Tumor conditions induce bone marrow expansion of granulocytic, but not monocytic, immunosuppressive leukocytes with increased CXCR2 expression in mice
Bibliographic record
Abstract
Myeloid-derived suppressor cells (MDSCs) promote tumor growth through, in part, inhibiting T-cell immunity. However, mechanisms underlying MDSC expansion and guidance of MDSCs toward the tumor microenvironment remain unclear. Employing Percoll density gradients, we separate bone marrow (BM) leukocytes from tumor-bearing mice into four density-increasing bands with myeloid leukocytes enriched in bands III and IV. Band III comprises monocytes and low-density granulocytes, both confirmed to be M-MDSCs and G-MDSCs, respectively, by displaying potent inhibition of T-cell proliferation. However, monocytes act as M-MDSCs not only under tumor conditions but also the healthy condition. In contrast, band IV contains non-inhibitory, mature granulocytes. Only band III G-MDSCs display significant expansion in mice bearing B16 melanoma, Lewis lung carcinoma, or MC38 colon carcinoma. The expanded G-MDSCs also show increased CXCR2 expression, which guides egress out of BM, and produce arginase-1 and ROS upon encountering antigen-activated T cells. Adoptive transfer assays demonstrate that both G-MDSCs and mature granulocytes infiltrate tumors, but only the former displays sustention and accumulation. Intratumoral administrations of granulocytes further demonstrate that G-MDSCs promote tumor growth, whereas mature granulocytes exert minimal effects, or execute powerful anti-tumor effects providing the presence of PMN activation mechanisms in the tumor microenvironment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".