Abstract 3475: Tumor stage dependent contribution of bone marrow derived cells to tumor neo-vascularization
Bibliographic record
Abstract
Abstract Introduction: The role of bone marrow derived cells (BMDC) in tumor neo-vascularization remains controversial. We have previously demonstrated that BMDC contribute to tumor neovascularization by differentiating into vascular support cells and not endothelial cell. In this study we focus on establishing the spatiotemporal role of BMDC in tumor neovascularisation, focusing on whether it is a tumor growth stage dependent process and more specifically examining the patterns of BMDC integration into tumor vasculature in response to radiation therapy (RTx). Methods: Animal Models: Bone marrow of NOD/SCID mice were stably reconstituted with BM harvested from green-fluorescent protein (GFP) transgenic mice. Intracranial (ic) xenografts were generated in intracranial window models (ICW) using a panel of glioma cell and breast cancer cells stably expressing mCherry. In-vivo imaging: Two-photon laser capture microscopy was used to obtain high-resolution real-time in-vivo longitudinal images of the tumor cells, tumor vasculature and tracing of the circulating GFP+BM cells. Mice were imaged 1d,2d,3d,7d,10d,14d,21d & 30d following cell implantation or RTx. Brain Tumor Analysis: Mice were sacrificed using perfusion fixation and brains collected for correlative immunohistochemical and Immunofluorscent confocal analysis. RTx: Using in-house designed x-ray micro-irradiator stereotactic radiation was delivered through ICW to ic-xenografts, treated with either 3×2Gy or 3×5Gy. Tumor+RTx was compared to RTx alone or tumor alone (n=15 each arm). Results: At early stages of tumor formation (<1wk) there is 90% integration of BMDC into the tumor vasculature, while to late stages of tumor growth (>2 wks) only 10% integration of BMDC is seen. At later stages of tumor growth (>2 wks) BMDC incorporation in the tumor vasculature is predominantly seen in the tumor periphery compared to the tumor centre, with the peripheral vessels demonstrating almost 100% integration of BMDC compared to the centre of the tumor where the vasculature have no integration of BMDC. Conclusions: Our results are the first to demonstrate that there is a specific tumor growth stage dependent contribution of BMDC to tumor neo-vascularization. At early stages of tumor growth neo-ascularization relies on host BMDC, while at later stages of tumor growth vascularization relies on branching of pre-existing vessels. A significant difference in extent of BMDC integration is noted between periphery versus the centre of the tumor, suggesting that the internal tumor micro-environment regulates neoascularization differently from the periphery. Intriguingly, this distinction is not seen with tumor neovascularization in recurrent tumors following RTx. These results have significant therapeutic implications and point to a need for scheduling of anti-angiogenic therapies according to tumor growth stage and timing post RTx. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3475. doi:10.1158/1538-7445.AM2011-3475
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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) | 0.004 | 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".