Steroid receptor coactivator-1 regulates glioma angiogenesis through polyomavirus enhancer activator 3 signaling
Bibliographic record
Abstract
Steroid receptor coactivator 1 (SRC-1) is a transcriptional coactivator for steroid receptors and other transcription factors. SRC-1 has been shown to play an important role in the progression of breast cancer and prostate cancer. However, its role in glioma progression remains unknown. Here, in this study, we report that SRC-1 is upregulated in the vessels of human glioma and exerts important regulatory functions. Specifically, SRC-1 expression significantly enhanced basic fibroblast growth factor (bFGF)-mediated angiogenesis in vivo. Downregulating of SRC-1 expression suppressed endothelial cell migration and tube formation in vitro and upregulated the expression of pro-angiogenic factors, including vascular endothelial growth factor (VEGF) and matrix metallopeptidase (MMP)-9 in glioma cells. These SRC-1-mediated effects were dependent on the activation of polyomavirus enhancer activator 3 (PEA3) transcriptional activity. VEGF and VEGF inducer GS4012 induced the direct binding of SRC-1 and PEA3 in glioma cells, and PEA3 could directly bind with VEGF and MMP-9 promoter under GS4012 treatment in glioma cell. The expression of pro-angiogenic factors induced by SRC-1 was abrogated by sh-PEA3 knockdown. Taken together, these novel outcomes indicated that SRC-1 modulated endothelial cell (EC) function and facilitated a pro-angiogenic microenvironment through PEA3 signaling. Moreover, a combination of targeting SRC-1 and PEA3 signaling in glioma could be a promising strategy for suppressing tumor angiogenesis.
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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) | 0.001 | 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".