Low intracellular ATP levels exacerbate carcinogen-induced inflammatory stress response and inhibit in vitro tubulogenesis in human brain endothelial cells
Bibliographic record
Abstract
Solid tumor development requires angiogenesis and is correlated to the expression of inflammatory markers through cellular metabolic and energetic adaptation. While high glycolysis rates enable the cancer cell compartment to generate adenosine triphosphate (ATP), very little is known about the impact of low intracellular ATP concentrations within the vascular endothelial cell compartment, which is responsible for tumor angiogenesis. Here, we investigated the effect of 2-deoxy-D-glucose (2-DG), a glucose analog that inhibits glycolysis through intracellular ATP depletion, on human brain microvascular endothelial cell (HBMEC) angiogenic properties. While preformed capillaries remained unaffected, we found that in vitro tubulogenesis was dose-dependently decreased by 2-DG and that this correlated with reduced intracellular ATP levels. Procarcinogenic signaling was induced with phorbol 12-myristate 13-acetate (PMA) and found to trigger the proinflammatory marker cyclooxygenase-2 (COX-2) and endoplasmic reticulum (ER) stress marker GRP78 expression, whose inductions were potentiated when PMA was combined with 2-DG treatment. Inversely, PMA-induced matrix-metalloproteinase-9 (MMP-9) gene expression and protein secretion were abrogated in the presence of 2-DG, and this can be partially explained by reduced nuclear factor-κB signaling. Collectively, we provide evidence for an intracellular ATP requirement in order for tubulogenesis to occur, and we link increases in ER stress to inflammation. A better understanding of the metabolic adaptations of the vascular endothelial cells that mediate tumor vascularization will help the development of new drugs and therapies.
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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".