Perivascular M2 Macrophages Stimulate Tumor Relapse after Chemotherapy
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Bibliographic record
Abstract
Tumor relapse after chemotherapy-induced regression is a major clinical problem, because it often involves inoperable metastatic disease. Tumor-associated macrophages (TAM) are known to limit the cytotoxic effects of chemotherapy in preclinical models of cancer. Here, we report that an alternatively activated (M2) subpopulation of TAMs (MRC1(+)TIE2(Hi)CXCR4(Hi)) accumulate around blood vessels in tumors after chemotherapy, where they promote tumor revascularization and relapse, in part, via VEGF-A release. A similar perivascular, M2-related TAM subset was present in human breast carcinomas and bone metastases after chemotherapy. Although a small proportion of M2 TAMs were also present in hypoxic tumor areas, when we genetically ablated their ability to respond to hypoxia via hypoxia-inducible factors 1 and 2, tumor relapse was unaffected. TAMs were the predominant cells expressing immunoreactive CXCR4 in chemotherapy-treated mouse tumors, with the highest levels expressed by MRC1(+) TAMs clustering around the tumor vasculature. Furthermore, the primary CXCR4 ligand, CXCL12, was upregulated in these perivascular sites after chemotherapy, where it was selectively chemotactic for MRC1(+) TAMs. Interestingly, HMOX-1, a marker of oxidative stress, was also upregulated in perivascular areas after chemotherapy. This enzyme generates carbon monoxide from the breakdown of heme, a gas known to upregulate CXCL12. Finally, pharmacologic blockade of CXCR4 selectively reduced M2-related TAMs after chemotherapy, especially those in direct contact with blood vessels, thereby reducing tumor revascularization and regrowth. Our studies rationalize a strategy to leverage chemotherapeutic efficacy by selectively targeting this perivascular, relapse-promoting M2-related TAM cell population.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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 it