Integrating a 92-Gene Expression Analysis for the Management of Neuroendocrine Tumors of Unknown Primary

Neuroendocrine tumour of the lesser omentum

A man in his early 20s presented to us in the outpatient department with a history of diarrhoea for 4 months. Investigations revealed elevated serum chromogranin levels and an intensely avid lesion in the gastrohepatic ligament in Gallium DOTATATE positron emission tomography (PET). The tumour was excised laparoscopically, and no other lesions were seen. The patient improved clinically and had a normal serum chromogranin level postoperatively. He is currently much improved at the 1year follow-up. We did an extensive workup to look for a primary tumour. It was concluded that it was a de novo tumour arising from the lesser sac. The recommended investigations in case of neuroendocrine tumour (NET) with unknown primary include blood investigations to look for the functional status of the tumour, histopathological examination, including immunohistochemistry, and radiological imaging, which must include a Gallium DOTATATE PET. An isolated NET of the lesser sac has not been reported in the literature.

An abdominal wall neuroendocrine tumor of unknown primary origin: A case report and review of the literature

Background

Neuroendocrine tumors (NETs) are neoplasms that arise from cells of the endocrine and nervous system. NETs, often found in the gastrointestinal tract, can be found anywhere in the body, and have metastatic potential. NETs occasionally present with metastatic disease without an identifiable primary tumor.

Case

A 79‐year‐old female patient presented with an abdominal wall mass. Percutaneous biopsy was consistent with a NET. Preoperative endoscopy and PillCam were unremarkable. PET Dotatate demonstrated uptake in the abdominal wall as well as vague uptake in the pelvis. Intraoperatively, we identified a suspicious nodule on the sigmoid colon, which was consistent with a drop metastasis on final pathology.

Conclusion

In this case report we present a patient with a NET metastasis to the abdominal wall without a known primary site. This case highlights the limitations of endoscopy and imaging in the workup of metastatic NETs. Additionally, this is a novel case report of a metastatic NET to the abdominal wall without an identifiable primary site.

Genome Methylation Accurately Predicts Neuroendocrine Tumor Origin: An Online Tool

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.

Current Practices and Novel Techniques in the Diagnosis and Management of Neuroendocrine Tumors of Unknown Primary

Neuroendocrine tumors (NETs) comprise a heterogeneous group of neoplasms in which tumor staging/prognosis and response to treatments depend heavily on accurate and timely identification of the anatomic primary site or NET subtype. Despite recent technological advancements and use of multiple diagnostic modalities, 10% to 14% of newly diagnosed NETs are not fully characterized based on subtype or anatomic primary site. Inability to fully characterize NETs of unknown primary may cause delays in surgical intervention and limit potential treatment options. To address this unmet need, clinical validity and utility are being demonstrated for novel approaches that improve NET subtype or anatomic primary site identification. Functional imaging using Ga-radiolabeled DOTATATE positron emission tomography/computed tomography has been shown to overcome some false-positive and resolution issues associated with octreotide scanning and computed tomography/magnetic resonance imaging. Using a genomic approach, molecular tumor classification based on differential gene expression has demonstrated high diagnostic accuracy in blinded validation studies of different NET types and subtypes. Given the widespread availability of these technologies, we propose an algorithm for the workup of NETs of unknown primary that integrates these approaches. Including these technologies in the standard workup will lead to better NET subtype identification and improved treatment optimization for patients.