Novel function of Oncostatin M as a potent tumour‐promoting agent in lung
Bibliographic record
Abstract
Oncostatin M is a leukocyte product that has been reported to have anti-proliferative effects directly on melanoma and other cancer cell lines in vitro. However, its function(s) in cancers in vivo appears complex and its roles in cancer growth in lungs are unknown. Here, we show that OSM promotes marked growth of tumour cells in mouse lungs. Local pulmonary administration of adenovirus vector expressing mouse OSM (AdOSM) induced >13-fold increase in lung tumour burden of ectopically delivered B16-F10 melanoma cells in C57BL/6 mice. AdOSM caused increases in tumour size (14 days post-challenge), whereas control vector (Addel70) did not. AdOSM had no such action in C57BL/6 mice deficient in the OSM receptor beta chain (OSMRβ-/-), indicating that these effects required OSMRβ expression on non-tumour cells in the recipient mice. AdOSM induced elevated levels of chemokines and inflammatory cells in the bronchoalveolar lavage (BAL) fluid, elevated arginase-1 mRNA levels (60-fold), and increased arginase-1+immunostaining macrophage numbers in lungs. Adherent BAL cells collected from AdOSM-treated mice expressed elevated arginase-1 activity. In contrast to AdOSM-induced effects, pulmonary over-expression of IL-1β (AdIL-1β) induced neutrophil accumulation and iNOS mRNA, but did not modulate tumour burden. AdOSM also increased lung tumour load (>50-fold) upon ectopic administration of Lewis lung carcinoma (LLC) cells in vivo. However, in vitro, neither recombinant OSM nor AdOSM infection stimulated B16-F10 or LLC cell growth directly. We conclude that pulmonary over-expression of OSM promotes tumour growth, and does so through altering the local lung environment with accumulation of M2 macrophages.
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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) | 0.001 | 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 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".