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Cited by 377Gut microbiota and healthOral microbiology and periodontitis researchCancer Risks and Factors

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

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Zhu, Jia, Liao, Ming, Yao, Ziting, Liang, Wenying, Li, Qibin, Liu, Jianlun, Yang, Huawei, Ji, Yinan, Wei, Wei, Tan, Aihua, Liang, Siyuan, Chen, Yang, Lin, Haisong, Zhu, Xiujuan, Huang, Shengzhu, Tian, Jiarong, Tang, Ruiqiang, Wang, Qiuyan, Mo, Zengnan·2018·Microbiome
DOI 10.1186/s40168-018-0515-3PMC PMC6080540
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Abstract

Increasing 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. We 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. Microbial 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. The 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.

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Fig. 1 Diversity of gut microbiota in breast cancer patients and healthy controls. a Total number of species in the four groups. b, c Alpha diversity of the four cohorts at species level, measured in terms of the Chao1 index and Shannon index. d Beta diversity of the four cohorts at species level. Each dot refers to a sample; if a sample has a high average JSD value, it indicates that the gut microbiota community structure of this sample is very different. Furthermore, if most samples of a group have high average JSD values, it indicates that the between-sample variability of the group is high. NS non-significant. *P < 0.05, **P < 0.01, ***P < 0.001
Fig. 1 Diversity of gut microbiota in breast cancer patients and healthy controls. a Total number of species in the four groups. b, c Alpha diversity of the four cohorts at species level, measured in terms of the Chao1 index and Shannon index. d Beta diversity of the four cohorts at species level. Each dot refers to a sample; if a sample has a high average JSD value, it indicates that the gut microbiota community structure of this sample is very different. Furthermore, if most samples of a group have high average JSD values, it indicates that the between-sample variability of the group is high. NS non-significant. *P < 0.05, **P < 0.01, ***P < 0.001CC BY · PubMed Central
Fig. 2 Relative abundance of the gut microbiota in the four groups at species level
Fig. 2 Relative abundance of the gut microbiota in the four groups at species levelCC BY · PubMed Central
Fig. 3 Relative abundance of 45 species differing significantly between postmenopausal breast cancer patients and postmenopausal healthy controls
Fig. 3 Relative abundance of 45 species differing significantly between postmenopausal breast cancer patients and postmenopausal healthy controlsCC BY · PubMed Central
Fig. 4 Classification to differentiate samples from postmenopausal breast cancer patients or postmenopausal healthy controls. a Probability of postmenopausal breast cancer in the training set. b ROC curves for the training set. The AUC was 87.25% (95% CI 79.82–94.68%). Classification of the test set consisted of 18 premenopausal breast cancer patients (red) and 25 premenopausal healthy controls (blue). c Classification of each sample. We used two cutoffs to assign the samples into three groups: 50% cases were classified into “Case” (probability of case > 50%), and 68% controls were classified into “Not case” (probability of case < 35%). Four cases and five controls stayed in “Uncertain.” d ROC for the test set. The AUC is 72% and the 95% CI is 56.01–88.44%
Fig. 4 Classification to differentiate samples from postmenopausal breast cancer patients or postmenopausal healthy controls. a Probability of postmenopausal breast cancer in the training set. b ROC curves for the training set. The AUC was 87.25% (95% CI 79.82–94.68%). Classification of the test set consisted of 18 premenopausal breast cancer patients (red) and 25 premenopausal healthy controls (blue). c Classification of each sample. We used two cutoffs to assign the samples into three groups: 50% cases were classified into “Case” (probability of case > 50%), and 68% controls were classified into “Not case” (probability of case < 35%). Four cases and five controls stayed in “Uncertain.” d ROC for the test set. The AUC is 72% and the 95% CI is 56.01–88.44%CC BY · PubMed Central
Fig. 5 Relative abundance of genes encoding virulence factors and pathogen-host interactions in postmenopausal breast cancer patients and postmenopausal controls. a Relative abundance of pathogen-host interaction genes in the two groups. b The top 15 representation of Pathogen-Host Interactions genes in the two groups and their implication in human diseases. c Relative abundance of virulence factor genes in the two groups. d Relative abundance of the top 15 virulence factor genes in the two groups
Fig. 5 Relative abundance of genes encoding virulence factors and pathogen-host interactions in postmenopausal breast cancer patients and postmenopausal controls. a Relative abundance of pathogen-host interaction genes in the two groups. b The top 15 representation of Pathogen-Host Interactions genes in the two groups and their implication in human diseases. c Relative abundance of virulence factor genes in the two groups. d Relative abundance of the top 15 virulence factor genes in the two groupsCC BY · PubMed Central
Fig. 6 Correlation between gut microbiota species and clinical indices of breast cancer. Spearman’s rank correlation coefficient is indicated using a color gradient: red indicates positive correlation; blue, negative correlation. *P < 0.05
Fig. 6 Correlation between gut microbiota species and clinical indices of breast cancer. Spearman’s rank correlation coefficient is indicated using a color gradient: red indicates positive correlation; blue, negative correlation. *P < 0.05CC BY · PubMed Central
Fig. 7 Functions of genes expressed in gut microbiota in pre- and postmenopausal breast cancer patients and healthy controls. a Gene functions in gut microbiota in premenopausal patients and controls; 26 KEGG modules were enriched in patients (red), and 18 were enriched in controls (blue). b Gene functions in gut microbiota in postmenopausal patients and controls; 43 KEGG modules were enriched in patients (blue)
Fig. 7 Functions of genes expressed in gut microbiota in pre- and postmenopausal breast cancer patients and healthy controls. a Gene functions in gut microbiota in premenopausal patients and controls; 26 KEGG modules were enriched in patients (red), and 18 were enriched in controls (blue). b Gene functions in gut microbiota in postmenopausal patients and controls; 43 KEGG modules were enriched in patients (blue)CC BY · PubMed Central

