Abstract 5208: Neovascularization in brain metastasis is through both angiogenesis and vasculogenesis
Bibliographic record
Abstract
Abstract Metastatic brain tumors are the most common brain tumor in adults with an incidence 10 times greater than primary brain tumors. A variety of malignancies eventually spread to the brain, with a majority arising from cancers of the lung, breast, kidney, and skin. Experimental studies using breast and melanoma cell lines have recently shown that growth of metastatic brain tumors may occur by utilizing pre-existing blood vessel, or by co-opting rather than inducing new vessel formation. Whether the same mechanisms of vascular utilization and expansion play a role in human metastatic brain tumors is unknown and is the focus of the present study. We examined the immuno-phenotype of blood vessels in primary and metastatic human brain tumors to determine the presence of new blood vessels formation. Glioblastoma multiforme (n = 12) and secondary tumors from melanoma (n = 10), breast (n = 10), kidney (n = 5), and lung (n = 13) all showed extensive immunoreactivity for endothelial marker CD31. We also found a significant number of endothelial cells expressing Ki-67, most notably among breast carcinoma, glioblastoma multiforme and melanoma cases, indicating microvessel proliferation and angiogenesis. Interestingly, both primary and secondary metastatic tumors also showed vascular endothelial cells concomitantly expressing stem cell markers, such as Oct4, suggesting that some of these microvessels are derived through vasculogenesis. These findings show that both proliferation of endothelial cells and de novo endothelial differentiation may underlie metastatic tumor growth to different degrees depending on their site of primary origin. Currently, our laboratory is determining the exact contribution of angiogenesis and vasculogenesis in brain metastasis. Our findings show that neo-vessels are evident in brain metastasis. Elucidating the source of these vessels may uncover new treatment targets for patients with brain metastasis. Citation Format: Stephanie Mok, Lee-Cyn Ang, Christopher J. Howlett, Zia A. Khan. Neovascularization in brain metastasis is through both angiogenesis and vasculogenesis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5208. doi:10.1158/1538-7445.AM2015-5208
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.006 | 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".