Abstract 5271: Ibuprofen, an inhibitor of angiogenesis, enhances radiosensitivity and suppresses glioma invasion: Role of p75NTR and VEGF
Bibliographic record
Abstract
Abstract Current treatments of malignant glioma, including anti-VEGF therapy, are limited by the invasive phenotype. Ionizing radiation is known to stimulate invasion, and p75NTR is a key regulator of glioma invasion. Because angiogenic inhibitors have been proposed as radiosensitizers, we hypothesized that ibuprofen (previously shown to regulate p75NTR) would serve as a radiosensitizer of glioma cells, and we studied its effect on glioma migration, invasion, and the expression of p75NTR and VEGF. The purpose of this study was to investigate the effect of combining radiation with ibuprofen on expression of p75NTR in human (U87, U251) and murine (GL261) glioma cells, and link to radiosensitivity, migration and invasion, and angiogenesis. Methods: We determined radiosensitivity using a clonogenic assay of glioma cells, including clones that were transfected to stably overexpress p75NTR. Glioma cells transfected with empty vector (pcDNA) were used as a control. Glioma migration and invasion were determined, respectively, by a wound scratch assay and Matrigel-Boyden chamber assay. Expression levels of p75NTR and VEGF165 were determined by Western blot analysis. Results: Ibuprofen increased the radiosensitivity of glioma cells as evidenced by a decreased survival fraction in the clonogenic assay. U87+p75NTR demonstrated increased radiosensitivity compared to control (U87pcDNA). As expected, U87+p75NTR U251+p75NTR were highly invasive and migratory compared to U87pcDNA and U251pcDNA. At a dose of 10 Gy, migration was significantly inhibited (P=0.02) in pcDNA cells only. Induction of p75NTR with ibuprofen correlated to increased radiosensitivity of glioma cells. Paradoxically we found that increased expression of p75NTR by ibuprofen correlated to a reduction of invasion and migration. In addition, expression of VEGF was lower in U87+p75 compared to U87pcDNA. When U87+p75 was treated with ibuprofen alone, VEGF was undetectable, when treated with radiation alone VEGF levels were lower than control but detected, and no VEGF was detectable when the cells were treated with both ibuprofen and radiation. In contrast, expression of VEGF was increased when p75pcDNA glioma cells were treated with ibuprofen, and further increased when treated with radiation. However, adding ibuprofen and radiation resulted in undetectable VEGF. Conclusion: Our results suggest that ibuprofen could be useful clinically as a radiosensitizer and/or an agent to inhibit glioma invasion, migration and angiogenesis. Furthermore, our preliminary data suggest that there may be a “VEGF-switch” modulated by p75NTR status. The VEGF-p75NTR link could be important to drug discovery and translation to clinical control of the glioma malignant phenotype. (Supported by Dept of Defense grant USAMRAA -RX4301803, The Greg Wohrle Fund of the FBTA, the Moffitt Cancer Center Foundation, The Ben and Catherine Ivy Foundation). Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 5271.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.003 | 0.001 |
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".