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Authors
Zhu, J., Liao, M., Yao, Z., Liang, W., Li, Q., Liu, J., Yang, H., Ji, Y., Wei, W., Tan, A., Liang, S., Chen, Y., Lin, H., Zhu, X., Huang, S., Tian, J., Tang, R., Wang, Q., & Mo, Z.
Affiliations
  • Guangxi Medical University (CN)
  • First Affiliated Hospital of GuangXi Medical University (CN)
Corresponding author
  • Wang, Qiuyan
  • Mo, Zengnan
ORCID
Venue
Microbiome
Publisher
Springer Science and Business Media LLC
Published
2018-08-06
Volume
6
Issue
1
Pages
136-136
ISSN
2049-2618 (ISSN-L)
DOI
10.1186/s40168-018-0515-3
PMC
PMC6080540
OpenAlex
W2885458712
Cited by
377
References
60
Citations by year
2026: 23 · 2025: 45 · 2024: 50 · 2023: 50 · 2022: 49 · 2021: 97 · 2020: 41 · 2019: 19 · 2018: 3
FWCI
14.23
Type
journal article
Language
en
Open access
Licence
Locations
  • Microbiome (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Guangxi Natural Science Foundation (2012GXNSFBA053117)
  • Guangxi Natural Science Fund for Innovation Research Team (2013GXNSFFA019002)
  • Guangxi Collaborative Innovation Center for genomic and personalized medicine (201319)
  • National Natural Science Foundation of China (81060169)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
  • Health Sciences › Medicine › Oncology › Cancer Risks and Factors
Keywords
breast cancer, postmenopausal women, gut microbiota, gut metagenome, microbial diversity, Escherichia coli, Enterococcus gallinarum, Shewanella putrefaciens, Erwinia amylovora, Actinomyces, C-reactive protein, estradiol, CD8+ T cells, lipopolysaccharide biosynthesis, iron transport, fatty acid beta-oxidation, host-microbe interactions
MeSH terms
Gastrointestinal Microbiome, Adult, Bacteria, Bacterial Proteins, Breast Neoplasms, C-Reactive Protein, Estradiol, Female, Humans, Middle Aged, Phylogeny, Case-Control Studies, Premenopause, Postmenopause, Gene Regulatory Networks, Metagenomics

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