Bone morphogenetic protein antagonist gremlin-1 regulates colon cancer progression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it