HIF-dependent Neuropeptide Y Receptor Y1 and Y5 expression sensitizes hypoxic cells to NPY stimulation
Bibliographic record
Abstract
ABSTRACT Neuropeptide Y (NPY) is an abundant neurohormone in the central and peripheral nervous system involved in feeding behavior, energy balance, nociception, and anxiety. Several NPY receptor (NPYR) subtypes display elevated expression in many cancers including in breast cancer where this is exploited for imaging and diagnosis. Here, we show that NPY1R and NPY5R mRNA abundance is induced by hypoxia in a Hypoxia Inducible Factor (HIF)-dependent manner in breast cancer cell lines MCF7 and MDA-MB-231. The HIFs bind to several genomic regions upstream of the NPY1R and NPY5R transcription start sites. The MAPK/ERK pathway is activated more rapidly upon NPY5R stimulation in hypoxic cells compared to normoxic cells. This pathway requires IGF1R activity in normoxia, but not in hypoxic cells where they display resistance to the radiosensitizer and IGF1R inhibitor AG1024. Hypoxic cells proliferate and migrate more when stimulated with NPY relative to normoxic cells, with a more robust response observed with a Y5-specific agonist. Our data suggest that hypoxia induced NPYRs render hypoxic cells more sensitive to NPY stimulation. Considering that breast tissue receives a constant supply of NPY, and hypoxia is a common feature of the tumor microenvironment, breast tumors are the perfect storm for hyperactive NPYR. This study not only highlights a new relationship between the HIFs and NPYR expression and activity, but may inform the use of chemotherapeutics targeting NPYRs and hypoxic cells.
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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) | 0.002 | 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".