Clinico-Genomic Characterization of Patients with Metastatic Urothelial Carcinoma in Real-World Practice Identifies a Novel Bladder Immune Performance Index (BIPI)

Author:

Szabados Bernadett12,Ponz-Sarvisé Mariano3ORCID,Machado Robson4,Saldana Diego4,Kadel Edward E.5ORCID,Banchereau Romain6ORCID,Bouquet Fanny7,Garmhausen Marius8,Powles Thomas1ORCID,Schröder Carsten9ORCID,

Affiliation:

1. 1Barts Cancer Institute, Queen Mary University of London, London, United Kingdom.

2. 2Department of Urology, University College London Hospital, London, United Kingdom.

3. 3Medical Oncology Department, Clinica Universidad de Navarra and Program in Solid Tumors (CIMA), Universidad de Navarra, IDISNA, Pamplona, Spain.

4. 4Personalised Healthcare, Product Development, F. Hoffmann-La Roche Ltd., Basel, Switzerland.

5. 5US Medical Affairs and Oncology Biomarker Development, Genentech Inc., South San Francisco, California.

6. 6Oncology Biomarker Development, Genentech Inc., South San Francisco, California.

7. 7Global Product Development—Medical Affairs, F. Hoffmann-La Roche Ltd., Basel, Switzerland.

8. 8Personalised Healthcare, Data, Analytics and Imaging, Product Development, F. Hoffmann-La Roche Ltd., Basel, Switzerland.

9. 9Data & Statistical Sciences, Product Development, F. Hoffmann-La Roche Ltd., Basel, Switzerland.

Abstract

Abstract Purpose: This retrospective analysis of the largest available clinico-genomic database used de-identified patient-level electronic health record–derived real-world data (RWD) combined with FoundationOne comprehensive genomic profiling (CGP) to characterize patients with metastatic urothelial carcinoma (mUC) treated in the real-world setting, detect potential biomarkers, and develop a bladder immune performance index (BIPI). Experimental Design: Patients with mUC who started front-line single-agent immune checkpoint inhibitors (ICI) and an unmatched group treated with front-line platinum-based chemotherapy between January 1, 2011, and September 30, 2019, were selected. Clinical and genomic data were correlated with overall survival (OS). A novel BIPI predicting outcome with ICIs was developed using machine learning methods and validated using data from a phase II trial (NCT02951767). Results: In ICI-treated patients (n = 118), high tumor mutational burden (≥10 mutations/megabase) was associated with improved OS (HR, 0.58; 95% CI, 0.35–0.95; P = 0.03). In chemotherapy-treated patients (n = 268), those with high APOBEC mutational signature had worse OS (HR, 1.43; 95% CI, 1.06–1.94; P = 0.02). Neither FGFR3 mutations nor DNA damage–repair pathway alterations were associated with OS. A novel BIPI combining clinical and genomic variables (nonmetastatic at initial diagnosis, normal or above normal albumin level at baseline, prior surgery for organ-confined disease, high tumor mutational burden) identified ICI-treated patients with longest OS and was validated in an independent dataset. Conclusions: Contemporary RWD including FoundationOne CGP can be used to characterize outcomes in real-world patients according to biomarkers beyond PD-L1. A validated, novel clinico-genomic BIPI demonstrated satisfactory prognostic performance for OS in patients with mUC receiving front-line ICI therapy.

Publisher

American Association for Cancer Research (AACR)

Subject

Cancer Research,Oncology

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