Research
Scientists Develop A Liquid Biopsy Technique for the Diagnosis and Prognosis of Genitourinary Tumors
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By 2020 the estimated incidence of genitourinary (GU) cancers (such as kidney cancer, urothelial cancer and prostate cancer) will be over 2 million worldwide. The surgery can cure the majority of localized cancers without systemic therapy. However, the prognosis is poor when cancer metastasizes to distant sites. Therefore, detection and localization of GU cancers are key to improve the clinical outcome. Unfortunately, current biomarkers and diagnostic strategy are not sensitive enough and sometimes invasive.

A recent cooperative study led by Prof. CI Weimin from Beijing Institute of Genomics, Chinese Academy of Sciences, Prof. ZHOU Liqun and LI Xuesong from Peking University first hospital, Prof. HE Huiying from Peking University third hospital and Prof. ZHANG Bao from Beijing Aerospace Center Hospital developed a liquid biopsy technology for detection, localization and prognosis of genitourinary cancers. This work has been published in European Urology on November 17.

In this study, they developed an urine test, termed GUseek, using DNA methylomes and copy-number alterations (CNAs) by shallow whole-genome bisulfite sequencing of urinary sediment in 225 GU cancer patients (60 prostate cancer, 100 urothelial cancer, 65 kidney cancer patients) and 88 healthy individuals for detection and localization of GU cancers.

Firstly, they built binary classifiers which can accurately detect GU cancers from healthy individuals (AUC=0.972 for urothelial cancer, AUC=0.940 for prostate cancer, AUC=0.962 for kidney cancer).

They then built an ensemble classification system, GUseek, achieved a total accuracy of 90.57% with sensitivity of 100%, 100%, 80%, 72.73% in non-tumor, urothelial cancer, prostate cancer and kidney cancer cohorts, respectively.

Intriguingly, GUseek outperformed other 6 broadly used machine learning algorithms. Moreover, by integrating with TCGA clinical data, they constructed a prognostic prediction model that effectively predicted prognosis in both urothelial cancer and kidney cancer patients.

The study demonstrates the utility of urine sediment DNA methylation and CNA analysis in the diagnosis of GU cancers and represents a proof-of-concept for its use in prognosis of GU cancers.

This work was supported by CAS Strategic Priority Research Program, the National Key R&D Program of China, CAS, the National Natural Science Foundation of China, and K.C.Wong Education Foundation.

Methylome and copy number alteration (CNA) analysis (GUseek) of urine sediments for detection and classification of genitourinary (GU) cancers (Image by CI Weimin’s lab)

Contact
Prof. CI Weimin
Email: ciwm@big.ac.cn
CAS Key Laboratory of Genomic and Precision Medicine