted, and generalized UniFrac distance metrics. The most significant metric is shown in each ordination plot. (A) Lower tract benign vs cancer, α-diversity p = 0.417, (B) lower tract benign vs cancer, β-diversity weighted UniFrac (omnibus p = 0.04), (C) Uterus benign vs cancer, α-diversity p = 0.168, (D) uterus benign vs cancer, β-diversity weighted UniFrac (omnibus p = 0.194). Uterus cancer = 16, benign = 18, lower tract cancer N = 54, benign N = 64. ANOVA and PERMANOVA tests were adjusted for menopause status, vaginal pH, and obesity. *p ≤ 0.05.
Figure 4
Figure 4
Significantly enriched taxa among patients with and without cancer. (A) Proportion of significantly enriched OTUs, (B) Effect size plot of enriched OTUs. Analysis was adjusted for pH, menopause status, and BMI. Benign N = 67, Cancer N = 57. Samples rarefied prior to analysis. Wald statistical test with Q value cutoff = 0.1.
Figure 5
Figure 5
Network depiction of significant associations between endometrial cancer and ECbiome (17 taxa associated with endometrial cancer). In this network, nodes represent OTUs and clinical covariates; edges link either (i) an OTU with its statistically-associated clinical factor, or (ii) correlated OTUs found using SparCC on the entire OTU compositional (i.e. relative abundances) table. Eight of the 17 ECbiome taxa are independently enriched by postmenopause, which is depicted in this figure to clarify relationships. The microbe most strongly associated with endometrial cancer (P. somerae) is not associated with postmenopause. Species-level annotation for each OTU was determined by identifying its phylogenetically closest bacterial genome using BLAST.
Figure 6
Figure 6
Significant enrichment of Porphyromonas somerae in endometrial cancer. Proportion of significantly enriched OTU28 (P. somerae) among cancer and benign patients. Benign N = 67, Cancer N = 57. Samples rarefied prior to analysis. Wald statistical test.
Figure 7
Figure 7
Predictive potential of Porphyromonas OTUs in endometrial cancer. (A) Receiver operator characteristic (ROC) curve for the ability of all Porphyromonas OTUs (Porph; AUC = 76.7%, 95% CI 67.9–85.5%), patient factors alone. (C) AUC = 84.4%, 95% CI 77.1–91.7%), and Porphyromonas OTUs and patient factors together (Porph + C; AUC = 88.6%, 95% CI 82.4–94.7%) to predict EC. Patient characteristics included in the ROC curve were patient age, BMI, menopause status, and vaginal pH. Benign N = 67, EC N = 57. (B) ROC curve for the ability of all Porphyromonas OTUs to predict EC in the high-risk post-menopausal and obese patients (AUC = 81.9%, 95% CI 64.2–99.5%). Benign N = 5, EC N = 35. Samples rarefied prior to analysis. CI = confidence intervals.
Figure 8
Figure 8
Significant detection of Porphyromonas somerae in endometrial cancer by qPCR. qPCR detection of P. somerae among vaginal swabs of patients with and without cancer. Benign N = 73, Endometrial Cancer N = 65. Samples rarefied prior to analysis.

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