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Whole-genome sequencing reveals distinct genetic bases for insulinomas and non-functional pancreatic neuroendocrine tumours: leading to a new classification system

OBJECTIVE: Insulinomas and non-functional pancreatic neuroendocrine tumours (NF-PanNETs) have distinctive clinical presentations but share similar pathological features. Their genetic bases have not been comprehensively compared. Herein, we used whole-genome/whole-exome sequencing (WGS/WES) to ident...

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Detalles Bibliográficos
Autores principales: Hong, Xiafei, Qiao, Sitan, Li, Fuqiang, Wang, Wenze, Jiang, Rui, Wu, Huanwen, Chen, Hao, Liu, Lulu, Peng, Junya, Wang, Jing, Jia, Congwei, Liang, Xiaolong, Dai, Hongmei, Jiang, Jialin, Zhang, Taiping, Liao, Quan, Dai, Menghua, Cong, Lin, Han, Xianlin, Guo, Dan, Liang, Zhiyong, Li, Dongjing, Zheng, Zetian, Ye, Chen, Li, Siliang, Zhao, Yupei, Wu, Kui, Wu, Wenming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7229893/
https://www.ncbi.nlm.nih.gov/pubmed/31462556
http://dx.doi.org/10.1136/gutjnl-2018-317233
Descripción
Sumario:OBJECTIVE: Insulinomas and non-functional pancreatic neuroendocrine tumours (NF-PanNETs) have distinctive clinical presentations but share similar pathological features. Their genetic bases have not been comprehensively compared. Herein, we used whole-genome/whole-exome sequencing (WGS/WES) to identify genetic differences between insulinomas and NF-PanNETs. DESIGN: The mutational profiles and copy-number variation (CNV) patterns of 211 PanNETs, including 84 insulinomas and 127 NF-PanNETs, were obtained from WGS/WES data provided by Peking Union Medical College Hospital and the International Cancer Genome Consortium. Insulinoma RNA sequencing and immunohistochemistry data were assayed. RESULTS: PanNETs were categorised based on CNV patterns: amplification, copy neutral and deletion. Insulinomas had CNV amplifications and copy neutral and lacked CNV deletions. CNV-neutral insulinomas exhibited an elevated rate of YY1 mutations. In contrast, NF-PanNETs had all three CNV patterns, and NF-PanNETs with CNV deletions had a high rate of loss-of-function mutations of tumour suppressor genes. NF-PanNETs with CNV alterations (amplification and deletion) had an elevated risk of relapse, and additional DAXX/ATRX mutations could predict an increased relapse risk in the first 2-year period. CONCLUSION: These WGS/WES data allowed a comprehensive assessment of genetic differences between insulinomas and NF-PanNETs, reclassifying these tumours into novel molecular subtypes. We also proposed a novel relapse risk stratification system using CNV patterns and DAXX/ATRX mutations.