PD52-02 FGFR3 MUTATIONS AND THEIR RELATION TO FGFR3 EXPRESSION AND CLINICAL OUTCOME IN A LARGE RADICAL CYSTECTOMY COHORT: IMPLICATIONS FOR ANTI-FGFR3 BLADDER CANCER TREATMENT?
Bibliographic record
Abstract
You have accessJournal of UrologyBladder Cancer: Invasive V (PD52)1 Apr 2019PD52-02 FGFR3 MUTATIONS AND THEIR RELATION TO FGFR3 EXPRESSION AND CLINICAL OUTCOME IN A LARGE RADICAL CYSTECTOMY COHORT: IMPLICATIONS FOR ANTI-FGFR3 BLADDER CANCER TREATMENT? Bas van Rhijn, Laura Mertens, Roman Mayr, Peter Bostrom, Mirari Marquez, Ellen Zwarthoff, Joost Boormans, Cheno Abas, Geert van Leenders, Stefanie Gotz, Simone Bertz, Yann Neuzillet, Joyce Sanders, Annegien Broeks, Michiel van der Heijden, Michael Jewett, Francisco Real, Robert Stohr, Alexandre Zlotta, Markus Eckstein, Yanish Scoorojebally, Max Burger, Wolfgang Otto, Francois Radvanyi, Nanour Sirab, Damien Pouessel, Theo van der Kwast, Nuria Malats, Arndt Hartmann, Yves Allory, Deric van der Schoot, and Tahlita Zuiverloon* Bas van RhijnBas van Rhijn More articles by this author , Laura MertensLaura Mertens More articles by this author , Roman MayrRoman Mayr More articles by this author , Peter BostromPeter Bostrom More articles by this author , Mirari MarquezMirari Marquez More articles by this author , Ellen ZwarthoffEllen Zwarthoff More articles by this author , Joost BoormansJoost Boormans More articles by this author , Cheno AbasCheno Abas More articles by this author , Geert van LeendersGeert van Leenders More articles by this author , Stefanie GotzStefanie Gotz More articles by this author , Simone BertzSimone Bertz More articles by this author , Yann NeuzilletYann Neuzillet More articles by this author , Joyce SandersJoyce Sanders More articles by this author , Annegien BroeksAnnegien Broeks More articles by this author , Michiel van der HeijdenMichiel van der Heijden More articles by this author , Michael JewettMichael Jewett More articles by this author , Francisco RealFrancisco Real More articles by this author , Robert StohrRobert Stohr More articles by this author , Alexandre ZlottaAlexandre Zlotta More articles by this author , Markus EcksteinMarkus Eckstein More articles by this author , Yanish ScoorojeballyYanish Scoorojebally More articles by this author , Max BurgerMax Burger More articles by this author , Wolfgang OttoWolfgang Otto More articles by this author , Francois RadvanyiFrancois Radvanyi More articles by this author , Nanour SirabNanour Sirab More articles by this author , Damien PouesselDamien Pouessel More articles by this author , Theo van der KwastTheo van der Kwast More articles by this author , Nuria MalatsNuria Malats More articles by this author , Arndt HartmannArndt Hartmann More articles by this author , Yves AlloryYves Allory More articles by this author , Deric van der SchootDeric van der Schoot More articles by this author , and Tahlita Zuiverloon*Tahlita Zuiverloon* More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000556958.45525.c0AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Fibroblast Growth Factor Receptor 3 (FGFR3) is a potentially actionable target in bladder cancer (BC). FGFR3 mutations are associated with favorable prognosis in non-muscle invasive (NMI) BC and MIBC. Over-expression of FGFR3 was reported in up to 40% of FGFR3 wild-type MIBC. p53 alterations rarely coincide with FGFR3 mutations. We analyzed FGFR3 mutations, protein-expression of FGFR3 and p53 and assessed their prognostic value in a multi-center, multi-laboratory setting. METHODS: We included 1000 cN0M0, chemotherapy-naive patients who underwent radical cystectomy (RC) with pelvic node dissection. Specimens were reviewed by eight uro-pathologists. At seven laboratories, FGFR3 mutation status was examined using PCR-SNaPshot. p53 and FGFR3 expression