Dataset Information

Endometrial microbiota from endometrial cancer and paired pericancer tissues in postmenopausal women: differences and clinical relevance.

ABSTRACT:

Objective

The incidence of postmenopausal endometrial cancer (EC) is rising, and the uterine microbiota has recently been suggested to be an etiology of EC. However, the differences in microbiota profiles in paired EC and the adjacent non-EC endometrium, and the functional microbiota of clinical relevance remain largely unknown. Therefore, we examined the differences in microbiota profiles between EC and non-EC endometrium and investigated their clinical relevance to EC.

Methods

Twenty-eight EC-affected postmenopausal women undergoing hysterectomy were enrolled. Endometrial microbiome from paired EC and adjacent non-EC tissue samples were detected using 16S rRNA sequencing, and the data were analyzed using R language software.

Results

The α diversity and evenness of the endometrial bacterial community significantly increased in EC tissues than those in pericancer tissues ( P < 0.05 for all variables). Lactobacillus and Gardnerella were the main bacterial genera present in both EC and adjacent non-EC-invading endometrium, whereas Prevotella , Atopobium , Anaerococcus , Dialister , Porphyromonas , and Peptoniphilus were more commonly enriched in the EC endometrium (corrected P < 0.05 for all variables). Finally, the abundance of some observed endometrial bacteria was associated with clinical aspects, particularly the vaginal pH, vaginal Lactobacillus abundance, and EC clinical stage.

Conclusions

Paired EC and adjacent non-EC endometrium harbor different endometrial microbiota, and the functional bacteria residing in the endometrium are clinically relevant but require further investigation.

SUBMITTER: Wang L

PROVIDER: S-EPMC9512232 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Publications

Endometrial microbiota from endometrial cancer and paired pericancer tissues in postmenopausal women: differences and clinical relevance.

Wang Lili L Yang Jiaolin J Su Huancheng H Shi Liuming L Chen Bangtao B Zhang Sanyuan S

Menopause (New York, N.Y.) 20220906 10

<h4>Objective</h4>The incidence of postmenopausal endometrial cancer (EC) is rising, and the uterine microbiota has recently been suggested to be an etiology of EC. However, the differences in microbiota profiles in paired EC and the adjacent non-EC endometrium, and the functional microbiota of clinical relevance remain largely unknown. Therefore, we examined the differences in microbiota profiles between EC and non-EC endometrium and investigated their clinical relevance to EC.<h4>Methods</h4>T ...[more]

PMID: 36150116

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Project description:BackgroundDisinfection byproducts (DBPs) and N-nitroso compounds (NOC), formed endogenously after nitrate ingestion, are suspected endometrial carcinogens, but epidemiological studies are limited.ObjectivesWe investigated the relationship of these exposures with endometrial cancer risk in a large prospective cohort.MethodsAmong postmenopausal women in the Iowa Women's Health Study cohort, we evaluated two major classes of DBPs, total trihalomethanes (TTHM) and five haloacetic acids (HAA5), and nitrate-nitrogen (NO3-N) in public water supplies (PWS) in relation to incident primary endometrial cancer (1986-2014). For women using their PWS >10y at enrollment (n=10,501; cases=261), we computed historical averages of annual concentrations; exposures were categorized into quantiles and when possible ≥95th percentile. We also computed years of PWS use above one-half the U.S. maximum contaminant level (>½ MCL; 40μg/L TTHM; 30μg/L HAA5; 5mg/L NO3-N). Dietary nitrate/nitrite intakes were estimated from a food frequency questionnaire. We estimated hazard ratios (HR) and 95% confidence intervals (CI) via Cox models adjusted for age, endometrial cancer risk factors [e.g., body mass index, hormone replacement therapy (HRT)], and mutually adjusted for DBPs or NO3-N. We evaluated associations for low-grade (cases=99) vs. high-grade (cases=114) type I tumors. We assessed interactions between exposures and endometrial cancer risk factors and dietary factors influencing NOC formation.ResultsHigher average concentrations of DBPs (95th percentile: TTHM ≥93μg/L, HAA5 ≥49μg/L) were associated with endometrial cancer risk (TTHM: HR95vsQ1=2.19, 95% CI: 1.41, 3.40; HAA5: HR95vsQ1=1.84, 95% CI: 1.19, 2.83; ptrend<0.01). Associations were similarly observed for women greater than median years of PWS use with levels >½ MCL, in comparison with zero years (TTHM: HR36+vs0y=1.61, 95% CI: 1.18, 2.21; HAA5: HR38+vs0y=1.85, 95% CI: 1.31, 2.62). Associations with DBPs appeared stronger for low-grade tumors (TTHM: HRQ4vsQ1=2.12, 95% CI: 1.17, 3.83; p-trend=0.008) than for high-grade tumors (TTHM: HRQ4vsQ1=1.40, 95% CI: 0.80, 2.44; p-trend=0.339), but differences were not statistically significant (p-heterogeneity=0.43). Associations with TTHM were stronger among ever HRT users than non-HRT users (p-interaction<0.01). We observed no associations with NO3-N in drinking water or diet.DiscussionWe report novel associations between the highest DBP levels and endometrial cancer for our Iowa cohort that warrant future evaluation. https://doi.org/10.1289/EHP10207.

