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UCseek: ultrasensitive early detection and recurrence monitoring of urothelial carcinoma by shallow-depth genome-wide bisulfite sequencing of urinary sediment DNA.
Wang, Ping; Shi, Yue; Zhang, Jianye; Shou, Jianzhong; Zhang, Mingxin; Zou, Daojia; Liang, Yuan; Li, Juan; Tan, Yezhen; Zhang, Mei; Bi, Xingang; Zhou, Liqun; Ci, Weimin; Li, Xuesong.
Afiliación
  • Wang P; Department of Urology, Peking University First Hospital, Beijing, 100034, China; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China; University of Chinese Academy of Sci
  • Shi Y; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
  • Zhang J; Department of Urology, Peking University First Hospital, Beijing, 100034, China; Institute of Urology, Peking University, Beijing, 100034, China.
  • Shou J; Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
  • Zhang M; Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, 266003, China.
  • Zou D; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
  • Liang Y; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
  • Li J; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
  • Tan Y; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
  • Zhang M; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
  • Bi X; Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. Electronic address: bixingang@csco.org.cn.
  • Zhou L; Department of Urology, Peking University First Hospital, Beijing, 100034, China; Institute of Urology, Peking University, Beijing, 100034, China; National Urological Cancer Center, Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, Beijing, 100034, China.
  • Ci W; CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China; Institute for Stem Cell and Regeneration, Chinese
  • Li X; Department of Urology, Peking University First Hospital, Beijing, 100034, China; Institute of Urology, Peking University, Beijing, 100034, China; National Urological Cancer Center, Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, Beijing, 100034, China.
EBioMedicine ; 89: 104437, 2023 Mar.
Article en En | MEDLINE | ID: mdl-36758479
BACKGROUND: Current methods for the detection and surveillance of urothelial carcinomas (UCs) are often invasive, costly, and not effective for low-grade, early-stage, and minimal residual disease (MRD) tumors. We aimed to develop and validate a model from urine sediments to predict different grade and stage UCs with low cost and high accuracy. METHODS: We collected 167 samples, including 90 tumors and 77 individuals without tumors, as a discovery cohort. We assessed copy number variations and methylation values for them and constructed a diagnostic classifier to detect UC, UCseek, by using an individual read-based method and support vector machine. The performance of UCseek was validated in an independent cohort derived from three hospitals (n = 206) and a relapse cohort (n = 42) for monitoring recurrence. FINDINGS: We constructed UCseek, which could predict UCs with high sensitivity (92.7%), high specificity (90.7%), and high accuracy (91.7%) in the independent validation set. The accuracy of UCseek in low-grade and early-stage patients reached 91.8% and 94.3%, respectively. Notably, UCseek retained great performance at ultralow sequencing depths (0.3X-0.5X). It also demonstrated a powerful ability to monitor recurrence in a surveillance cohort compared with cystoscopy (90.91% vs. 59.09%). INTERPRETATION: We optimized an improved approach named UCseek for the noninvasive diagnosis and monitoring of UCs in both low- and high-grade tumors and in early- and advanced-stage tumors, even at ultralow sequencing depths, which may reduce the burden of cystoscopy and blind second surgery. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgments section.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Vejiga Urinaria / Carcinoma de Células Transicionales Tipo de estudio: Clinical_trials / Diagnostic_studies / Prognostic_studies / Screening_studies Límite: Humans Idioma: En Revista: EBioMedicine Año: 2023 Tipo del documento: Article Pais de publicación: Países Bajos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Vejiga Urinaria / Carcinoma de Células Transicionales Tipo de estudio: Clinical_trials / Diagnostic_studies / Prognostic_studies / Screening_studies Límite: Humans Idioma: En Revista: EBioMedicine Año: 2023 Tipo del documento: Article Pais de publicación: Países Bajos