A Urine-Based Liquid Biopsy Method for Detection of Upper Tract Urinary Carcinoma

Yansheng Xu; Xin Ma; Xing Ai; Jiangping Gao; Yiming Liang; Qin Zhang; Tonghui Ma; Kaisheng Mao; Qiaosong Zheng; Sizhen Wang; Yuchen Jiao; Xu Zhang; Hongzhao Li

doi:10.3389/fonc.2020.597486

A Urine-Based Liquid Biopsy Method for Detection of Upper Tract Urinary Carcinoma

Front Oncol. 2021 Feb 9:10:597486. doi: 10.3389/fonc.2020.597486. eCollection 2020.

Authors

Yansheng Xu^{1

2}, Xin Ma¹, Xing Ai³, Jiangping Gao⁴, Yiming Liang⁵, Qin Zhang⁵, Tonghui Ma⁵, Kaisheng Mao⁵, Qiaosong Zheng⁵, Sizhen Wang⁵, Yuchen Jiao⁶, Xu Zhang¹, Hongzhao Li¹

Affiliations

¹ Department of Urology, The First Medical Center of Chinese PLA General Hospital, Beijing, China.
² Department of Urology, The Sixth Medical Center of Chinese PLA General Hospital, Beijing, China.
³ Department of Urology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, China.
⁴ Department of Urology, The Fourth Medical Center of Chinese PLA General Hospital, Beijing, China.
⁵ Genetron Health (Beijing) Technology, Co. Ltd., Beijing, China.
⁶ State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Abstract

Background: Conventional clinical detection methods such as CT, urine cytology, and ureteroscopy display low sensitivity and/or are invasive in the diagnosis of upper tract urinary carcinoma (UTUC), a factor precluding their use. Previous studies on urine biopsy have not shown satisfactory sensitivity and specificity in the application of both gene mutation or gene methylation panels. Therefore, these unfavorable factors call for an urgent need for a sensitive and non-invasive method for the diagnosis of UTUC.

Methods: In this study, a total of 161 hematuria patients were enrolled with (n = 69) or without (n = 92) UTUC. High-throughput sequencing of 17 genes and methylation analysis for ONECUT2 CpG sites were combined as a liquid biopsy test panel. Further, a logistic regression prediction model that contained several significant features was used to evaluate the risk of UTUC in these patients.

Results: In total, 86 UTUC- and 64 UTUC+ case samples were enrolled for the analysis. A logistic regression analysis of significant features including age, the mutation status of TERT promoter, and ONECUT2 methylation level resulted in an optimal model with a sensitivity of 94.0%, a specificity of 93.1%, the positive predictive value of 92.2% and a negative predictive value of 94.7%. Notably, the area under the curve (AUC) was 0.957 in the training dataset while internal validation produced an AUC of 0.962. It is worth noting that during follow-up, a patient diagnosed with ureteral inflammation at the time of diagnosis exhibiting both positive mutation and methylation test results was diagnosed with ureteral carcinoma 17 months after his enrollment.

Conclusion: This work utilized the epigenetic biomarker ONECUT2 for the first time in the detection of UTUC and discovered its superior performance. To improve its sensitivity, we combined the biomarker with high-throughput sequencing of 17 genes test. It was found that the selected logistic regression model diagnosed with ureteral cancer can evaluate upper tract urinary carcinoma risk of patients with hematuria and outperform other existing panels in providing clinical recommendations for the diagnosis of UTUC. Moreover, its high negative predictive value is conducive to rule to exclude patients without UTUC.

Keywords: hematuria; liquid biopsy; logistic regression model; methylation; next-generation sequencing; upper tract urinary carcinoma.