MP15-02 A LNCRNA-BASED CLASSIFIER IDENTIFIES HIGH GRADE T1 BLADDER CANCER PATIENTS WITH EXCELLENT OUTCOMES AFTER RADICAL CYSTECTOMY

You have accessJournal of UrologyBladder Cancer: Basic Research & Pathophysiology I (MP15)1 May 2024MP15-02 A LNCRNA-BASED CLASSIFIER IDENTIFIES HIGH GRADE T1 BLADDER CANCER PATIENTS WITH EXCELLENT OUTCOMES AFTER RADICAL CYSTECTOMY Yair Lotan, Joep J. de Jong, James Proudfoot, Sia Daneshmand, Robert Svatek, Vikram Narayan, Shreyas Joshi, Roger Li, Brant Inman, Jonathan Wright, Paras Shah, and Ewan Gibb Yair LotanYair Lotan , Joep J. de JongJoep J. de Jong , James ProudfootJames Proudfoot , Sia DaneshmandSia Daneshmand , Robert SvatekRobert Svatek , Vikram NarayanVikram Narayan , Shreyas JoshiShreyas Joshi , Roger LiRoger Li , Brant InmanBrant Inman , Jonathan WrightJonathan Wright , Paras ShahParas Shah , and Ewan GibbEwan Gibb View All Author Informationhttps://doi.org/10.1097/01.JU.0001009500.87761.bf.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: In select patients with high grade (HG) clinical T1 non-muscle-invasive bladder cancer (NMIBC) radical cystectomy (RC) is a recommended therapy. However, even after radical surgery patients may experience disease recurrence, increasing the risk of cancer-related mortality. In previous work, a long non-coding RNA (lncRNA)-based classifier was developed to identify patients with favorable biology and excellent prognosis after RC in patients with muscle-invasive bladder cancer (MIBC). Here, we further evaluate this classifier in a cohort of patients with HG clinical T1 and T2 urothelial bladder tumors undergoing RC only. METHODS: Microarray data was analyzed from bladder tumor specimens resected transurethrally (TURBT) in two cohorts (MOLI n=206, MOLII n=200) of patients with high grade cT1-T2 N0M0 UC who subsequently underwent RC without neoadjuvant chemotherapy (NAC). Molecular subtypes were determined using the Decipher Bladder genomic subtyping classifier (GSC) [Seiler 2017, Batista da Costa 2019] and a lncRNA-based classifier was used to identify patients with good outcomes [de Jong et al, 2019]. The primary endpoints were overall survival (OS) and cancer specific mortality (CSM), quantified by Kaplan-Meier and cumulative incidence plots, respectively. RESULTS: In the MOLII cohort, molecular subtyping identified 51 (cT1=37, cT2=13) luminal-type FGFR3 active (FGFR3+) cases with high FGFR3, SHH and p53 pathway activity, and lower EMT hallmark scores. At five years, the freedom from event (FFE) rates for OS in the full cohort were 87% and 54% for FGFR3+ and FGFR3-, respectively. By stage, the T1 FGFR3+ patients had 97% vs 57% FFE rates compared to FGFR3- patients. In T2 patients, the FFE rate was 69% for FGFR3+ and 51% for FGFR3- tumors. For CSM, the event rates for the full cohort were 11% and 30% for FGFR3+ and FGFR3- cases, respectively. By stage, for T1 tumors, the rates were 0% for FGFR3+ and 21% for FGFR3-, compared to 31% and 38% for FGFR3- in T2 tumors. Similar patterns were seen for the MOLI cohort, but with less separation in event rates. CONCLUSIONS: Application of a lncRNA-based classifier to two cystectomy cohorts revealed that FGFR3+ patients with cT1 disease have excellent outcomes after RC, suggesting these less aggressive tumors are both organ-confined and readily cured with surgery alone. These findings represent a first step towards identifying cT1 patients with less favorable biology that may warrant systemic treatment before radical surgery. Source of Funding: Veracyte © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e229 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Yair Lotan More articles by this author Joep J. de Jong More articles by this author James Proudfoot More articles by this author Sia Daneshmand More articles by this author Robert Svatek More articles by this author Vikram Narayan More articles by this author Shreyas Joshi More articles by this author Roger Li More articles by this author Brant Inman More articles by this author Jonathan Wright More articles by this author Paras Shah More articles by this author Ewan Gibb More articles by this author Expand All Advertisement PDF downloadLoading ...