Expression of α-Methylacyl-CoA Racemase (P504S) in Nephrogenic Adenoma: A Significant Immunohistochemical Pitfall Compounding the Differential Diagnosis With Prostatic Adenocarcinoma
Bibliographic record
Abstract
Alpha-Methylacyl-CoA racemase (AMACR, P504S) has recently been shown to be a useful marker for the diagnosis of prostatic adenocarcinoma and a potential aid in its distinction from its many mimics, one of which is the benign lesion, nephrogenic adenoma (NA). The goal of this study was to assess the expression of AMACR in NA by immunohistochemistry, as well as other potentially useful markers, high-molecular-weight cytokeratin clone 34betaE12, p63, and prostate-specific antigen (PSA). AMACR was expressed in 4/4 NAs involving the prostatic urethra and underlying stroma, and in 3/16 NAs involving the bladder. The prostatic cases showed circumferential granular cytoplasmic AMACR expression of at least moderate intensity, in >75% of tubules in 3 cases and in <10% of tubules in the remaining case. The AMACR-positive cases in the bladder typically showed focal weak noncircumferential staining of the tubules and stronger staining of the cells lining the papillae. 34betaE12 staining was observed in 1/4 prostatic NAs and 4/16 bladder NAs, typically in a cytoplasmic pattern in a minority of cells. p63 and PSA were negative in all cases. Our data indicate that NA of the prostatic urethra commonly expresses AMACR and lacks basal cell-specific markers, making it not only a potential morphologic mimic of prostatic adenocarcinoma but also a significant immunohistochemical mimic as well. Awareness of NA as a significant pitfall in the diagnosis of prostatic adenocarcinoma and careful examination of hematoxylin and eosin-stained sections remains the key to the correct diagnosis, which can be supported by a negative PSA stain.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".