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Circulating Gene Expression Assay as a Diagnostic and Prognostic Biomarker for Pancreatic Neuroendocrine Tumors in
Eline N M van Vliembergen1,2, Mark J C van Treijen1,3, Rachel S van Leeuwaarde1,3
1Department of Endocrine Oncology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands.
Objective:
There is an unmet need for biomarkers in multiple endocrine neoplasia type 1 (MEN1)-related pancreatic neuroendocrine tumors (PanNETs) that allow prediction of clinical behaviour and metastatic potential. This study aims to investigate the potential of a circulating NET mRNA gene expression assay as a diagnostic and prognostic biomarker.
Design:
Single-center, prospective, cohort study.
Methods:
MEN1 patients were enrolled between July 2016 and June 2017. Blood samples were collected in PAXgene tubes and the original NETest assay recalibrated for MEN1 PanNETs. The mNET assay was performed at baseline. Patients were followed for 39 months (range 12-48 months). Diagnostic and predictive values were assessed using the area under the receiver operating characteristic curve (AUC).
Results:
Of 110 eligible patients, 60% were diagnosed with PanNETs at baseline and 9% developed PanNETs during follow-up. At baseline, the mNET assay differentiated between patients without manifestations and patients with only PanNETs (P = .04). The AUC for predicting PanNET development was 0.65 (P = .15). In separate analyses, the assay did not predict PanNET growth (AUC = 0.49), number of PanNETs (AUC = 0.54), new metastatic disease (AUC = 0.39), or metastasis progression (AUC = 0.46).
Conclusion:
In line with previous studies in non-MEN1 associated NET, in MEN1, a circulating NET gene expression assay identified patients without any manifestations from PanNETs. The mNET assay did not predict PanNET development, progression, or metastasis. The underlying genetic condition, epigenetic modifications, microadenomas, and coexistence of multiple manifestations may impact circulating RNA profiles. Further research should explore alternative biomarkers or develop clinico-molecular algorithms for personalized management strategies in MEN1.
