Detection of early-stage urothelial cancers using methylation patterns in urine cell-free DNA.

T Tyler F. Stewart (Department of Medicine, UC San Diego Moores Cancer Center, San Diego, CA) A Archana Shenoy (GRAIL, Inc, Menlo Park, CA) R Rojin Safavi (GRAIL, Inc, Menlo Park, CA) S Sarah Stuart (GRAIL, Inc, Menlo Park, CA) K Kelly McClintock (GRAIL, Inc, Menlo Park, CA) A Amani Alchaar (GRAIL, Inc, Menlo Park, CA) A Aditya Bagrodia (UC San Diego Health, La Jolla, CA, 92093) K Karim Kader (Moores Cancer Center, University of California San Diego, La Jolla, CA) R Rana R. McKay (Department of Medicine, Urology, and Radiation Medicine and Applied Sciences University of California‐San Diego La Jolla California USA) N Neil Recio (Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada) H Heidi Wagner (Division of Urologic Oncology, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada) N Neil Eric Fleshner (Division of Urologic Oncology, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada) M Matthew H. Larson (GRAIL, Inc, Menlo Park, CA) A Amirali Salmasi (Department of Urology, University of California, San Diego, San Diego, CA)

Abstract

687 Background: Urine cell-free DNA (ucfDNA) has the potential to improve detection and monitoring of early-stage urothelial carcinoma (UC). We previously demonstrated the utility of ucfDNA methylation patterns to detect non-muscle invasive bladder cancer (NMIBC) in patients with suspicious bladder lesions (by cystoscopy or imaging). Based on those results, we trained a biopsy-free urine classifier for cancer detection. Here, we evaluate the performance of the urine classifier in an independent test set of patients with early-stage NMIBC or upper tract UC (UTUC). Methods: The urine classifier was trained using GRAIL’s biobank of plasma and cancer tissue, as well as prospectively collected urine from cancer and non-cancer participants (urine samples, n = 468). The locked classifier was evaluated at 95% and 98% target specificities on an independent test set of biobanked urine from patients with a new diagnosis of NMIBC (n = 49, 24 low grade and 25 high grade) and UTUC (n = 19, 9 low grade and 10 high grade), as well as age- and gender-matched non-cancer controls (n = 66). Results: The observed specificities in the test set at target specificities of 95% and 98% were 93.9% (62/66, 95% CI 85.2-98.3%) and 97.0% (64/66, 95% CI 89.5-99.6%), respectively. Observed sensitivity was the same at both target specificities. Of the 68 patients with a new diagnosis of either NMIBC or UTUC, 57 were classified as cancer, while 11 were classified as non-cancer. The urine classifier had a sensitivity of 100% for high grade NMIBC (25/25; 95% CI 86.3-100%) and 58.3% for low grade NMIBC (14/24; 95% CI 36.6-77.9%). For patients with UTUC, the urine classifier had a sensitivity of 100% for high grade UTUC (10/10; 95% CI 69.2-100%) and 88.9% for low grade UTUC (8/9; 95% CI 51.8-99.7%). Conclusions: A biopsy-free urine classifier based on ucfDNA methylation patterns is able to identify early-stage NMIBC and UTUC with high sensitivity at high specificity, particularly for patients with high grade disease. The classifier performance was validated in urine with an independent test set and did not require matched blood or tissue, highlighting the potential for a non-invasive and cost-effective method for UC screening. Current efforts are focused on evaluating urine classifier performance in prospective cohorts of UC patients undergoing both screening and recurrence monitoring.

Article Details

Volume / Issue Vol. 43, Issue 5_suppl
Published February 10, 2025
Pages 687-687
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (14)

T

Tyler F. Stewart

Department of Medicine, UC San Diego Moores Cancer Center, San Diego, CA

A

Archana Shenoy

GRAIL, Inc, Menlo Park, CA

R

Rojin Safavi

GRAIL, Inc, Menlo Park, CA

S

Sarah Stuart

GRAIL, Inc, Menlo Park, CA

K

Kelly McClintock

GRAIL, Inc, Menlo Park, CA

A

Amani Alchaar

GRAIL, Inc, Menlo Park, CA

A

Aditya Bagrodia

UC San Diego Health, La Jolla, CA, 92093

K

Karim Kader

Moores Cancer Center, University of California San Diego, La Jolla, CA

R

Rana R. McKay

Department of Medicine, Urology, and Radiation Medicine and Applied Sciences University of California‐San Diego La Jolla California USA

N

Neil Recio

Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada

H

Heidi Wagner

Division of Urologic Oncology, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada

N

Neil Eric Fleshner

Division of Urologic Oncology, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada

M

Matthew H. Larson

GRAIL, Inc, Menlo Park, CA

A

Amirali Salmasi

Department of Urology, University of California, San Diego, San Diego, CA