Abstract 2463: Protease nexin 1 modulates prostate adenocarcinoma by regulating the Hedgehog pathway in humans and mice
Bibliographic record
Abstract
Abstract Prostate adenocarcinoma is the most frequent cancer and is the second leading cause of cancer death of men in the Western world. Aberrant activation of the Hedgehog (Hh) pathway is implicated in the growth and progression of prostate cancer. We show that the Hh pathway is inhibited by the serine protease inhibitor, protease nexin 1 (PN1), an extracellular matrix (ECM) protein highly expressed in normal prostate. We demonstrate here that PN1 regulates Hh signalling by reduction of the Hh ligand, Sonic (SHH), and its downstream effectors in tissue culture and in vivo. Conversely, matrix metalloproteinase 9 (MMP9) enhances Hh signalling through degradation of PN1. MRI imaging was used to determine variation in tumour formation in an orthotopic prostate tumour model using PN1 and MMP9 knock-out mice. In PN1-/- animals, SHH was increased and tumor growth was stimulated. In contrast, PN1 levels were elevated in MMP9-/- mice while Hh signalling was reduced with concomitant decreased tumor growth. Finally, genetic alterations in Hh pathway genes identified by comparative genomic hybridization (CGH) from intermediate risk prostate cancer patients correlated with a worse clinical outcome (HR=2.67, p=0.00067), indicating the importance of this pathway in human cancer. Our data identify PN1 as a novel regulator of SHH and its downstream targets allowing PN1 levels to influence prostate tumor growth. Regulation of the PN1-Hh pathway could constitute a significant therapeutic advance in treating cancers that exhibit high expression of Hh markers. These data also provide a mechanism through which MMP-9 can regulate hedgehog pathway signalling in tissues rich in PN1. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2463. doi:1538-7445.AM2012-2463
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".