Abstract A17: A lincRNA orchestrates glioma stem cell-mediated angiogenesis in glioblastoma
Bibliographic record
Abstract
Abstract Angiogenesis is a hallmark of glioblastoma. Recent data suggest that glioma stem cells (GSCs) contribute to pathologic angiogenesis through transdifferentiation into endothelial cells or vascular pericytes. Using an unbiased screen, we identified a lincRNA near the VEGFR1 gene, which we named LIVE (lincRNA-VEGFR1), that directs physiologic vascular network formation through global effects on gene expression. LIVE is highly expressed in glioblastoma and enriched in GSCs. Over-expression of LIVE results in specification of GSCs along a vascular lineage. LIVE associates with PARP1 in GSCs and RNA helicase A in endothelial cells to drive pericyte-specific and endothelial-associated gene expression, respectively. Depletion of LIVE in a xenograft model of glioblastoma results in decreased microvascular density, vascular perfusion and pericyte coverage, and depletion of GSCs within the vascular niche. Our findings demonstrate a novel role for lincRNAs in the orchestration of tumour angiogenesis and reveal a therapeutic potential for targeting LIVE in glioblastoma. Citation Format: Jenny J. Wang, Megan Wu, Christopher Li, Uswa Shahzad, Jason Karamchandani, Phil Marsden, Sunit Das. A lincRNA orchestrates glioma stem cell-mediated angiogenesis in glioblastoma. [abstract]. In: Proceedings of the AACR Special Conference on Noncoding RNAs and Cancer: Mechanisms to Medicines ; 2015 Dec 4-7; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2016;76(6 Suppl):Abstract nr A17.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".