CDC73 mutations and parafibromin immunohistochemistry in parathyroid tumors: clinical correlations in a single-centre patient cohort
Bibliographic record
Abstract
OBJECTIVE: To determine if molecular and immunohistochemical (IHC) features of the HRPT2/CDC73 gene and its product, parafibromin, predict the natural history of parathyroid malignancy, particularly atypical adenoma, as seen in a single-centre patient cohort. METHODS: Matched tumor and non-tumor tissues were obtained from 46 patients with parathyroid carcinoma (CA) (n = 15), atypical adenoma (AA) (n = 14) and typical adenoma (TA) (n = 17), as defined by standardized histopathological criteria. Exons and exon-intron boundaries of the CDC73 gene were sequenced to identify germline or somatic mutations. IHC staining for parafibromin was performed and scored as positive if nuclear staining was at least partially IHC-positive. RESULTS: Mutations of CDC73 were observed in 9/15 (60 %) CA, 2/14 (14 %) AA, and 1/17 (6 %) TA tumors. A recurrent two basepair mutation in exon 7 -- c.679_680delAG -- accounted for half of all identified mutations. Absence of parafibromin nuclear staining was noted in 8/12 (67 %) CA, 2/13 (15 %) AA, and 3/17 (18 %) TA tumors. Median follow up times were 88 months for CA, 76 months for AA, and 104 months for TA patients. One patient, a member of a previously reported multiplex family with a germline CDC73 mutation was found to have a second adenoma after removal of an atypical adenoma. CONCLUSIONS: Molecular screening and IHC are both useful tools in the differential diagnosis of parathyroid tumors, but both have limited sensitivity and specificity. CDC73 mutations and negative immunostaining were common in atypical adenomas, but no local recurrence was observed in any case with successful surgical removal after follow-up periods of 27 to 210 months.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".