Tumor microenvironment conditions that favor vessel co-option in colorectal cancer liver metastases: A theoretical model
Bibliographic record
Abstract
Vessel co-option is an alternative strategy by which tumour cells vascularize and gain access to nutrients to support tumour growth, survival and metastasis. In vessel co-option, the cancer cells move towards the pre-existing vasculature and hijack them. Vessel co-option is adopted by a wide range of human tumours including colorectal cancer liver metastases (CRCLM) and is responsible for the effectiveness of treatment in CRCLM. Furthermore, vessel co-option is an intrinsic feature and an acquired mechanism of resistance to anti-angiogenic treatment. In this review, we describe the microenvironment, the molecular players, discovered thus far of co-opting CRCLM lesions and propose a theoretical model. We also highlight key unanswered questions that are critical to improving our understanding of CRCLM vessel co-option and for the development of effective approaches for the treatment of co-opting tumours.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".