Spindle Cell Oncocytomas and Granular Cell Tumors of the Pituitary Are Variants of Pituicytoma
Bibliographic record
Abstract
Pituicytomas are neoplasms that arise from pituicytes, which are specialized glia of the posterior pituitary. Pituicytes have 5 ultrastructural variants: light, dark, granular, ependymal, and oncocytic. Granular cell tumors of the pituitary gland are thought to arise from granular pituicytes. Spindle cell oncocytomas are considered to arise from folliculostellate cells, which are sustentacular cells of the adenohypophysis. Recent data suggest that, whereas pituicytes and all 3 tumor types are positive for TTF-1, folliculostellate cells are negative for TTF-1. We investigated 7 spindle cell oncocytomas, 4 pituicytomas, and 3 granular cell tumors for their genetic (BRAF(V600E) mutation and BRAF-KIAA fusion), immunohistochemical (GFAP, vimentin, S100 protein, olig2, IDH1-R132H, NF, galectin-3, chromogranin-A, CD56, EMA, CAM5.2, CD68, TTF-1, and bcl-2), and ultrastructural features to refine their classification. All tumors had nuclear positivity for TTF-1 and were negative for CAM5.2, chromogranin-A, and NF. GFAP, vimentin, S100, galectin-3, EMA, and CD68 were variably positive in the majority of the 3 tumor groups. Olig2 was only positive in 1 pituicytoma. Whereas granular cell tumors were negative for bcl-2 and CD56, pituicytomas and spindle cell oncocytomas showed variable positivity. All tumors were negative with the IDH1-R132H mutation-specific antibody, and none had evidence of BRAF alterations (BRAF(V600E) mutation and BRAF-KIAA fusion). Diffuse TTF-1 expression in nontumorous pituicytes, pituicytomas, spindle cell oncocytomas, and granular cell tumors indicates a common pituicyte lineage. The ultrastructural variants of pituicytes are reflected in these 3 morphologic variants of tumors arising from these cells. We propose the terminology "oncocytic pituicytomas" and "granular cell pituicytomas" to refine the classification of these lesions.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".