Papillary renal neoplasm with reverse polarity is biologically and clinically distinct from eosinophilic papillary renal cell carcinoma
Bibliographic record
Abstract
Papillary renal neoplasm with reverse polarity (PRNRP) is a recently described indolent entity with distinct features and its recognition from other oncocytic/eosinophilic papillary renal cell carcinoma (ePRCC) has important prognostic implications. ABCC2, a renal drug transporter, is overexpressed in aggressive PRCCs. In this study, we compared the clinicopathological parameters and the biological ABCC2 expression between PRNRP and ePRCC. PRNRP (n = 8) and ePRCC (n = 21) cases were selected from resection specimens and corresponding clinicopathological data were collected. ABCC2 immunohistochemical (IHC) staining was performed and ABCC2 staining patterns were classified as negative, cytoplasmic, and brush-border. RNA in-situ hybridization (ISH) was used to assess ABCC2 transcript levels. All eight PRNRP cases had weak cytoplasmic ABCC2 IHC reactivity; however, they showed no detectable ABCC2 transcripts on RNA ISH. In comparison, 76% (16/21) of ePRCCs showed ABCC2 IHC brush-border expression and significantly higher ABCC2 RNA ISH transcript levels (p < 0.001). Additionally, the ePRCC group showed a significantly larger tumor size (p = 0.004), higher WHO/ISUP grade (p < 0.001), and stage (p = 0.044). None of the PRNRP cases showed disease progression, while 9.5% (2/21) ePRCCs had disease progression. PRNRP is clinically and biologically distinct from ePRCC. Hence, it is crucial to differentiate between these two entities, particularly in needle core biopsies.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".