Pancreatic Disorders & Therapy

Pancreatic Disorders & Therapy
Open Access

ISSN: 2165-7092

+44 7868 792050


Alterations in Cancer-related Genes Associated with Grading of Well Differentiated Pancreatic Neuroendocrine Neoplasms

Yudai Yokota, Mitsuharu Fukasawa, Shinichi Takano, Hiroko Shindo, Ei Takahashi, Makoto Kadokura, Kunio Mochizuki, Shinya Maekawa, Jun Itakura, Hideki Fujii, Tadashi Sato and Nobuyuki Enomoto

Objectives: Although recent advances in next-generation sequencing (NGS) have revealed some genetic alterations in various tumors, including pancreatic neuroendocrine tumors (PanNETs), their clinical significance is not fully understood. To investigate the clinical significance of gene alteration in PanNETs, we performed genetic analysis of well differentiated PanNETs using NGS.

Methods: Twenty-nine resected primary PanNET tissue samples and three samples of metastatic liver tissues, obtained from 29 PanNET patients, were analyzed. DNA was extracted from laser-captured formalin-fixed paraffinembedded tissues, and 50 cancer-associated genes, including approximately 2,800 hotspots, were amplified by multiplex PCR. Amplified libraries were sequenced using NGS, and the results were analyzed in conjunction with respective clinicopathological features.

Results: Among 50 investigated genes, somatic mutations were observed in four of 29 PanNET cases. We identified APC mutations in three cases, PTEN in two, and VHL and STK11 in one. The identified mutations were observed only in NET G2 tumors. All liver metastases contained at least one mutation, such as PTEN or TP53, which was not observed in the primary tumor.

Conclusion: The cancer-related gene mutations observed in PanNETs were associated with G2 grade tumors. The mutations were more frequent in PanNET liver metastasis than in the primary tumors. Our analysis of liver metastasis cases suggested that cancer-related gene mutations might raise the tumor grade and promote liver metastasis. Further studies of associations between genetic alterations and clinicopathological features should help in the cancer diagnosis and prediction of therapeutic effects of molecular-target drugs.

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