Whole-exome sequencing of calcitonin-producing pancreatic neuroendocrine neoplasms indicates a unique molecular signature

INTRODUCTION: Calcitonin-producing pancreatic neuroendocrine neoplasms (CT-pNENs) are an extremely rare clinical entity, with approximately 60 cases reported worldwide. While CT-pNENs can mimic the clinical and diagnostic features of medullary thyroid carcinoma, their molecular profile is poorly understood. METHODS: Whole-exome sequencing (WES) was performed on tumor and corresponding serum samples of five patients with increased calcitonin serum levels and histologically validated calcitonin-positive CT-pNENs. cBioPortal analysis and DAVID gene enrichment analysis were performed to identify dysregulated candidate genes compared to control databases. Immunohistochemistry was used to detect the protein expression of MUC4 and MUC16 in CT-pNEN specimens. RESULTS: Mutated genes known in the literature in pNENs like MEN1 (35% of cases), ATRX (18-20% of cases) and PIK3CA (1.4% of cases) were identified in cases of CT-pNENs. New somatic SNVs in ATP4A, HES4, and CAV3 have not been described in CT- pNENs, yet. Pathogenic germline mutations in FGFR4 and DPYD were found in three of five cases. Mutations of CALCA (calcitonin) and the corresponding receptor CALCAR were found in all five tumor samples, but none of them resulted in protein sequelae or clinical relevance. All five tumor cases showed single nucleotide variations (SNVs) in MUC4, and four cases showed SNVs in MUC16, both of which were membrane-bound mucins. Immunohistochemistry showed protein expression of MUC4 in two cases and MUC16 in one case, and the liver metastasis of a third case was double positive for MUC4 and MUC16. The homologous recombination deficiency (HRD) score of all tumors was low. DISCUSSION: CT-pNENs have a unique molecular signature compared to other pNEN subtypes, specifically involving the FGFR4, DPYD, MUC4, MUC16 and the KRT family genes. However, a major limitation of our study was the relative small number of only five cases. Therefore, our WES data should be interpreted with caution and the mutation landscape in CT-pNENs needs to be verified by a larger number of patients. Further research is needed to explain differences in pathogenesis compared with other pNENs. In particular, multi-omics data such as RNASeq, methylation and whole genome sequencing could be informative.