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Updated: Nov 24, 2025
Methyl-binding DNA capture Sequencing for Patient Tissues
Published on: October 31, 2016
Genome Methylation Accurately Predicts Neuroendocrine Tumor Origin: An Online Tool
Wenzel M Hackeng1, Koen M A Dreijerink2, Wendy W J de Leng3
1Department of Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands. wenzelhackeng@gmail.com l.a.a.brosens@umcutrecht.nl.
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.
