1251 Impact of intra-tumoral mammary microbiota on macrophage biology and anti-tumor immune response in breast cancer
Bibliographic record
Abstract
Background In recent decades, a revolution in knowledge about the human gut microbiota has shed light on the major role of commensal bacteria in carcinogenesis, tumor progression, and the response to immunotherapy. We now know that bacteria can infiltrate various solid tumors and form a local microbiota in breast cancer. The discovery of this bacterial population has opened a new area of research into the intra-tumoral breast microbiota and its role in the tumor microenvironment (TME), particularly regarding immune content. Our laboratory detected, using immunohistochemistry on human breast tumor sections, the presence of macrophages carrying bacterial components such as lipopolysaccharide (LPS). A positive correlation was also observed between the abundance of intra-tumoral bacteria and long-term survival in patients with advanced-grade or stage breast cancer. However, at the fundamental level, the impact of these bacteria on tumor-associated immune responses and the TME remains poorly characterized in breast cancer. Considering the functional plasticity of macrophages and their prognostic significance in breast cancer, we hypothesize that certain bacterial species within the intra-tumoral breast microbiota may modulate macrophage biology, and consequently, anti-tumor immune responses, which could influence the response to immunotherapy.Methods We aimed to determine the impact of heat-inactivated bacteria ( E. coli and S. epidermidis) on the polarization phenotype of macrophages and their effect on tumors. To this end, we differentiated blood monocytes into macrophages and co-cultured them with breast cancer cell lines (MDA-MB-231, BT549, T47D, SKBR3) expressing green fluorescent protein (GFP) at the nuclear level. The macrophages were exposed to components of Gram-negative bacteria, such as LPS, or to bacteria in combination with interferon-gamma (IFN-γ).Results Based on the results obtained by fluorescent microscopy, E. coli stimulation led to a reduction in tumor cell numbers when co-cultured with macrophages. In contrast, S. epidermidis did not show any significant effect on tumor cell numbers. From a phenotypic perspective, flow cytometry and multiplex cytokine assay results showed an increased expression of surface markers associated with the M1 phenotype, such as CD86, and elevated levels of several pro-inflammatory cytokines and chemokines, including TNF-α and CXCL10, in macrophages stimulated with E. coli bacteria.Conclusions Our results suggest that macrophages stimulated by heat-inactivated E. coli can be polarized towards the tumoricidal M1 phenotype. These findings provide insights into the potential of leveraging the intra-tumoral microbiota to reprogram macrophages and modulate immune responses, offering promising strategies for improving the efficacy of immunotherapy in breast cancer patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".