ANGI-11. BONE MARROW-DERIVED MESENCHYMAL STEM CELLS-MEDIATED RADIORESISTANCE IN GLIOBLASTOMA ANGIOGENESIS
Bibliographic record
Abstract
As the central component of heightened vascularization in glioblastoma (GBM), endothelial cells (EC) are arguably the most responsive stromal cells in the tumor microenvironment (TME) during conventional treatment using ionizing radiation (IR) and have important implication in cancer progression as well as therapy-resistance. Although the inherent tumor tropism and angiogenic property of mesenchymal stem cells (MSC) has been documented in GBM, little is known about the function of MSC that are recruited to the GBM Tumor microenvironment. To elucidate the effect of MSC on irradiated EC, we studied the influence of IR, MSC or MSC condition media (CM) on human umbilical vein endothelial cells (HUVECs). IR decreased HUVEC cell proliferation at 24 and 48 hours whilst MSCCM increased cell proliferation at 48 hours. MSCCM doubled the viable number of non-irradiated HUVECs at 48 hours. IR caused phosphorylation of p53 in HUVECs regardless of MSC presence. While 2Gy of radiation was able to transiently increase p-ATM level at 4 hours post IR, MSCCM prolonged this process up to 8 hours. IR preferentially increased p-Akt levels (but not p-ERK1/2) at 8 hours post IR while MSCCM advanced this event to 4 hours and amplified it by two folds when given 15Gy. IR was found to up-regulate mRNA levels of CXCL5, CXCL10, ICAM1, VCAM1 and tissue factor in a dose-dependent manner whereas MSC co-culture boosted the expression of above angiogenic factors. Interestingly, up-regulation of the same set of IR-driven genes in GBM was positively correlated with poor survival in the TCGA GBM database, a strong correlation that was absent if using gene list that was obtained from IR and MSC combine treatment in HUVEC. These findings suggest that MSC promotes angiogenesis in GBM by facilitating the IR-induced active state as well as the effectiveness of DNA damage repair in endothelial cells.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".