Hypoxia-Induced NPY1R And NPY5R Are Linked To Breast Cancer Progression And Can Be Antagonized With Commercially Available Inhibitors
Bibliographic record
Abstract
Neuropeptide Y (NPY) is the most abundant neuropeptide in the mammalian central and peripheral nervous system. It acts on the cardiovascular, digestive, immune, endocrine, nervous, and immune systems. Various NPY receptors (NPYRs) display elevated expression in different types of cancers, but NPY1R and NPY5R are the most highly expressed in breast tumours. Here, we investigate how hypoxia, a feature that drives malignancy in the tumour microenvironment, influences the activity of NPYRs. We show that NPY1R and NPY5R expression and activity are directly influenced by hypoxia inducible factors (HIFs) in both ER+ (MCF7) and ER- (MDA-MB-231) cell lines. We found that cells are more responsive to NPY5R stimulation in hypoxia compared to normoxia, leading to enhanced migration and proliferation. We demonstrate that we can impede these augmented responses through pharmacological inhibition of NPY1R in MDA-MB-231 and NPY5R in MCF7. We establish that these cellular responses occur in both cell monolayers and spheroids, which recapitulate the tumour microenvironment more closely. In line with this, we find that expression of NPY1R and NPY5R correlate with adverse patient outcomes in breast tissue samples from the Ontario Tumour Bank. This study reveals for the first time that hypoxia-induced NPYRs render cells more sensitive to NPY stimulation, and that this response can be impeded by blocking the receptors. Since breast tissue is highly innervated by the nervous system, and the expression of NPYRs correlate with negative patient prognosis, further research into antagonizing these receptors may aid in the development of novel therapeutics and personalized treatment plans.
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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) | 0.003 | 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".