Abstract 978: Monocyte-derived macrophages contribute to the inflammation-induced survival of experimental micrometastases in the lung
Bibliographic record
Abstract
Abstract Circulating tumor cells become fully metastatic if they are able to extravasate from the microvasculature and move into microenvironmental niches that facilitate their survival within distant site organs. To determine if inflammation promotes this process in the lungs, inflammatory asthma, hypersensitivity pneumonitis, or bleomycin-induced injury were initiated prior to the intravenous introduction of low malignant potential B16F0 melanoma cells. All three conditions increased end-stage metastatic burden without increasing the initial tumor cell extravasation from the lung microvasculature. There was, however, an increase in the number and size of early micrometastatic lesions within the lung interstitia that were visible 96 hr after melanoma cell introduction. There was also an increase in tumor cell survival within these early lesions located in the inflamed lungs that was associated with the presence of nearby newly recruited CD11c+CD11b+ monocyte-derived macrophages (MoDM). Adoptive transfer experiments indicated that these MoDM cells facilitated B16F0 cell metastasis in the absence of inflammation. Additionally, a factor, or factors, secreted by MoDM promoted B16F0 cell survival under stress-inducing condition. Taken together, these findings demonstrate that inflammation-induced monocyte-derived macrophages act as a modifier of the post-extravasation microenvironment that appears to facilitate the early emergence of distant site metastasis. Citation Format: Arif A. Arif, Spencer A. Freeman, Jawairia Atif, Pamela Dean, Megan Gilmour, Marie-Renee Blanchet, Kimberly Wiegand, Kelly M. McNagny, Michael Underhill, Michael Gold, Pauline Johnson, Calvin D. Roskelley. Monocyte-derived macrophages contribute to the inflammation-induced survival of experimental micrometastases in the lung [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 978.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".