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Cited by 631Gut microbiota and healthOral microbiology and periodontitis researchReproductive tract infections research

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The Microbiota of Breast Tissue and Its Association with Breast Cancer

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Urbaniak, Camilla, Gloor, Gregory B., Brackstone, Muriel, Scott, Leslie, Tangney, Mark, Reid, Gregor·2016·Applied and Environmental Microbiology
DOI 10.1128/aem.01235-16PMC PMC4968547
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Abstract

UNLABELLED: In the United States, 1 in 8 women will be diagnosed with breast cancer in her lifetime. Along with genetics, the environment contributes to disease development, but what these exact environmental factors are remains unknown. We have previously shown that breast tissue is not sterile but contains a diverse population of bacteria. We thus believe that the host's local microbiome could be modulating the risk of breast cancer development. Using 16S rRNA amplicon sequencing, we show that bacterial profiles differ between normal adjacent tissue from women with breast cancer and tissue from healthy controls. Women with breast cancer had higher relative abundances of Bacillus, Enterobacteriaceae and Staphylococcus Escherichia coli (a member of the Enterobacteriaceae family) and Staphylococcus epidermidis, isolated from breast cancer patients, were shown to induce DNA double-stranded breaks in HeLa cells using the histone-2AX (H2AX) phosphorylation (γ-H2AX) assay. We also found that microbial profiles are similar between normal adjacent tissue and tissue sampled directly from the tumor. This study raises important questions as to what role the breast microbiome plays in disease development or progression and how we can manipulate this for possible therapeutics or prevention. IMPORTANCE: This study shows that different bacterial profiles in breast tissue exist between healthy women and those with breast cancer. Higher relative abundances of bacteria that had the ability to cause DNA damage in vitro were detected in breast cancer patients, as was a decrease in some lactic acid bacteria, known for their beneficial health effects, including anticarcinogenic properties. This study raises important questions as to the role of the mammary microbiome in modulating the risk of breast cancer development.

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FIG 1 Breast tissue microbiota in 43 Canadian women identified by 16S rRNA amplicon sequencing. (A) The relative abundances of bacterial genera in different breast tissue samples were visualized by bar plots. Each bar represents a subject and each colored box, a bacterial taxon. The height of a colored box represents the relative abundance of that organism within the sample. Taxa present at less than 2% abundance in a given sample are displayed in the remaining fraction section at the top of the graph (gray boxes). As shown by the bar plots, a variety of bacteria was detected in breast tissue. The legend is read from bottom to top, with the bottom organism on the legend corresponding to the bottom colored box on the bar plot. (B) Box plots of the six phyla identified in breast tissue. The box signifies the 75% (upper) and 25% (lower) quartiles and thus shows where 50% of the samples lie. The black line inside the box represents the median. The whiskers represent the lowest datum still within 1.5 interquartile range (IQR) of the lower quartile and the highest datum still within 1.5 IQR of the upper quartile. Outliers are shown with open circles.
FIG 1 Breast tissue microbiota in 43 Canadian women identified by 16S rRNA amplicon sequencing. (A) The relative abundances of bacterial genera in different breast tissue samples were visualized by bar plots. Each bar represents a subject and each colored box, a bacterial taxon. The height of a colored box represents the relative abundance of that organism within the sample. Taxa present at less than 2% abundance in a given sample are displayed in the remaining fraction section at the top of the graph (gray boxes). As shown by the bar plots, a variety of bacteria was detected in breast tissue. The legend is read from bottom to top, with the bottom organism on the legend corresponding to the bottom colored box on the bar plot. (B) Box plots of the six phyla identified in breast tissue. The box signifies the 75% (upper) and 25% (lower) quartiles and thus shows where 50% of the samples lie. The black line inside the box represents the median. The whiskers represent the lowest datum still within 1.5 interquartile range (IQR) of the lower quartile and the highest datum still within 1.5 IQR of the upper quartile. Outliers are shown with open circles.CC BY · PubMed Central
FIG 2 Comparison of bacterial profiles between breast cancer patients and healthy controls. Weighted UniFrac principal-coordinate (PCoA) plot (A) and K-means clusterplot of centered log ratio-transformed data (B). Each breast tissue sample, represented by a colored point, was plotted on a 3-dimensional, 3-axis plane representing 79% of the variation observed between all samples (A) or 44.85% of the variation on a 2-axis plane (B). Samples (points) that cluster together are similar in biota composition and abundance. The distinct separation between the two groups indicates that bacterial profiles differ between women with and without cancer. The PERMANOVA performed on the weighted UniFrac distances showed that the observed differences were statistically significant (10,000 permutations; pseudo F statistic, 14.4; P < 0.01).
FIG 2 Comparison of bacterial profiles between breast cancer patients and healthy controls. Weighted UniFrac principal-coordinate (PCoA) plot (A) and K-means clusterplot of centered log ratio-transformed data (B). Each breast tissue sample, represented by a colored point, was plotted on a 3-dimensional, 3-axis plane representing 79% of the variation observed between all samples (A) or 44.85% of the variation on a 2-axis plane (B). Samples (points) that cluster together are similar in biota composition and abundance. The distinct separation between the two groups indicates that bacterial profiles differ between women with and without cancer. The PERMANOVA performed on the weighted UniFrac distances showed that the observed differences were statistically significant (10,000 permutations; pseudo F statistic, 14.4; P < 0.01).CC BY · PubMed Central
FIG 3 Differences in relative abundances of taxa exist between healthy and cancer patients. The top panels show the bacteria that had statistically significant higher relative abundances in healthy patients than in those with cancer (i.e., normal adjacent tissue), and the bottom panels shows the bacteria that had statistically significant higher relative abundances in cancer patients than in healthy controls. The box in each graph signifies the 75% (upper) and 25% (lower) quartiles and thus shows where 50% of the samples lie. The black line inside the box represents the median. The whiskers represent the lowest datum still within 1.5 interquartile range (IQR) of the lower quartile and the highest datum still within 1.5 IQR of the upper quartile. Outliers are shown with open circles. Significance was based on the Benjamini-Hochberg corrected P value of the Wilcoxon rank test (significance threshold, P < 0.1).
FIG 3 Differences in relative abundances of taxa exist between healthy and cancer patients. The top panels show the bacteria that had statistically significant higher relative abundances in healthy patients than in those with cancer (i.e., normal adjacent tissue), and the bottom panels shows the bacteria that had statistically significant higher relative abundances in cancer patients than in healthy controls. The box in each graph signifies the 75% (upper) and 25% (lower) quartiles and thus shows where 50% of the samples lie. The black line inside the box represents the median. The whiskers represent the lowest datum still within 1.5 interquartile range (IQR) of the lower quartile and the highest datum still within 1.5 IQR of the upper quartile. Outliers are shown with open circles. Significance was based on the Benjamini-Hochberg corrected P value of the Wilcoxon rank test (significance threshold, P < 0.1).CC BY · PubMed Central
FIG 4 DNA damage ability of E. coli isolated from breast cancer patients. E. coli was isolated from normal adjacent tissue of 2 patients with breast cancer and tested for its ability to induce DNA double-stranded breaks. E. coli (isolates H and E) from subject 41, isolate L from subject 34, and strain IHE3034 were incubated with HeLa cells at an MOI of 100 for 4 h and then stained for γ-H2AX and DAPI. Etoposide, a chemical that induces DNA double-stranded breaks in eukaryotic cells, was used as a technical positive control. (A) Representative immunofluorescent images of HeLa cells at ×1,000 magnification. (B) Image J was used to measure the mean fluorescent intensity of γ-H2AX-positive cells from the digitally acquired images. (C) Percentages of total cells stained for γ-H2AX calculated from the immunofluorescent images. Data displayed in the bar graphs represent the mean and standard deviation of results from 3 experiments, representing a total of 48 fields of view and approximately 300 cells for each treatment group. **, P < 0.01.
FIG 4 DNA damage ability of E. coli isolated from breast cancer patients. E. coli was isolated from normal adjacent tissue of 2 patients with breast cancer and tested for its ability to induce DNA double-stranded breaks. E. coli (isolates H and E) from subject 41, isolate L from subject 34, and strain IHE3034 were incubated with HeLa cells at an MOI of 100 for 4 h and then stained for γ-H2AX and DAPI. Etoposide, a chemical that induces DNA double-stranded breaks in eukaryotic cells, was used as a technical positive control. (A) Representative immunofluorescent images of HeLa cells at ×1,000 magnification. (B) Image J was used to measure the mean fluorescent intensity of γ-H2AX-positive cells from the digitally acquired images. (C) Percentages of total cells stained for γ-H2AX calculated from the immunofluorescent images. Data displayed in the bar graphs represent the mean and standard deviation of results from 3 experiments, representing a total of 48 fields of view and approximately 300 cells for each treatment group. **, P < 0.01.CC BY · PubMed Central

