Cancer-associated fibroblast-derived Gremlin 1 promotes breast cancer progression
Bibliographic record
Abstract
BACKGROUND: Bone morphogenetic proteins (BMPs) have been reported to maintain epithelial integrity and to antagonize the transforming growth factor β (TGFβ)-induced epithelial to mesenchymal transition. The expression of soluble BMP antagonists is dysregulated in cancers and interrupts proper BMP signaling in breast cancer. METHODS: In this study, we mined the prognostic role of BMP antagonists GREMLIN 1 (GREM1) in primary breast cancer tissues using in-house and publicly available datasets. We determined which cells express GREM1 RNA using in situ hybridization (ISH) on a breast cancer tissue microarray. The effects of Grem1 on the properties of breast cancer cells were assessed by measuring the mesenchymal/stem cell marker expression and functional cell-based assays for stemness and invasion. The role of Grem1 in breast cancer-associated fibroblast (CAF) activation was measured by analyzing the expression of fibroblast markers, phalloidin staining, and collagen contraction assays. The role of Grem1 in CAF-induced breast cancer cell intravasation and extravasation was studied by utilizing xenograft zebrafish breast cancer (co-) injection models. RESULTS: Expression analysis of clinical breast cancer datasets revealed that high expression of GREM1 in breast cancer stroma is correlated with a poor prognosis regardless of the molecular subtype. The large majority of human breast cancer cell lines did not express GREM1 in vitro, but breast CAFs did express GREM1 both in vitro and in vivo. Transforming growth factor β (TGFβ) secreted by breast cancer cells, and also inflammatory cytokines, stimulated GREM1 expression in CAFs. Grem1 abrogated bone morphogenetic protein (BMP)/SMAD signaling in breast cancer cells and promoted their mesenchymal phenotype, stemness, and invasion. Moreover, Grem1 production by CAFs strongly promoted the fibrogenic activation of CAFs and promoted breast cancer cell intravasation and extravasation in co-injection xenograft zebrafish models. CONCLUSIONS: Our results demonstrated that Grem1 is a pivotal factor in the reciprocal interplay between breast cancer cells and CAFs, which promotes cancer cell invasion. Targeting Grem1 could be beneficial in the treatment of breast cancer patients with high Grem1 expression.
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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 | 0.001 | 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) | 0.003 | 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".