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Podium 4: Oncology – Other





                                                             POD-4.4
                                                             A renal tumor prediction tool using the Canadian Kidney Cancer
                                                             information system
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                                                             Ameeta Nayak , Luke T. Lavallée , Ranjeeta Mallick , Simon Tanguay ,
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                                                             Antonio Finelli , Anil Kapoor , Alan I. So , Bimal Bhindi , Ricardo A.
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                                                             Rendon , Adrian Fairey , Frédéric Pouliot , Lori A. Wood , Rodney H.
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                                                             Breau 2
                                                             1 Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada;  Division
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                                                             of Urology, University of Ottawa, Ottawa, ON, Canada;  Division of
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                                                             Urology, McGill University, Montreal, QC, Canada;  Division of Urology,
                                                             University of Toronto, Toronto, ON, Canada;  Division of Urology, McMaster
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                                                             University, Hamilton, ON, Canada;  Department of Urologic Sciences,
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                                                             University of British Columbia, Vancouver, BC, Canada;  Department
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                                                             of Urology, Mayo Clinic, Rochester, MN, United States;  Department of
                                                             Urology, Dalhousie University, Halifax, NS, Canada;  Division of Urology,
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                                                             University of Alberta, Edmonton, AB, Canada;  Division of Urology,
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                                                             Université Laval, Quebec City, ON, Canada;  Division of Medical
                                                             Oncology, Dalhousie University, Halifax, NS, Canada
                                                             Introduction: With the increased use of cross-sectional images, inciden-
                                                             tal kidney tumors are frequently discovered. However, many surgically
                                                             removed kidney tumors are found to be benign, and some cancerous
                                                             tumors are not aggressive and may not require treatment. We sought to
                                                             determine the clinical and radiographical predictive factors of kidney
                                                             tumor malignancy and develop a nomogram to distinguish between
                                                             benign and malignant renal masses.
                                                             Methods: Patients diagnosed with solitary renal masses were identi-
        POD-4.3. Fig. 1. The prognostic and predictive implications of 12-CK score.   fied from the Canadian Kidney Cancer information system (CKCis).
        Kaplan-Meier survival analyses revealed improved (A) PFS (HR 0.29; p=0.004);   Demographic, clinical, and imaging data were compared to the patho-
        (B) DSS (HR 0.29; p=0.004); and (C) OS (HR 0.55; p=0.03) in 12-CK-high MIBC   logical diagnosis from surgery or biopsy. Tumors were categorized into
        patients treated with radical cystectomy at Moffitt Cancer Center. The favor-  malignant or benign, and aggressive (high-grade malignant) or indolent
        able prognosis in (D) PFS (HR 0.55; p=0.007); (E) DSS (HR 0.40; p=0.002); and   (low-grade malignant and benign). Logistic regression models were con-
                                                             structed to identify predictors of each category. Nomograms were created
        (F) OS (HR 0.59; p=0.01) were confirmed in patients from TCGA. (G) From the   using statistically significant risk factors and were internally validated
        INVIGOR-210 study testing the efficacy of atezolizumab in chemotherapy-  using bootstrap methods.
        refractory locally advanced or metastatic bladder cancer patients, complete   Results: Of 3991 patients diagnosed with a solitary kidney tumor between
        responders were found to have significantly higher 12-CK scores than the   2011 and 2017, 93% patients had malignant tumors and 43% had high-
        other cohorts. (H) Stratified by the 12-CK score, 12-CK-high patients were   grade tumors. Factors associated with cancer and high-grade cancer were
        found to have an 11.2-month OS benefit (19.1 vs. 7.9 months) after treatment   age (odds ratio [OR] 0.99; 95% confidence interval [CI] 0.98–1.00; OR
        using atezolizumab.  p<0.05;  p<0.01;  p<0.001.      1.01, 95% CI 1.00–1.02, respectively) and tumor size (OR 1.25; 95%
                     *
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                                                             CI 1.18–1.32; OR 1.28; 95% CI 1.25–1.31, respectively). Male sex was
        developed TLSs. Chi-squared and Fisher exact was used to compare   also predictive of high-grade cancer (OR 1.48; 95% CI 1.26–1.73). The
        immune cell infiltrates type I-III TLSs 12-CKHi vs. 12-CKLo. Finally, we   nomograms were able to discriminate between malignant/benign tumors
        examined the association between high 12-CK scores and response to   (area under the curve [AUC] 0.71;  95%CI 0.68–0.74), and aggressive/
        atezolizumab in the IMVIGOR 210 study                indolent tumors (AUC 0.77; 95% CI 0.75–0.78).
        Results: Twenty-five (19.2%) of patients were categorized as 12-CKHi.   Conclusions: Patient and tumor characteristics are independently associ-
        Pathological review of 43 bladder tumor specimens confirmed higher   ated with cancer risk and high-grade cancer risk. The CKCis nomograms
        levels of type III TLSs (p=0.02) and immune cell infiltrates CD4 (p=0.1),   presented have good discriminative accuracy and this prediction tool can
        CD8 (p=0.02), CD20 (0.008), and LAMP3 (0.047) in 12-CKHi patients.   be used by physicians and patients with kidney tumors to help determine
        12-CK had improved progression-free survival (PFS, p=0.004), disease-  an optimal management plan.
        specific survival (DSS, p=0.004), and overall survival  (OS, p=0.03) in the
        Moffitt cohort (Figs. 1A–C) These findings were confirmed in the TCGA   POD-4.5
        BLCA (Figs. 1D–F). With the IMvigor 210 trial, 12-CK-Hi patients had   Trimodal therapy vs. radical cystectomy for T2 bladder cancer:
        an 11.2-month OS, suggesting it as a potential marker for ICB response.   Real-world evidence from Ontario
        Conclusions: This is the first study to link high 12-CK scores to the pres-  Marian S. Wettstein 1,2,3 , Alejandro Berlin , Song Pham , Srikala S. Sridhar ,
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        ence of TLSs in the TME of bladder cancer and is associated with better   Peter Chung , Shabbir M.H. Alibhai , Theodorus van der Kwast , Syed
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        patient survival outcome and response to ICB. This 12-CK score may prove   R. Qadri , Kathy Li , Ning Liu , Thomas Hermanns , Girish S. Kulkarni 1,2
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        to be a useful prognostic marker in bladder cancer.  1 Division of Urology, Department of Surgery, Princess Margaret Cancer
                                                             Centre, University Health Network, University of Toronto, Toronto, ON,
                                                             Canada;  ICES, Toronto, ON, Canada;  Department of Urology, University
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                                                             Hospital of Zurich, University of Zurich, Zurich, Switzerland;  Radiation
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                                                             Medicine Program, Princess Margaret Cancer Centre, University Health
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                                                             Network, University of Toronto, Toronto, ON, Canada;  Division of
                                                             Medical Oncology, Department of Medicine, Princess Margaret Cancer
                                                             Centre, University Health Network, University of Toronto, Toronto, ON,
                                                             Canada;  Division of Geriatric Medicine, Department of Medicine,
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                                                             Princess Margaret Cancer Centre, University Health Network, University
                                                             of Toronto, Toronto, ON, Canada;  Department of Pathology, Princess
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                                                CUAJ • June 2020 • Volume 14, Issue 6(Suppl2)                S39
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