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Metadata

Authors
Urbaniak, C., Gloor, G. B., Brackstone, M., Scott, L., Tangney, M., & Reid, G.
Affiliations
  • Western University (CA)
  • London Regional Cancer Program, London, Ontario, Canada
  • University College Cork (IE)
Corresponding author
Reid, Gregor
ORCID
Venue
Applied and Environmental Microbiology
Publisher
American Society for Microbiology
Published
2016-08-15
Volume
82
Issue
16
Pages
5039-5048
ISSN
  • 0099-2240 (ISSN-L)
  • 1098-5336
DOI
10.1128/aem.01235-16
PMC
PMC4968547
OpenAlex
W2493607481
Cited by
625
References
53
Citations by year
2026: 51 · 2025: 102 · 2024: 75 · 2023: 82 · 2022: 68 · 2021: 88 · 2020: 63 · 2019: 41 · 2018: 29 · 2017: 19 · 2016: 5
FWCI
16.29
Type
journal article
Language
en
Open access
Licence
Locations
  • Applied and Environmental Microbiology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Arrow@dit (Dublin Institute of Technology) (submittedVersion, cc-by)
  • Cork Open Research Archive (University College Cork, Ireland) (submittedVersion, cc-by)
  • Scholarship@Western (Western University) (submittedVersion)
Funders
Canadian Institutes of Health Research
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
  • Life Sciences › Immunology and Microbiology › Microbiology › Reproductive tract infections research
Keywords
breast microbiome, breast cancer, bacterial diversity, adjacent normal tissue, tumor tissue, Bacillus, Enterobacteriaceae, Staphylococcus epidermidis, Escherichia coli, DNA double-strand breaks, H2AX phosphorylation, lactic acid bacteria, cancer risk, environmental factors
MeSH terms
Adult, Aged, Aged, 80 and over, Bacteria, Breast, Breast Neoplasms, Female, Humans, Middle Aged, Ontario, RNA, Ribosomal, 16S, Sequence Analysis, DNA, Young Adult, Microbiota

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