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. 2021 Mar 1;27(5):1341-1350.
doi: 10.1158/1078-0432.CCR-20-3281. Epub 2020 Dec 22.

Genome Methylation Accurately Predicts Neuroendocrine Tumor Origin: An Online Tool

Wenzel M Hackeng  1 , Koen M A Dreijerink  2 , Wendy W J de Leng  3 , Folkert H M Morsink  3 , Gerlof D Valk  4 , Menno R Vriens  5 , G Johan A Offerhaus  3 , Christoph Geisenberger #  6 , Lodewijk A A Brosens #  1
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Genome Methylation Accurately Predicts Neuroendocrine Tumor Origin: An Online Tool

Wenzel M Hackeng et al. Clin Cancer Res. .

Abstract

Purpose: The primary origin of neuroendocrine tumor metastases can be difficult to determine by histopathology alone, but is critical for therapeutic decision making. DNA methylation-based profiling is now routinely used in the diagnostic workup of brain tumors. This has been enabled by the availability of cost-efficient array-based platforms. We have extended these efforts to augment histopathologic diagnosis in neuroendocrine tumors.

Experimental design: Methylation data was compiled for 69 small intestinal, pulmonary, and pancreatic neuroendocrine tumors. These data were used to build a ridge regression calibrated random forest classification algorithm (neuroendocrine neoplasm identifier, NEN-ID). The model was validated during 3 × 3 nested cross-validation and tested in a local and an external cohort (n = 198 cases).

Results: NEN-ID predicted the origin of tumor samples with high accuracy (>95%). In addition, the diagnostic approach was determined to be robust across a range of possible confounding experimental parameters, such as tumor purity and array quality. A software infrastructure and online user interface were built to make the model available to the scientific community.

Conclusions: This DNA methylation-based prediction model can be used in the workup for patients with neuroendocrine tumors of unknown primary. To facilitate validation and clinical implementation, we provide a user-friendly, publicly available web-based version of NEN-ID.

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