Development and Multicenter Case–Control Validation of Urinary Comprehensive Genomic Profiling for Urothelial Carcinoma Diagnosis, Surveillance, and Risk-Prediction

Author:

Salari Keyan123ORCID,Sundi Debasish4ORCID,Lee Jason J.1ORCID,Wu Shulin5ORCID,Wu Chin-Lee5ORCID,DiFiore Gabrielle4ORCID,Yan Q. Robert6ORCID,Pienkny Andrew6ORCID,Lee Chi K.6ORCID,Oberlin Daniel6ORCID,Barme Greg6ORCID,Piser Joel6ORCID,Kahn Robert6ORCID,Collins Edward6ORCID,Phillips Kevin G.7ORCID,Caruso Vincent M.7ORCID,Goudarzi Mahdi7ORCID,Garcia-Ransom Monica7ORCID,Lentz Peter S.7ORCID,Evans-Holm Martha E.7ORCID,MacBride Andrew R.7ORCID,Fischer Daniel S.7ORCID,Haddadzadeh Iden J.7ORCID,Mazzarella Brian C.7ORCID,Gray Joe W.8ORCID,Koppie Theresa M.89ORCID,Bicocca Vincent T.7ORCID,Levin Trevor G.7ORCID,Lotan Yair10ORCID,Feldman Adam S.1ORCID

Affiliation:

1. 1Department of Urology, Massachusetts General Hospital, Boston, Massachusetts.

2. 2Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.

3. 3Broad Institute of MIT and Harvard, Cambridge, Massachusetts.

4. 4Department of Urology, The Ohio State University Comprehensive Cancer Center & Pelotonia Institute for Immuno-Oncology, Columbus, Ohio.

5. 5Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts.

6. 6Golden Gate Urology, Oakland, Berkeley and San Francisco, California.

7. 7Convergent Genomics, South San Francisco, California.

8. 8Oregon Health & Science University, Portland, Oregon.

9. 9Willamette Urology, Salem, Oregon.

10. 10Department of Urology, University of Texas Southwestern Medical Center Dallas, Dallas, Texas.

Abstract

Abstract Purpose: Urinary comprehensive genomic profiling (uCGP) uses next-generation sequencing to identify mutations associated with urothelial carcinoma and has the potential to improve patient outcomes by noninvasively diagnosing disease, predicting grade and stage, and estimating recurrence risk. Experimental Design: This is a multicenter case–control study using banked urine specimens collected from patients undergoing initial diagnosis/hematuria workup or urothelial carcinoma surveillance. A total of 581 samples were analyzed by uCGP: 333 for disease classification and grading algorithm development, and 248 for blinded validation. uCGP testing was done using the UroAmp platform, which identifies five classes of mutation: single-nucleotide variants, copy-number variants, small insertion-deletions, copy-neutral loss of heterozygosity, and aneuploidy. UroAmp algorithms predicting urothelial carcinoma tumor presence, grade, and recurrence risk were compared with cytology, cystoscopy, and pathology. Results: uCGP algorithms had a validation sensitivity/specificity of 95%/90% for initial cancer diagnosis in patients with hematuria and demonstrated a negative predictive value (NPV) of 99%. A positive diagnostic likelihood ratio (DLR) of 9.2 and a negative DLR of 0.05 demonstrate the ability to risk-stratify patients presenting with hematuria. In surveillance patients, binary urothelial carcinoma classification demonstrated an NPV of 91%. uCGP recurrence-risk prediction significantly prognosticated future recurrence (hazard ratio, 6.2), whereas clinical risk factors did not. uCGP demonstrated positive predictive value (PPV) comparable with cytology (45% vs. 42%) with much higher sensitivity (79% vs. 25%). Finally, molecular grade predictions had a PPV of 88% and a specificity of 95%. Conclusions: uCGP enables noninvasive, accurate urothelial carcinoma diagnosis and risk stratification in both hematuria and urothelial carcinoma surveillance patients.

Funder

National Cancer Institute

Publisher

American Association for Cancer Research (AACR)

Subject

Cancer Research,Oncology

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