Pancreatic Endocrine Microadenomatosis in Patients With von Hippel-Lindau Disease
Bibliographic record
Abstract
Introduction Von Hippel-Lindau (VHL) disease is an inherited syndrome caused by germline mutation in the VHL tumor suppressor gene predisposing to pancreatic endocrine tumors (PET). Whether these tumors derive from preexisting endocrine microadenomatosis as in multiple endocrine neoplasia type 1 (MEN1) is yet unknown. pVHL regulates hypoxia-inducible factor (HIF) that causes transcription activity of target genes like carbonic anhydrase 9 (CA9), vascular endothelial growth factor (VEGF), and cyclin D1. Our aim was to look for overexpression of these molecules to identify precursor endocrine lesions in the pancreas of VHL patients. Methods Nontumoral pancreas of 18 VHL patients operated on for PET, was examined for microadenomatosis (≤5 mm) and compared with pancreatic specimen obtained from non-VHL patients or MEN1 patients. The immunohistochemical expression of chromogranin, insulin, glucagon, HIF-1α, HIF-2α, VEGF, CA9, cyclin D1, and CD34 was assessed. Results In addition to 39 macrotumors (1 to 5/patient), chromogranin-positive endocrine microadenomas were found in 13 (72%) patients located within acini or close to ducts or islets. Strong coexpression of HIF-1α, cyclin D1, CA9, and VEGF and lack of expression of insulin and glucagon allowed distinction with normal or hyperplastic islets. CD34 identified a high microvessel density in these nodules. Expression of HIF-1α and CA9 was not found in islets of controls and in MEN1 microadenomas. Conclusions Pancreatic endocrine microadenomas are present in >70% of VHL patients operated on for PET. These results demonstrate that the pVHL/HIF pathway is involved very early in pancreatic endocrine tumorigenesis in this disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".