J Cancer 2016; 7(9):1044-1048. doi:10.7150/jca.14815 This issue

Research Paper

Genomic Profiling of Metastatic Gastroenteropancreatic Neuroendocrine Tumor (GEP-NET) Patients in the Personalized-Medicine Era

Seung Tae Kim, Su Jin Lee, Se Hoon Park, Joon Oh Park, Ho Yeong Lim, Won Ki Kang, Jeeyun Lee, Young Suk Park

Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

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Kim ST, Lee SJ, Park SH, Park JO, Lim HY, Kang WK, Lee J, Park YS. Genomic Profiling of Metastatic Gastroenteropancreatic Neuroendocrine Tumor (GEP-NET) Patients in the Personalized-Medicine Era. J Cancer 2016; 7(9):1044-1048. doi:10.7150/jca.14815. Available from https://www.jcancer.org/v07p1044.htm

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Background: We have conducted molecular profiling through a high-throughput molecular test as part of our clinical practice for patients with advanced gastrointestinal (GI) cancer or rare cancers including gastroenteropancreatic neuroendocrine tumors (GEP-NETs). Herein, we report on the molecular characterization of 14 metastatic GEP-NET patients.

Methods: We conducted the Ion AmpliSeq Cancer Hotspot Panel v2 (detecting 2,855 oncogenic mutations in 50 commonly mutated genes) and nCounter Copy Number Variation Assay, which was designed with 21 genes based on available targeted agents, as a high throughput genomic platform in 14 patients with metastatic GEP-NETs.

Results: Among the 14 GEP-NET patients analyzed in this study, 8 patients had grade III neuroendocrine carcinoma (NEC) and 6 had grade I/II NET. Primary sites included pancreas (n=3), small intestine and ascending colon (n=3), distal colon and rectum (n=5), and unknown primary origin (n=3). The most common metastatic site was the liver. Of 14 GEP-NET patients available for mutational profiling, 7 (50.0%) patients had one or more aberrations detected. Common aberrations were as follows: SMARCB1 mutation (n=2), TP53 mutation (n=2), STK11 mutation (n=1), RET mutation (n=1), and BRAF mutation (n=1). Gene amplification by nCounter was detected in only 1 patient, showing CCNE1 amplification, and this patient also had a TP53 mutation.

Conclusions: This high throughput genomic test may be useful to identify new drug targets in metastatic GEP-NET patients. Currently, we plan to conduct further genomic analysis to develop predictive and prognostic biomarkers in a larger number of GEP-NET patients.

Keywords: molecular profiling, Gastroenteropancreatic neuroendocrine tumor (GEP-NET)