Interaction between the breast tumor microenvironment and gut microbiome
Bibliographic record
Abstract
Previously believed to be sterile, the breast microenvironment has been revealed by modern DNA sequencing technologies to harbor a diverse community of microorganisms. The breast tumor microenvironment (TME) has a microbial signature unique to that of other breast pathologies as well as between breast cancer subtypes and stage. Among the plethora of microorganisms identified, Methylobacterium radiotolerans and Sphingomonas yanoikuyae stand out, both elevated in breast cancer tissue and associated with cancer stage. Breast cancer is the most common malignancy affecting women and the second most common cause of cancer-specific death in women worldwide. Gut dysbiosis has recently emerged as a key player, although the exact mechanisms are still unclear. Hypothesized mechanisms include bacterial metabolites inducing genomic instability, imbalances in the local and systemic immune system, the role of gut microbiota in the regulation of estrogen metabolism. Probiotic commensals Akkermansia muciniphila and Bifidobacterium appear to have a protective effect, with evidence of gut wall protection, correlation with less advanced disease and better treatment efficacy and tolerability. This review outlines the relationship between the breast microbiome, the gut microbiome, the ‘estrabolome’, and the immune system in breast cancer. This characterization could make a significant clinical contribution, potentially leading to new methods of primary prevention, better prognostication and prediction, as well as new avenues of treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".