Fluorescent In-situ Hybridization Study of Non-papillary Oncocytic/Eosinophilic Renal Cell Carcinoma
Bibliographic record
Abstract
AIMS: Papillary renal cell carcinoma (PRCC) and clear cell RCC (CRCC) can display extensive areas with oncocytic/eosinophilic changes and may be associated with either minimal papillary architecture. These nonpapillary oncocytic/eosinophilic RCC often mimic renal oncocytoma (RO). We investigated numeric changes of chromosomes 7, 17, and Y and loss of the small arm of chromosome 3 in the above-mentioned oncocytic RCC by using the florescent in-situ hybridization (FISH). MATERIALS AND METHODS: Archival cases of oncocytic RCC previously screened by immunohistochemical study were submitted for FISH. RESULTS: There were a total of 9 cases out of a total of 650 renal carcinomas surgically resected. Seven tumors displayed an immunoprofile of CRCC or PRCC with RCC(+)/CD117(-) and variable reactivity for CK7 and α-methylacyl-CoA racemase. FISH showed trisomies 7/17 with or without loss of Y in 5 tumors. Loss of loci 3p25 and 3p14 was identified in another 2 cases. The remaining 2 carcinomas previously reported as malignant RO owing to cytological atypia and lymph node metastasis showed immunoprofile of RCC(-)/CD117(+) and absence of numeric changes for chromosomes 7, 17, and Y or loss of loci 3p25 or 3p14. CONCLUSIONS: In this uncommon variant of RCC, FISH for chromosomes 7, 17, and Y lend more support for the role of immunostaining in distinguishing RO and chromophobe RCC from the nonchromophobe RCC. FISH for chromosomes 7, 17, Y, and loci 3p25 and 3p14, and not immunostaining for α-methylacyl-CoA racemase and CK7 is helpful in distinguishing CRCC from PRCC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".