Cerebrovascular inflammation promotes the formation of brain metastases
Bibliographic record
Abstract
Brain metastases are the most prevalent intracranial malignancy. Patient outcome is poor and treatment options are limited. Hence, new avenues must be explored to identify potential therapeutic targets. Inflammation is a known critical component of cancer progression. Intratumoral inflammation drives progression and leads to the release of circulating tumor cells (CTCs). Inflammation at distant sites promotes adhesion of CTCs to the activated endothelium and then initiates the formation of metastases. These interactions mostly involve cell adhesion molecules expressed by activated endothelial cells. For example, the vascular cell adhesion molecule-1 (VCAM-1) is known to promote transendothelial migration of cancer cells in different organs. However, it is unclear whether a similar mechanism occurs within the specialized environment of the brain. Our objective was therefore to use molecular imaging to assess the potential role of VCAM-1 in promoting the entry of CTCs into the brain. First, magnetic resonance imaging (MRI) and histological analyses revealed that cerebrovascular inflammation induced by intracranial injection of lipopolysaccharide significantly increased the expression of VCAM-1 in the Balb/c mouse brain. Next, intracardiac injection of 4T1 mammary carcinoma cancer cells in animals with cerebrovascular inflammation yielded a higher brain metastasis burden than in the control animals. Finally, blocking VCAM-1 prior to 4T1 cells injection prevented this increased metastatic burden. Here, we demonstrated that by contributing to CTCs adhesion to the activated cerebrovascular endothelium, VCAM-1 improves the capacity of CTCs to form metastatic foci in the brain.
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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 | 0.000 | 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 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".