Macrophages eliminate circulating tumor cells after monoclonal antibody therapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of monoclonal antibodies (mAbs) as therapeutic tools has increased dramatically in the last decade and is now one of the mainstream strategies to treat cancer. Nonetheless, it is still not completely understood how mAbs mediate tumor cell elimination or the effector cells that are involved. Using intravital microscopy, we found that antibody-dependent phagocytosis (ADPh) by macrophages is a prominent mechanism for removal of tumor cells from the circulation in a murine tumor cell opsonization model. Tumor cells were rapidly recognized and arrested by liver macrophages (Kupffer cells). In the absence of mAbs, Kupffer cells sampled tumor cells; however, this sampling was not sufficient for elimination. By contrast, antitumor mAb treatment resulted in rapid phagocytosis of tumor cells by Kupffer cells that was dependent on the high-affinity IgG-binding Fc receptor (FcγRI) and the low-affinity IgG-binding Fc receptor (FcγRIV). Uptake and intracellular degradation were independent of reactive oxygen or nitrogen species production. Importantly, ADPh prevented the development of liver metastases. Tumor cell capture and therapeutic efficacy were lost after Kupffer cell depletion. Our data indicate that macrophages play a prominent role in mAb-mediated eradication of tumor cells. These findings may help to optimize mAb therapeutic strategies for patients with cancer by helping us to aim to enhance macrophage recruitment and activity.
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.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 it