Immature Low-Density Neutrophils Exhibit Metabolic Flexibility that Facilitates Breast Cancer Liver Metastasis
Bibliographic record
Abstract
Neutrophils are phenotypically heterogeneous and exert either anti- or pro-metastatic functions. We show that cancer-cell-derived G-CSF is necessary, but not sufficient, to mobilize immature low-density neutrophils (iLDNs) that promote liver metastasis. In contrast, mature high-density neutrophils inhibit the formation of liver metastases. Transcriptomic and metabolomic analyses of high- and low-density neutrophils reveal engagement of numerous metabolic pathways specifically in low-density neutrophils. iLDNs exhibit enhanced global bioenergetic capacity, through their ability to engage mitochondrial-dependent ATP production, and remain capable of executing pro-metastatic neutrophil functions, including NETosis, under nutrient-deprived conditions. We demonstrate that NETosis is an important neutrophil function that promotes breast cancer liver metastasis. iLDNs rely on the catabolism of glutamate and proline to support mitochondrial-dependent metabolism in the absence of glucose, which enables sustained NETosis. These data reveal that distinct pro-metastatic neutrophil populations exhibit a high degree of metabolic flexibility, which facilitates the formation of liver metastases.
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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) | 0.001 | 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".