Vascular endothelial growth factor is an autocrine growth factor, signaling through neuropilin-1 in non-small cell lung cancer
Bibliographic record
Abstract
BACKGROUND: The VEGF pathway has become an important therapeutic target in lung cancer, where VEGF has long been established as a potent pro-angiogenic growth factor expressed by many types of tumors. While Bevacizumab (Avastin) has proven successful in increasing the objective tumor response rate and in prolonging progression and overall survival in patients with NSCLC, the survival benefit is however relatively short and the majority of patients eventually relapse. The current use of tyrosine kinase inhibitors alone and in combination with chemotherapy has been underwhelming, highlighting an urgent need for new targeted therapies. In this study, we examined the mechanisms of VEGF-mediated survival in NSCLC cells and the role of the Neuropilin receptors in this process. METHODS: NSCLC cells were screened for expression of VEGF and its receptors. The effects of recombinant VEGF and its blockade on lung tumor cell proliferation and cell cycle were examined. Phosphorylation of Akt and Erk1/2 proteins was examined by high content analysis and confocal microscopy. The effects of silencing VEGF on cell proliferation and survival signaling were also assessed. A Neuropilin-1 stable-transfected cell line was generated. Cell growth characteristics in addition to pAkt and pErk1/2 signaling were studied in response to VEGF and its blockade. Tumor growth studies were carried out in nude mice following subcutaneous injection of NP1 over-expressing cells. RESULTS: Inhibition of the VEGF pathway with anti-VEGF and anti-VEGFR-2 antibodies or siRNA to VEGF, NP1 and NP2 resulted in growth inhibition of NP1 positive tumor cell lines associated with down-regulation of PI3K and MAPK kinase signaling. Stable transfection of NP1 negative cells with NP1 induced proliferation in vitro, which was further enhanced by exogenous VEGF. In vivo, NP1 over-expressing cells significantly increased tumor growth in xenografts compared to controls. CONCLUSIONS: Our data demonstrate that VEGF is an autocrine growth factor in NSCLC signaling, at least in part, through NP1. Targeting this VEGF receptor may offer potential as a novel therapeutic approach and also support the evaluation of the role of NP1 as a biomarker predicting sensitivity or resistance to VEGF and VEGFR-targeted therapies in the clinical arena.
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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".