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?
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Résumé
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 ...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».