Molecular classification helps pinpoint subtype, origin of NETs

Liz Meszaros, MDLinx

North American Neuroendocrine Tumor Society (NANETS) 10th Annual Symposium

Philadelphia, Pennsylvania, United States | October 19-21, 2017

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Philadelphia, PA, October 19, 2017—Molecular classification can be useful in identifying distinct neuroendocrine tumor (NET) types and subtypes, and significant differences in the distribution of molecular diagnoses of NET subtypes by age and gender, which in turn, can result in improved diagnostic accuracy and treatment decisions, according to researchers here at the North American Endocrine Tumor Society (NANETS) 2017 Symposium.

Take-home messages

  • Half of patients with NETS are diagnosed with metastases on presentation, and of these, 15% have a tumor of unknown origin.
  • Molecular classification can identify distinct neuroendocrine tumor (NET) types and subtypes, as well as differences in the distribution of molecular diagnoses of NET subtypes by age and gender.

“Fifty percent of patients with NETs are diagnosed with metastases on presentation, and about 15% have a tumor of unknown origin, meaning we know it’s a neuroendocrine tumor, but we’re not exactly clear of the subtype or of the anatomic site of origin,” said Andrew E. Hendifar, MD, medical oncology lead, Gastrointestinal Disease Research Group, and co-director of Pancreas Oncology, Cedars Sinai Medical Center, Los Angeles, CA.

“In those patients, it is important to understand the subtype and the anatomic site in more detail, because it can lead to enhanced treatment options for these patients,” he added.

Researchers created a de-identified database containing clinical and molecular information from consecutive cases that were submitted for testing with the 92-gene assay.

“This molecular classification was put together many years ago for carcinoma of unknown primary. They took about 600 tumors, and sequenced about 20,000 genes. They then put together, based on reverse transcription polymerase chain reaction (RTPCR), a reference gene expression profile that they compared tumors to,” explained Dr. Hendifar.

For their retrospective review of a large cohort of patients, Dr. Hendifar and colleagues included 24,484 patients (median age: 65 years; 51% female) with tumors of unknown primary origins. They used this database to analyze patient demographics and molecular diagnoses based on biopsy site, age, and gender, and used Chi-squared testing to make subgroup comparisons.

A molecular diagnosis of NET was given in 6.3% of cases, or 1,551 patients. The most common NET molecular diagnosis was small and large cell lung cancer (50%), followed by gastrointestinal carcinoid (14%), islet cell (14%), Merkel cell (10%), and lung carcinoid (9%).

Among the 39% of cases that underwent liver biopsy, all seven NET subtypes were identified by the 92-gene assay.

Dr. Hendifar and colleagues found that the proportion of molecular diagnoses that were classified as small/large cell lung NET increased with age, from 25% in cases aged less than 40 years, to 45% in those aged 40 to 65 years, to 55% in those more than 65 years old. Conversely, the proportion of islet cell NET classified decreased with age (P < 0.001). They also found a higher proportion of molecular diagnoses that were small and large cell lung NET in men compared with women (53% vs 46%, respectively; P < 0.0001).

“For patients who have a NET that we don’t quite understand the subtype or the site of origin, this could be a very useful tool to help further understand the patient’s disease and biology, and of course, that would extend to better treatment options for the patients,” concluded Dr. Hendifar.

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