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ITDetect: a method to detect internal tandem duplication of FMS-like tyrosine kinase (FLT3) from next-generation sequencing data with high sensitivity and clinical application.
Lee, Sungyoung; Sun, Choong-Hyun; Jang, Heejun; Kim, Daeyoon; Yoon, Sung-Soo; Koh, Youngil; Na, Seung Chan; Cho, Sung Im; Kim, Man Jin; Seong, Moon-Woo; Byun, Ja Min; Yun, Hongseok.
Afiliación
  • Lee S; Department of Genomic Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
  • Sun CH; Center for Precision Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
  • Jang H; GenomeOpinion Inc., 117-3 Hoegiro, Dongdaemoon-gu, Seoul, Republic of Korea.
  • Kim D; Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Yoon SS; Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Koh Y; Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Na SC; Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
  • Cho SI; Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Kim MJ; Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
  • Seong MW; Department of Laboratory Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
  • Byun JM; Department of Laboratory Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
  • Yun H; Department of Genomic Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
BMC Bioinformatics ; 24(1): 62, 2023 Feb 23.
Article en En | MEDLINE | ID: mdl-36823555
ABSTRACT
Internal tandem duplication (ITD) of the FMS-like tyrosine kinase (FLT3) gene is associated with poor clinical outcomes in patients with acute myeloid leukemia. Although recent methods for detecting FLT3-ITD from next-generation sequencing (NGS) data have replaced traditional ITD detection approaches such as conventional PCR or fragment analysis, their use in the clinical field is still limited and requires further information. Here, we introduce ITDetect, an efficient FLT3-ITD detection approach that uses NGS data. Our proposed method allows for more precise detection and provides more detailed information than existing in silico methods. Further, it enables FLT3-ITD detection from exome sequencing or targeted panel sequencing data, thereby improving its clinical application. We validated the performance of ITDetect using NGS-based and experimental ITD detection methods and successfully demonstrated that ITDetect provides the highest concordance with the experimental methods. The program and data underlying this study are available in a public repository.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Leucemia Mieloide Aguda / Receptor 1 de Factores de Crecimiento Endotelial Vascular Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Leucemia Mieloide Aguda / Receptor 1 de Factores de Crecimiento Endotelial Vascular Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article