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Record W1994503104 · doi:10.1097/pas.0b013e31802bdd56

Cystic Nephroma and Mixed Epithelial and Stromal Tumor of Kidney: A Detailed Clinicopathologic Analysis of 34 Cases and Proposal for Renal Epithelial and Stromal Tumor (REST) as a Unifying Term

2007· article· en· W1994503104 on OpenAlexaff
Julia Turbiner, Mahul B. Amin, Peter A. Humphrey, John R. Srigley, Laurence de Leval, Anuradha Radhakrishnan, Esther Oliva

Bibliographic record

VenueThe American Journal of Surgical Pathology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsMcMaster University
Fundersnot available
KeywordsStromal cellPathologyStromaImmunohistochemistryCuboidal CellHyalineMedicineAtypiaBiologyProgesterone receptorEstrogen receptorInternal medicineBreast cancerCancer

Abstract

fetched live from OpenAlex

Cystic nephroma (CN) and mixed epithelial and stromal tumor (MEST) are rare benign renal neoplasms that have overlapping clinical and morphologic features, including predominance in middle-aged women, variably cystic architecture, eosinophilic cells, and hobnail cells lining the cysts and ovarian-type stroma. The aim of this study was to analyze and compare the histologic features and immunohistochemical profile of these tumors. We studied 34 cases from 5 large academic institutions. Twenty tumors were diagnosed as CNs, 18 in women and 2 in men, their age ranged from 24 to 63 (mean 48; median 50) years. Fourteen tumors were diagnosed as MESTs, all in women, their age ranged from 26 to 84 (mean 52; median 51) years. Histologically, all tumors were well-circumscribed except for one MEST. The stromal/epithelial ratio was approximately 2.3 in MESTs versus 0.3 in CNs; cellular ovarian-type stroma composed 45% of the stroma in MESTs and 12% of the stroma of CNs. Stromal hyalinization was prominent in both. Five MESTs showed stromal luteinization. In the epithelial component, the relative amount of large cysts, medium to small cysts, and phyllodes-type glands was: 65%/25%/10% in CNs versus 25%/40%/35% in MESTs. The epithelial component ranged from flat to cuboidal to hobnail cells in both types of tumors. No significant atypia of either component was seen, although the epithelial cells showed reactive changes. Immunohistochemical stains for estrogen receptors and progesterone receptors showed 62% and 85% positivity in the stromal component of MESTs versus 19% and 40% in CNs. CD10 positivity was seen in 77% of MESTs versus 50% of CNs, calretinin was seen in 69% of MESTs versus 41% of CNs, and inhibin in 42% of MESTs versus 36% of CNs, although the staining was focal. Follow-up in both categories of tumors (mean 3.2 y, median 3 y for CNs and mean 2.5 y, median of 2 y for MESTs) showed no evidence of recurrence or metastases in keeping with their benign nature. This study highlights the remarkable similarity between CN and MEST in sex predilection, age distribution, and morphologic attributes of both the epithelial and stromal components and immunohistochemical profile albeit with variation in individual categories with higher prevalence of stromal to epithelial ratio, prominent ovarian stroma, smaller cysts with phyllodes glands pattern and stromal luteinization being more common in MEST; and large cysts, thin septae and low stromal to epithelial ratio in CN. The presence of ovarian-type stroma and müllerian related immunohistochemical markers raises the possibility that these tumors may originate from müllerian remnants misplaced during embryogenesis. On the basis of detailed morphologic analysis of this series of CN and MEST, we propose a unifying term of "renal epithelial and stromal tumor" (REST) to encompass the spectrum of findings observed in these tumors at least until new molecular studies can prove or disprove this challenging hypothesis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.276
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations203
Published2007
Admission routes1
Has abstractyes

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