The Morphologic and Immunohistochemical Spectrum of Papillary Renal Cell Carcinoma
Bibliographic record
Abstract
Papillary renal cell carcinomas (pRCC) are classically divided into type 1 and 2 tumors. However, many cases do not fulfill all the criteria for either type. We describe the clinical, morphologic, and immunohistochemical (IHC) features of 132 pRCCs to better characterize the frequency and nature of tumors with overlapping features. Cases were reviewed and classified; IHC evaluation of CK7, EMA, TopoIIα, napsin A, and AMACR was performed on 95 cases. The frequencies of type 1, type 2, and "overlapping" pRCC were 25%, 28%, and 47%, respectively. The 2 categories of "overlapping" tumors were: (1) cases with bland cuboidal cells but no basophilic cytoplasm (type A); and (2) cases with predominantly type 1 histology admixed with areas showing prominent nucleoli (type B). The pathologic stage of "overlapping" cases showed concordance with type 1 tumors. Using the 2 discriminatory markers (CK7, EMA), "type A" cases were similar to type 1. Although the high-nuclear grade areas of "type B" tumors showed some staining differences from their low-nuclear grade counterpart, their IHC profile was closer to type 1. Single nucleotide polymorphism array results, although preliminary and restricted to only 9 cases (3 with overlapping features), also seemed to confirm those findings. In conclusion, we demonstrate that variations in cytoplasmic quality and/or presence of high-grade nuclei in tumors otherwise displaying features of type 1 pRCCs are similar in stage and IHC profile those with classic type 1 histology, suggesting that their spectrum might be wider than originally described.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".