Diagnostic and Prognostic Role of Immunohistochemical Expression of Napsin-A Aspartic Peptidase in Clear Cell and Papillary Renal Cell Carcinoma
Bibliographic record
Abstract
Napsin-A aspartic peptidase (napsin-A) is an aspartic protease that is predominantly expressed in the proximal renal tubules and type II pneumocytes of the lung. Recently, napsin-A was reported to be present in a proportion of renal cell carcinomas (RCCs). However, the utilization of napsin-A immunohistochemistry as a routine diagnostic tool for RCC, and the correlation of the level of napsin-A expression with histologic features have not yet been established. In the current study, using tissue microarrays composed of primary and metastatic RCCs, napsin-A expression was demonstrated in 86 of 222 (39%) clear cell RCCs (CRCCs) and 16 of 21 (76%) papillary RCCs (PRCCs), with a strong and diffuse staining pattern observed in PRCCs and a relatively weak and focal positivity in CRCCs. Compared with primary CRCCs, a comparable proportion of metastatic CRCCs retained napsin-A expression (45/132, 34%), suggesting the potential utility of napsin-A in the evaluation of metastatic tumors. The expression of napsin-A was also found to be inversely correlated to aggressive local tumor characteristics, such as advanced pathologic stage and high Fuhrman nuclear grade. We conclude that napsin-A may be a valuable immunohistochemical marker in the diagnosis of RCCs, particularly PRCC.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".