were determined by immunohistochemistry (IHC). FGFR3 mutation status, p53 and FGFR3 protein expressions were correlated to each-other, clinico-pathological parameters and disease-specific survival (DSS). RESULTS: FGFR3 mutations were found in 107/1000 RCs (11%), of which 67 were S249C. Over-expression of FGFR3 was found in 279/1000 (28%) of tumors. p53 overexpression (cut-off>10%) was found in 638/926 (69%) of available cases. Among FGFR3 mutant tumors, 73% had FGFR3 over-expression. Among FGFR3 wild-type tumors, 22% had FGFR3 over-expression. FGFR3 mutations were associated with lower pT-stage (P<0.001), lower grade (G2-WHO 1973) (P<0.001), absence of CIS (P=0.009), pN0 (P<0.001), normal p53 (P<0.001) and prolonged DSS (Plog-rank=0.001). FGFR3 over-expression was associated with lower pT-stage (P<0.001) and G2 (P<0.001) but not with absence of CIS (P=0.860), pN0 (P=0.230), normal p53 (P=0.330) nor prolonged DSS (Plog-rank=0.204). We found no significant difference in DSS for patients with FGFR3 mutant tumors comparing normal vs over-expression of FGFR3 (Plog-rank=0.444). Furthermore, we also found no significant difference in DSS for patients with FGFR3 wild-type tumors comparing normal vs over-expression of FGFR3 (Plog-rank=0.754). CONCLUSIONS: FGFR3 mutations identified patients with favorable BC with fewer p53 alterations at RC. FGFR3 over-expression was not associated with DSS in patients with FGFR3 wild-type tumors. Our results suggest that FGFR3 mutations (driver effect) have a distinct functional role than FGFR3 over-expression (passenger effect). Hence, patients with FGFR3 mutations may be more likely to benefit from anti-FGFR3 therapy than patients with only over-expression of FGFR3. Source of Funding: none Amsterdam, Netherlands; Regensburg, Germany; Turku, Finland; Madrid, Spain; Rotterdam, Netherlands; Regensburg, Germany; Erlangen, Germany; Amsterdam, Netherlands; Toronto, Canada; Madrid, Spain; Erlangen, Germany; Toronto, Canada; Erlangen, Germany; Paris, France; Regensburg, Germany; Paris, France; Toronto, Canada; Madrid, Spain; Erlangen, Germany; Paris, France; Breda, Netherlands; Rotterdam, Netherlands© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e924-e924 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Bas van Rhijn More articles by this author Laura Mertens More articles by this author Roman Mayr More articles by this author Peter Bostrom More articles by this author Mirari Marquez More articles by this author Ellen Zwarthoff More articles by this author Joost Boormans More articles by this author Cheno Abas More articles by this author Geert van Leenders More articles by this author Stefanie Gotz More articles by this author Simone Bertz More articles by this author Yann Neuzillet More articles by this author Joyce Sanders More articles by this author Annegien Broeks More articles by this author Michiel van der Heijden More articles by this author Michael Jewett More articles by this author Francisco Real More articles by this author Robert Stohr More articles by this author Alexandre Zlotta More articles by this author Markus Eckstein More articles by this author Yanish Scoorojebally More articles by this author Max Burger More articles by this author Wolfgang Otto More articles by this author Francois Radvanyi More articles by this author Nanour Sirab More articles by this author Damien Pouessel More articles by this author Theo van der Kwast More articles by this author Nuria Malats More articles by this author Arndt Hartmann More articles by this author Yves Allory More articles by this author Deric van der Schoot More articles by this author Tahlita Zuiverloon* More articles by this author Expand All Advertisement PDF downloadLoading ...
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".