Vascularization of colorectal carcinoma liver metastasis: insight into stratification of patients for anti‐angiogenic therapies
Bibliographic record
Abstract
Current treatment for metastatic disease targets angiogenesis. With the increasing data demonstrating that cancer cells do not entirely rely on angiogenesis but hijack the existing vasculature through mechanisms such as co-option of existing blood vessels, identification of targets has become of utmost importance. Our study looks at the vasculature of chemonaïve and treated colorectal carcinoma liver metastases (CRCLMs) to obtain a basic understanding of the microvessel density, type of vasculature (mature versus immature), and correlation with histopathological growth patterns that demonstrate unique patterns of angiogenesis. We performed immunohistochemistry on chemonaïve sections of desmoplastic histopathological growth pattern (DHGP) and replacement histopathological growth patterns (RHGP) lesions with CD31 [endothelial cell (EC) marker] and CD34/Ki67 double staining, which denotes proliferating ECs. The CD31 stains demonstrated a lower microvascular CD31 +ve capillary density in the DHGP versus RHGP lesions; and integrating both immunostains with CD34/Ki67 staining on serial sections revealed proliferating vessels in DHGP lesions and co-option of mature existing blood vessels in RHGP lesions. Interestingly, upon treatment with chemotherapy and bevacizumab, the RHGP lesions showed no necrosis whereas the DHGP lesions had almost 100% necrosis of the cancer cells and in most cases there was a single layer of viable cancer cells, just under or within the desmoplastic ring. The survival of these cells may be directly related to spatial location and possibly a different microenvironment, which may involve adhesion to different extracellular matrix components and/or different oxygen/nutrient availability. This remains to be elucidated. We provide evidence that DHGP CRCLMs obtain their blood supply via sprouting angiogenesis whereas RHGP lesions obtain their blood supply via co-option of existing vasculature. Furthermore current treatment regimens do not affect RHGP lesions and although they kill the majority of the cancer cells in DHGP lesions, there are cells surviving within or adjacent to the desmoplastic ring which could potentially give rise to a growing lesion.
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How this classification was reachedexpand
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 | 0.005 | 0.001 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".