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MP50-11 PARALLELS BETWEEN IMMUNOHISTOCHEMICAL CLASSIFICATION OF UPPER AND LOWER TRACT UROTHELIAL CARCINOMA USING MARKERS OF UROTHELIAL DIFFERENTIATION

2019· article· en· W2941837699 on OpenAlexaboutno aff
Tetsutaro Hayashi, Kazuhiro Sentani, Kenichiro Ikeda, Keisuke Goto, Htoo Zarni Oo, Hamidreza Abdi, Shunsuke Shinmei, Shogo Inoue, Jun Teishima, Wataru Yasui, Peter C. Black, Akio Matsubara

Bibliographic record

VenueThe Journal of Urology · 2019
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsUrothelial carcinomaMedicineImmunohistochemistryBladder cancerTransitional cell carcinomaPathologyCancerInternal medicine

Abstract

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You have accessJournal of UrologyBladder Cancer: Upper Tract Transitional Cell Carcinoma I (MP50)1 Apr 2019MP50-11 PARALLELS BETWEEN IMMUNOHISTOCHEMICAL CLASSIFICATION OF UPPER AND LOWER TRACT UROTHELIAL CARCINOMA USING MARKERS OF UROTHELIAL DIFFERENTIATION Tetsutaro Hayashi*, Kazuhiro Sentani, Kenichiro Ikeda, Keisuke Goto, Htoo Zarni Oo, Hamidreza Abdi, Shunsuke Shinmei, Shogo Inoue, Jun Teishima, Wataru Yasui, Peter C Black, and Akio Matsubara Tetsutaro Hayashi*Tetsutaro Hayashi* More articles by this author , Kazuhiro SentaniKazuhiro Sentani More articles by this author , Kenichiro IkedaKenichiro Ikeda More articles by this author , Keisuke GotoKeisuke Goto More articles by this author , Htoo Zarni OoHtoo Zarni Oo More articles by this author , Hamidreza AbdiHamidreza Abdi More articles by this author , Shunsuke ShinmeiShunsuke Shinmei More articles by this author , Shogo InoueShogo Inoue More articles by this author , Jun TeishimaJun Teishima More articles by this author , Wataru YasuiWataru Yasui More articles by this author , Peter C BlackPeter C Black More articles by this author , and Akio MatsubaraAkio Matsubara More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000556426.17926.c6AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Despite a similar histologic appearance, upper tract urothelial carcinoma (UTUC) and bladder cancer (BC) have some clinico-pathologic differences. Here we compared the immunohistochemical classification of UTUC and BC using the urothelial differentiation markers Uroplakin3 (UPK3), GATA3 and Cytokeratin5/6 (CK5/6). METHODS: The study population consisted of 120 patients with pTa-4 UTUC treated with radical nephroureterectomy without neoadjuvant chemotherapy. Tissue sections from nephroureterectomy were stained for UPK3, GATA3 and CK5/6. Positive staining for these markers was defined by any cancer cell staining for UPK3, >20% of cancer cells staining for GATA3, or all layers staining for CK5/6. We compared these results to a cohort of 115 patients with muscle invasive BC. RESULTS: In normal urothelium of upper urinary tract, UPK3 expression was observed only in umbrella cells, while CK5/6 expression was detected only in the basal layer. GATA3 expression was detected in almost all layers but its expression was highest in intermediate cells. These staining patterns were the same as those in BC. UPK3, GATA3, and CK5/6 were positive in 36 (30%), 105 (88%) and 27 (22%) of all UTUC cases, respectively. Almost all UPK3+ cases (94%) and CK5/6- cases (98%) were GATA3+. We therefore classified three groups: differentiated (DG: UPK3+; n=33), intermediate (IG: UPK3- and GATA3+; n=58) and undifferentiated (UG: GATA3- or CK5/6+; n=29). The rates of DG/IG/UG were 70/57/52% in papillary morphology (P=0.32), 3/5/17% in histological variants (P=0.07), 24/33/48% in histological grade 3 (P=0.13), and 33/59/62% in pT3-4 tumors (P=0.03), respectively. Similar correlations were observed for BC. Cancer specific survival (CSS) at 10 years in DG/IG/UG was 84/75/59% (P=0.14), with prognosis in DG better than UG (P=0.034). In multivariable analysis, histological grade 3(P<0.01), but not IHC classification (P=0.25), was an independent predictor of poor prognosis. The rates of FGFR3, HER2 and EGFR expression, which are potential therapeutic targets, were 39/40/10%, 15/26/3% and 9/10/21% in DG, IG and UG, respectively. FGFR3 and HER2 expression were higher in DG and IG (P=0.0046 and 0.022) than in UG, which demonstrated the same tendency in BC. CONCLUSIONS: The expression of urothelial differentiation markers was similar in both UTUC and BC. A simple IHC classification of UTUC may enhance patient risk stratification, which could be useful in clinical practice. Source of Funding: none Hiroshima, Japan; Vancouver, Canada; Hawaii, HI; Vancouver, Canada; Ottawa, Canada; Hiroshima, Japan; Vancouver, Canada; Hiroshima, Japan© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e718-e718 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Tetsutaro Hayashi* More articles by this author Kazuhiro Sentani More articles by this author Kenichiro Ikeda More articles by this author Keisuke Goto More articles by this author Htoo Zarni Oo More articles by this author Hamidreza Abdi More articles by this author Shunsuke Shinmei More articles by this author Shogo Inoue More articles by this author Jun Teishima More articles by this author Wataru Yasui More articles by this author Peter C Black More articles by this author Akio Matsubara More articles by this author Expand All Advertisement PDF downloadLoading ...

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)0.004
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 score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.023
GPT teacher head0.283
Teacher spread0.259 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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