Bone morphogenetic protein antagonist gremlin-1 regulates colon cancer progression
Bibliographic record
Abstract
Bone morphogenetic proteins (BMP) are phylogenetically conserved signaling molecules of the transforming growth factor-beta (TGF-beta) superfamily of proteins, involved in developmental and (patho)physiological processes, including cancer. BMP signaling has been regarded as tumor-suppressive in colorectal cancer (CRC) by reducing cancer cell proliferation and invasion, and by impairing epithelial-to-mesenchymal transition (EMT). Here, we mined existing proteomic repositories to explore the expression of BMPs in CRC. We found that the BMP antagonist gremlin-1 (GREM1) is secreted from heterotypic tumor-host cell interactions. We then sought to investigate whether GREM1 is contextually and mechanistically associated with EMT in CRC. Using immunohistochemistry, we showed that GREM1-expressing stromal cells harbor prominent features of myofibroblasts (i.e., cancer-associated fibroblasts), such as expression of α-smooth muscle actin and laminin-beta-1, and were in contextual proximity to invasion fronts with loss of the tight junction protein occludin and parallel nuclear accumulation of β-catenin, two prominent EMT hallmarks. Furthermore, in vitro assays demonstrated that GREM1-dependent suppression of BMP signaling results in EMT induction, characterized by cadherin switching (loss of E-cadherin-upregulation of N-cadherin) and overexpression of Snail. Collectively, our data support that GREM1 promotes the loss of cancer cell differentiation at the cancer invasion front, a mechanism that may facilitate tumor 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) | 0.001 | 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".