Shuxiong Zeng1, Yidie Ying1, Naidong Xing2, Baiyun Wang3, Ziliang Qian3,4, Zunlin Zhou2, Zhensheng Zhang1, Weidong Xu1, Huiqing Wang1, Lihe Dai1, Li Gao5, Tie Zhou1, Jiatao Ji6, Chuanliang Xu7.
Abstract
PURPOSE: Urothelial carcinoma is a malignant cancer with frequent chromosomal aberrations. Here, we investigated the application of a cost-effective, low-coverage whole-genome sequencing technology in detecting all chromosomal aberrations. EXPERIMENTAL
DESIGN: Patients with urothelial carcinomas and nontumor controls were prospectively recruited in clinical trial NCT03998371. Urine-exfoliated cell DNA was analyzed by Illumina HiSeq XTen, followed by genotyping with a customized bioinformatics workflow named Urine Exfoliated Cells Copy Number Aberration Detector (UroCAD).
RESULTS: In the discovery phase, urine samples from 126 patients with urothelial carcinomas and 64 nontumor disease samples were analyzed. Frequent chromosome copy-number changes were found in patients with tumor as compared with nontumor controls. A novel diagnosis model, UroCAD, was built by incorporating all the autosomal chromosomal changes. The model reached performance of AUC = 0.92 (95% confidence interval, 89.4%-97.3%). At the optimal cutoff, |Z| ≥ 3.21, the sensitivity, specificity, and accuracy were 82.5%, 96.9%, and 89.0%, respectively. The prediction positivity was found correlated with tumor grade (P = 0.01). In the external validation cohort of 95 participants, the UroCAD assay identified urothelial carcinomas with an overall sensitivity of 80.4%, specificity of 94.9%, and AUC of 0.91. Meanwhile, UroCAD assay outperformed cytology tests with significantly improved sensitivity (80.4% vs. 33.9%; P < 0.001) and comparable specificity (94.9% vs. 100%; P = 0.49).
CONCLUSIONS: UroCAD could be a robust urothelial carcinoma diagnostic method with improved sensitivity and similar specificity as compared with cytology tests. It may be used as a noninvasive approach for diagnosis and recurrence surveillance in urothelial carcinoma prior to the use of cystoscopy, which would largely reduce the burden on patients. ©2020 American Association for Cancer Research.
PURPOSE: Urothelial carcinoma is a malignant cancer with frequent chromosomal aberrations. Here, we investigated the application of a cost-effective, low-coverage whole-genome sequencing technology in detecting all chromosomal aberrations. EXPERIMENTAL
DESIGN: Patients with urothelial carcinomas and nontumor controls were prospectively recruited in clinical trial NCT03998371. Urine-exfoliated cell DNA was analyzed by Illumina HiSeq XTen, followed by genotyping with a customized bioinformatics workflow named Urine Exfoliated Cells Copy Number Aberration Detector (UroCAD).
RESULTS: In the discovery phase, urine samples from 126 patients with urothelial carcinomas and 64 nontumor disease samples were analyzed. Frequent chromosome copy-number changes were found in patients with tumor as compared with nontumor controls. A novel diagnosis model, UroCAD, was built by incorporating all the autosomal chromosomal changes. The model reached performance of AUC = 0.92 (95% confidence interval, 89.4%-97.3%). At the optimal cutoff, |Z| ≥ 3.21, the sensitivity, specificity, and accuracy were 82.5%, 96.9%, and 89.0%, respectively. The prediction positivity was found correlated with tumor grade (P = 0.01). In the external validation cohort of 95 participants, the UroCAD assay identified urothelial carcinomas with an overall sensitivity of 80.4%, specificity of 94.9%, and AUC of 0.91. Meanwhile, UroCAD assay outperformed cytology tests with significantly improved sensitivity (80.4% vs. 33.9%; P < 0.001) and comparable specificity (94.9% vs. 100%; P = 0.49).
CONCLUSIONS: UroCAD could be a robust urothelial carcinoma diagnostic method with improved sensitivity and similar specificity as compared with cytology tests. It may be used as a noninvasive approach for diagnosis and recurrence surveillance in urothelial carcinoma prior to the use of cystoscopy, which would largely reduce the burden on patients. ©2020 American Association for Cancer Research.
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Year: 2020
PMID： 33037018 DOI： 10.1158/1078-0432.CCR-20-0401
Source DB: PubMed Journal: Clin Cancer Res ISSN： 1078-0432 Impact factor: 12.531