Neuropilin-1 exerts co-receptor function for TGF-beta-1 on the membrane of cancer cells and enhances responses to both latent and active TGF-beta
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Bibliographic record
Abstract
Neuropilin (Nrp)-1 and Nrp-2 are multifunctional proteins frequently expressed by cancer cells and contribute to tumor progression by mechanisms that are not well understood. They are co-receptors for vascular endothelial growth factor and class 3 semaphorins, but recently we found that Nrp1 also binds latent and active transforming growth factor (TGF)-β1, and activates the latent form latency-associated peptide (LAP)-TGF-β1. Here, we report that Nrp1 has affinity for TGF-β receptors TβRI and TβRII, the signaling TGF-β receptors, as well as TβRIII (betaglycan), as determined in binding assays, pull down assays and confocal microscopy. Nrp1 had a higher affinity for TβRI than TβRII and could form a complex with these receptors. In breast cancer cells, Nrp1 and TβRI cointernalized in the presence of TGF-β1. Nrp1 acted as a TGF-β co-receptor by augmenting canonical Smad2/3 signaling. Importantly, Nrp-positive cancer cells, unlike negative cells, were able to activate latent TGF-β1 and respond. We examined two other membrane proteins that bind LAP-TGF-β, i.e. an RGD-binding integrin (αvβ3) and Glycoprotein A repetitions predominant (CLRRC32). RGD-binding integrins are frequently expressed by cancer cells, and glycoprotein A repetitions predominant is expressed by activated regulatory T cells that appear linked to poor tumor immunity. In vitro, these receptors did not activate LAP-TGF-β1, but subsequent addition of Nrp1 activated the cytokine. Thus, Nrp1 might collaborate with other latent TGF-β receptors in TGF-β capture and activation. We also show that Nrp2 has activities similar to Nrp1. We conclude that Nrp1 is a co-receptor for TGF-β1 and augments responses to latent and active TGF-β. Since TGF-β promotes metastasis this is highly relevant to cancer biology.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it