Project description:ImportanceEndometrial carcinoma (EC) is the most commonly diagnosed gynecologic cancer. Its early detection is advisable because 20% of women have advanced disease at the time of diagnosis.ObjectiveTo clinically validate a metabolomics-based classification algorithm as a screening test for EC.Design, setting, and participantsThis diagnostic study enrolled 2 cohorts. A multicenter prospective cohort, with 50 cases (postmenopausal women with EC; International Federation of Gynecology and Obstetrics stage I-III and grade G1-G3) and 70 controls (no EC but matched on age, years from menopause, tobacco use, and comorbidities), was used to train multiple classification models. The accuracy of each trained model was then used as a statistical weight to produce an ensemble machine learning algorithm for testing, which was validated with a subsequent prospective cohort of 1430 postmenopausal women. The study was conducted at the San Giovanni di Dio e Ruggi d'Aragona University Hospital of Salerno (Italy) and Lega Italiana per la Lotta contro i Tumori clinic in Avellino (Italy). Data collection was conducted from January 2018 to February 2019, and analysis was conducted from January to March 2019.Main outcomes and measuresThe presence or absence of EC based on evaluation of the blood metabolome. Metabolites were extracted from dried blood samples from all participants and analyzed by gas chromatography-mass spectrometry. A confusion matrix was used to summarize test results. Performance indices included sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and accuracy. Confirmation or exclusion of EC in women with a positive test result was by means of hysteroscopy. Participants with negative results were followed up 1 year after enrollment to investigate the appearance of EC signs.ResultsThe study population consisted of 1550 postmenopausal women. The mean (SD) age was 68.2 (11.7) years for participants with no EC in the training cohort, 69.4 (13.8) years for women with EC in the training cohort, and 59.7 (7.7) years for women in the validation cohort. Application of the ensemble machine learning to the validation cohort resulted in 16 true-positives, 2 false-positives, and 0 false-negatives, and it correctly classified more than 99% of samples. Disease prevalence was 1.12% (16 of 1430).Conclusions and relevanceIn this study, dried blood metabolomic profile was used to assess the presence or absence of EC in postmenopausal women not receiving hormonal therapy with greater than 99% accuracy.

Dataset Information

Endometrial microbiota from endometrial cancer and paired pericancer tissues in postmenopausal women: differences and clinical relevance.

Objective

Methods

Results

Conclusions

Publications

Endometrial microbiota from endometrial cancer and paired pericancer tissues in postmenopausal women: differences and clinical relevance.

Similar Datasets

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