Runt related transcription factor-1 plays a central role in vessel co-option of colorectal cancer liver metastases
Bibliographic record
Abstract
Colorectal cancer liver metastasis (CRCLM) has two major histopathological growth patterns: angiogenic desmoplastic and non-angiogenic replacement. The replacement lesions obtain their blood supply through vessel co-option, wherein the cancer cells hijack pre-existing blood vessels of the surrounding liver tissue. Consequentially, anti-angiogenic therapies are less efficacious in CRCLM patients with replacement lesions. However, the mechanisms which drive vessel co-option in the replacement lesions are unknown. Here, we show that Runt Related Transcription Factor-1 (RUNX1) overexpression in the cancer cells of the replacement lesions drives cancer cell motility via ARP2/3 to achieve vessel co-option. Furthermore, overexpression of RUNX1 in the cancer cells is mediated by Transforming Growth Factor Beta-1 (TGFβ1) and thrombospondin 1 (TSP1). Importantly, RUNX1 knockdown impaired the metastatic capability of colorectal cancer cells in vivo and induced the development of angiogenic lesions in liver. Our results confirm that RUNX1 may be a potential target to overcome vessel co-option in CRCLM.
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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".