Tumor associated macrophages as key contributors and targets in current and future therapies for melanoma
Bibliographic record
Abstract
INTRODUCTION: Despite the success of immunotherapies for melanoma in recent years, there remains a significant proportion of patients who do not yet derive benefit from available treatments. Immunotherapies currently licensed for clinical use target the adaptive immune system, focussing on Tcell interactions and functions. However, the most prevalent immune cells within the tumor microenvironment (TME) of melanoma are macrophages, a diverse immune cell subset displaying high plasticity, to which no current therapies are yet directly targeted. Macrophages have been shown not only to activate the adaptive immune response, and enhance cancer cell killing, but, when influenced by factors within the TME of melanoma, these cells also promote melanoma tumorigenesis and metastasis. AREAS COVERED: We present a review of the most up-to-date literatureavailable on PubMed, focussing on studies from within the last 10 years. We also include data from ongoing and recent clinical trials targeting macrophages in melanoma listed on clinicaltrials.gov. EXPERT OPINION: Understanding the multifaceted role of macrophages in melanoma, including their interactions with immune and cancer cells, the influence of current therapies on macrophage phenotype and functions and how macrophages could be targeted with novel treatment approaches, are all critical for improving outcomes for patients with melanoma.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".