The Influence of Macrophages and the Tumor Microenvironment on Natural Killer Cells
Bibliographic record
Abstract
Numerous reviews in the field of NK cell biology dictate the pivotal role that NK cells play in tumor rejection. Although these cell types were originally described based on their cytotoxic ability, we now know that NK cells are not naturally born to kill. Both cellular interactions and the local environment in which the NK cell resides in may influence its cytotoxic functions. Just as organ specific NK cells have distinct phenotypic and functional differences, the tumor is a unique microenvironment in itself. The NK cells originally recruited to the tumor site are able to stimulate immune responses and aid in tumor destruction but eventually become persuaded otherwise by mechanisms of immunosuppression. Here, we review potential mechanisms and players involved in NK cell immunosuppression. In particular the effects of another innate immune player, macrophages, will be addressed in augmenting immunosuppression of NK cells within tumors. Tumorassociated macrophages (TAMs) are the main regulatory population of myeloid cells in the tumor and are characterized by their ability to promote tumor cell proliferation and metastasis. In addition, they express/release immunoregulatory factors which have been shown to directly inhibit NK cell function. Understanding how these two cell types interact in the distinct tumor microenvironment will allow us to consider therapies that target TAMs to promote enhanced NK cell activity. Keywords: Immunosuppression, tumor-associated macrophages (TAMs), tumor-associated NK cells, tumor microenvironment
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".