Single-Cell Sequencing-Enabled Hexokinase 2 Assay for Noninvasive Bladder Cancer Diagnosis and Screening by Detecting Rare Malignant Cells in Urine.

Document Type

Article

Publication Date

12-15-2020

Publication Title

Analytical chemistry

Abstract

Bladder cancer (BC) is among the most common tumors with a high recurrence rate, necessitating noninvasive and sensitive diagnostic methods. Accurate detection of exfoliated tumor cells (ETCs) in urine is crucial for noninvasive BC diagnosis but suffers from limited sensitivity when ETCs are rare and confounded by reactive, regenerative, or reparative cells. Single-cell sequencing (SCS) enables accurate detection of ETCs by surveying oncogenic driver mutations or genome-wide copy number alternations. To overcome the low-throughput limitation of SCS, we report a SCS-validated cellular marker, hexokinase 2 (HK2), for high-throughput screening cells in urine and detecting ETCs engaging elevated glycolysis. In the SCS-based training set, a total of 385 cells from urine samples of eight urothelial carcinoma (UC) patients were sequenced to establish a HK2 threshold that achieved >90% specificity for ETC detection. This urine-based HK2 assay was tested with a blinded patient group (n = 384) including UC and benign genitourinary disorders as a validation cohort for prospectively evaluating diagnostic accuracy. The sensitivity, specificity, positive predictive value, and negative predictive value of the assay were 90, 88, 83, and 93%, respectively, which were superior to urinary cytology. For investigating the potential to be a screening test, the HK2 assay was tested with a group of healthy individuals (n = 846) and a 6-month follow-up. The specificity was 98.4% in this health group. Three participants were found to have >5 putative ETCs that were sequenced to exhibit recurrent copy number alternations characteristic of malignant cells, demonstrating early BC detection before current clinical methods.

Clinical Institute

Cancer

Department

Oncology

Department

Institute for Systems Biology

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