Neutrophils: Orchestrators of the Malignant Phenotype
Bibliographic record
Abstract
Neutrophils are the first leukocytes recruited to sites of inflammation, where they execute anti-microbial functions to eliminate infectious agents. These functions include phagocytosis, release of reactive oxygen species and the formation of neutrophil extracellular traps via NETosis. Neutrophils are receiving increasing attention in the context of cancer, where these same neutrophil-associated functions are also important for modulating tumor growth and metastatic progression. Neutrophils are phenotypically heterogeneous and, depending on the context, exert anti- or pro-tumorigenic functions. Increasing evidence also suggests an important role of neutrophils and their involvement in promoting multiple steps of the metastatic cascade. The steps include: (1) local invasion and intravasation of cancer cells into circulation, (2) survival of cancer cells in the bloodstream and extravasation at a distant site, (3) early cancer cell seeding/survival, and (4) progressive growth of cancer cells to form macroscopic metastases. Although neutrophil functions designed to eliminate infectious agents can also eliminate tumor cells, their dysregulation can promote tumor growth and enable metastasis at multiple steps along the metastatic cascade. In this review, we will provide an overview of the current advances in neutrophil biology in the context of cancer. We also discuss the emerging field of immunometabolism, in which the rewiring of alternative metabolic pathways within neutrophils can impact their pro-tumorigenic/pro-metastatic functions.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".