Abstract 2293: A urine-based liquid biopsy method for detection of upper tract urinary carcinoma

Background: Upper tract urinary carcinoma (UTUC) includes renal pelvic cancer and ureteral cancer. For its diagnosis, ureteroscopy is the only method to obtain pathological result before surgery. However, there are also some problems with ureteroscopy. In addition to the trauma and infection risks, the possibility of exudation and adhesion of surrounding tissues after ureteroscopy is significantly increased, hypertension in the cavity may cause tumor spread, and the use of ureteroscopy and biopsy may cause recurrence of bladder tumors after surgery. These unfavorable factors make clinically urgent need for a sensitive and non-invasive method for the diagnosis of UTUC. Materials and Methods: In this study, 150 hematuria patients with upper tract urinary disease and 100 healthy people were enrolled. Among the patients, 75 were pathologically confirmed with upper tract urinary carcinoma while 75 with benign urinary diseases. A Genetron Urinary Assay was designed to maximize the number of unique driver gene variants of UTUC by a limited number of amplicons. Next-generation sequencing libraries were constructed using multiplex PCR methods. We also detected CpG-sites on ONECUT2 gene by performing bisulfite-specific real-time PCR for bisulfite converted DNA. Furthermore, we developed a prediction model based on several significant features to evaluate the risk of UTUC. Results: 234 samples were available for analysis. Our liquid biopsy assay demonstrated a sensitivity of 94%, a specificity of 96%, a positive predication value (PPV) of 92% and a negative predication value(NPV) of 98% in this study. By using a decision tree model, we found age, gene mutations of HRAS, TERT and TP53 and methylation of ONECUT2 did place at some key nodes to classify the risk of patients of UTUC, and age around 48.5, the frequencies of mutated genes above certain value and ΔCt value of ONECUT2 about 7.6 would be good cutoffs. This model was able to stratify patients into a low or high-risk group with an accuracy score at 94%. After further analysis, we found that ONECUT2 methylation and TP53 mutations were more common in high grade UTUC (p