Stromal Oncostatin M axis promotes breast cancer progression
Bibliographic record
Abstract
Abstract Cancer cells are constantly communicating with the surrounding tumour microenvironment (TME) and they hijack physiological cell interactions to overcome immune system surveillance and promote cancer progression 1,2 . However, the contribution of stromal cells to the reprogramming of the TME is not well understood. In this study we provide unprecedented evidence of the role of the cytokine Oncostatin M (OSM) as central node for multicellular interactions between immune and non-immune stroma and the epithelial compartment. We show that stromal expression of the OSM:Oncostatin M Receptor (OSMR) axis plays a key role in breast cancer progression. OSMR deletion in a multistage breast cancer model delays tumour onset, tumour growth and reduces metastatic burden. We ascribed causality to the stromal function of OSM axis by demonstrating reduced tumour burden of syngeneic tumours implanted in mice. Single-cell and bioinformatic analysis of murine and human breast tumours revealed that the expression of OSM signalling components is compartmentalized in the tumour stroma. OSM expression is restricted to myeloid cells, whereas OSMR expression is detected predominantly in fibroblasts and, to a lower extent, cancer cells. Myeloid-derived OSM reprograms fibroblasts to a more contractile and pro-tumorigenic phenotype, elicits the secretion of VEGF and pro-inflammatory chemokines (e.g. CXCL1 and CXCL16), leading to increased neutrophil and macrophage recruitment. In summary, our work sheds light on the mechanism of immune regulation by the tumour microenvironment, and supports that targeting OSM:OSMR interactions is a potential therapeutic strategy to inhibit tumour-promoting inflammation and breast cancer progression.
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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) | 0.002 | 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".