4T1 Murine Mammary Carcinoma Cells Enhance Macrophage-Mediated Innate Inflammatory Responses
Bibliographic record
Abstract
Tumor progression and the immune response are intricately linked. While it is known that cancers alter macrophage inflammatory responses to promote tumor progression, little is known regarding how cancers affect macrophage-dependent innate host defense. In this study, murine bone-marrow-derived macrophages (BMDM) were exposed to murine carcinoma-conditioned media prior to assessment of the macrophage inflammatory response. BMDMs exposed to 4T1 mammary carcinoma-conditioned medium demonstrated enhanced production of pro-inflammatory cytokines tumor necrosis factor α, interleukin-6, and CCL2 in response to lipopolysaccharide (LPS) while production of interleukin-10 remained unchanged. The increased LPS-induced production of pro-inflammatory cytokines was transient and correlated with enhanced cytokine production in response to other Toll-like receptor agonists, including peptidoglycan and flagellin. In addition, 4T1-conditioned BMDMs exhibited strengthened LPS-induced nitric oxide production and enhanced phagocytosis of Escherichia coli. 4T1-mediated augmentation of macrophage responses to LPS was partially dependent on the NFκB pathway, macrophage-colony stimulating factor, and actin polymerization, as well as the presence of 4T1-secreted extracellular vesicles. Furthermore, peritoneal macrophages obtained from 4T1 tumor-bearing mice displayed enhanced pro-inflammatory cytokine production in response to LPS. These results suggest that uptake of 4T1-secreted factors and actin-mediated ingestion of 4T1-secreted exosomes by macrophages cause a transient enhancement of innate inflammatory responses. Mammary carcinoma-mediated regulation of innate immunity may have significant implications for our understanding of host defense and cancer progression.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".