Inhibition of Tubulogenesis and of Carcinogen‐mediated Signaling in Brain Endothelial Cells Highlight the Antiangiogenic Properties of a Mumbaistatin Analog
Bibliographic record
Abstract
A better understanding of the metabolic adaptations of the vascular endothelial cells (EC) that mediate tumor vascularization would help the development of new drugs and therapies. Novel roles in cell survival and metabolic adaptation to hypoxia have been ascribed to the microsomal glucose-6-phosphate translocase (G6PT). While antitumorigenic properties of G6PT inhibitors such as chlorogenic acid (CHL) have been documented, those of the G6PT inhibitor and semi-synthetic analog AD4-015 of the polyketide mumbaistatin are not understood. In the present study, we evaluated the in vitro antiangiogenic impact of AD4-015 on human brain microvascular endothelial cells (HBMEC), which play an essential role as structural and functional components in tumor angiogenesis. We found that in vitro HBMEC migration and tubulogenesis were reduced by AD4-015 but not by CHL. The mumbaistatin analog significantly inhibited the phorbol 12-myristate 13-acetate (PMA)-induced matrix-metalloproteinase (MMP)-9 secretion and gene expression as assessed by zymography and RT-PCR. PMA-mediated cell signaling leading to cyclooxygenase (COX)-2 expression and IkappaB downregulation was also inhibited, further confirming AD4-015 as a cell signaling inhibitor in tumor promoting conditions. G6PT functions may therefore account for the metabolic flexibility that enables EC-mediated neovascularization. This process could be specifically targeted within the vasculature of developing brain tumors by G6PT inhibitors.
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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) | 0.001 | 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".