Dynamic differentiation of F4/80+ tumor-associated macrophage and its role in tumor vascularization in a syngeneic mouse model of colorectal liver metastasis
Bibliographic record
Abstract
Abstract Tumor-associated macrophages (TAMs) are highly heterogeneous and play vital roles in tumor progression. Here we adopted a C57BL/6 mouse model imitating the late-stage colorectal liver metastasis (CRLM) by Mc38 colorectal cancer cell injection via the portal vein. With serial sections of CRLM biopsies, we defined 7–9 days post-injection as the critical period for tumor neovascularization, which was initiated from the innate liver vessels via vessel cooption and extended by vascular mimicry and thereof growth of CD34 + cells. In samples with increasing-sized liver metastases, the infiltrated Ly6C + CD11b + F4/80 − monocytes steadily gained the expression of F4/80, a Kupffer cell marker, before transformed into Ly6C − CD11b int F4/80 + cells, which, the same phenotype was also adapted by Ly6C − CD11b − F4/80 + Kupffer cells. F4/80 + TAMs showed proximity to neovascularization and tumor vessels, functionally angiogenic in vivo; and greatly promoted the activation of a few key angiogenic markers such as VEGFA, Ki67, etc. in endothelial cells in vitro. Depletion of macrophages or diversion of macrophage polarization during neovascularization impeded tumor growth and vascularization and resulted in greatly reduced F4/80 + TAMs, yet increased CD11b + cells due to inhibition of TAM differentiation. In summary, our results showed dynamic and spatial–temporal F4/80 + TAM transformation within the tumor microenvironment and strengthened its role as perivascular and angiogenic TAMs in CRLM.
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 | 0.000 |
| 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".