Breast cancer in postmenopausal women is associated with an altered gut metagenome

Abstract

BackgroundIncreasing evidence suggests that gut microbiota play a role in the pathogenesis of breast cancer. The composition and functional capacity of gut microbiota associated with breast cancer have not been studied systematically.MethodsWe performed a comprehensive shotgun metagenomic analysis of 18 premenopausal breast cancer patients, 25 premenopausal healthy controls, 44 postmenopausal breast cancer patients, and 46 postmenopausal healthy controls.ResultsMicrobial diversity was higher in breast cancer patients than in controls. Relative species abundance in gut microbiota did not differ significantly between premenopausal breast cancer patients and premenopausal controls. In contrast, relative abundance of 45 species differed significantly between postmenopausal patients and postmenopausal controls: 38 species were enriched in postmenopausal patients, including Escherichia coli, Klebsiella sp_1_1_55, Prevotella amnii, Enterococcus gallinarum, Actinomyces sp. HPA0247, Shewanella putrefaciens, and Erwinia amylovora, and 7 species were less abundant in postmenopausal patients, including Eubacterium eligens and Lactobacillus vaginalis. Acinetobacter radioresistens and Enterococcus gallinarum were positively but weakly associated with expression of high-sensitivity C-reactive protein; Shewanella putrefaciens and Erwinia amylovora were positively but weakly associated with estradiol levels. Actinomyces sp. HPA0247 negatively but weakly correlated with CD3+CD8+ T cell numbers. Further characterization of metagenome functional capacity indicated that the gut metagenomes of postmenopausal breast cancer patients were enriched in genes encoding lipopolysaccharide biosynthesis, iron complex transport system, PTS system, secretion system, and beta-oxidation.ConclusionThe composition and functions of the gut microbial community differ between postmenopausal breast cancer patients and healthy controls. The gut microbiota may regulate or respond to host immunity and metabolic balance. Thus, while cause and effect cannot be determined, there is a reproducible change in the microbiota of treatment-naive patients relative to matched controls.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0515-3) contains supplementary material, which is available to authorized users.

Compositional and functional features of the female premenopausal and postmenopausal gut microbiota

“…We identified that the variance in the intestinal microbiome changed in the menopausal period, resulting in an obvious change in the gut microbial composition between premenopausal and postmenopausal women. Furthermore, Eubacterium eligens was reported to have reduced abundance in postmenopausal women with breast cancer , and a higher abundance in the Eubacterium rectale cluster stimulated by isoflavones had the ability to prevent women from developing menopause syndrome . Roseburia spp.…”

“…We identified that the variance in the intestinal microbiome changed in the menopausal period, resulting in an obvious change in the gut microbial composition between premenopausal and postmenopausal women. Furthermore, Eubacterium eligens was reported to have reduced abundance in postmenopausal women with breast cancer [16], and a higher abundance in the Eubacterium rectale cluster stimulated by isoflavones had the ability to prevent women from developing menopause syndrome [33]. Roseburia spp., commensal bacteria that have been demonstrated to produce short-chain fatty acids, and alteration in their abundance might affect numerous metabolic diseases [34], as they were less in postmenopausal women than in premenopausal women, which might be correlated with change of metabolism.…”

Fecal microbiota as a noninvasive biomarker to predict the tissue iron accumulation in intestine epithelial cells and liver

“…In a gut microbial study of patients with irritable bowel syndrome, based on machine learning and fivefold cross‐validation to reduce the complexity of sequencing data, gut microbial signature was used to distinguish healthy individuals and patients with different degrees of symptoms, using a LASSO regression model . Furthermore, gut microbial signature has also been used, in addition to cross‐validation and random forest analysis, to identify potential microbial biomarkers for early diagnosis of hepatocarcinoma and breast cancer . Obviously, robust statistical approaches could overcome the weakness of the difference on relative abundance between groups approach, and help identify key taxa.…”

“…37 Furthermore, gut microbial signature has also been used, in addition to cross-validation and random forest analysis, to identify potential microbial biomarkers for early diagnosis of hepatocarcinoma and breast cancer. 38,39 Obviously, robust statistical approaches could overcome the weakness of the difference on relative abundance between groups approach, and help identify key taxa. We incorporated relative abundance of bacterial species into machine learning models.…”

“…Several published studies have pointed out that key taxa may exist to support bacterial clustering. [36][37][38][39] To prove this hypothesis, machine learning approaches have been used widely in microbial studies. This could help identify signature microbiota, which could be utilized as diagnostic markers to predict progression of diseases, such as irritable bowel syndrome, 37 breast cancer, 39 and hepatocarcinoma.…”