Journal
GUT
Volume 69, Issue 5, Pages 877-887Publisher
BMJ PUBLISHING GROUP
DOI: 10.1136/gutjnl-2018-317233
Keywords
-
Categories
Funding
- Chinese Academy of Medical Sciences Initiative for Innovative Medicine (CAMS-I2M) [2017-I2M-1-001]
- National Natural Science Foundation of China (NSFC) [81573009, 81773292, 81603157]
- PUMCH Science Fund for Junior Faculty [JQ201507, pumch-2016-2.22]
- Science, Technology and Innovation Commission of Shenzhen Municipality [JCYJ20160531193931852]
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available