Methylation Profiles Differ According to Clinical Characteristics in Well-Differentiated Neuroendocrine Tumors of the Lung

TL;DR

This study shows that methylation patterns in lung neuroendocrine tumors differ based on clinical features like metastasis and receptor status, which could help improve diagnosis and treatment.

Contribution

The study identifies distinct methylation clusters in lung neuroendocrine tumors linked to clinical characteristics, offering potential for better diagnostic and management strategies.

Findings

Three methylation clusters were identified, with C3 showing 100% typical carcinoids and 89.7% non-metastasized cases.

Differential methylation was associated with metastasis, SSTR status, and endocrine activity in lung neuroendocrine tumors.

Genes affected by methylation changes were primarily involved in cell signaling pathways.

Abstract

Neuroendocrine tumors (NET) of the lung constitute a rare entity of primary lung malignancies that often exhibit an indolent clinical course. Epigenetics-related differences have been described previously for lung NET, but the clinical significance remains unclear. In this study, we performed genome-wide methylation analysis using the Infinium MethylationEPIC BeadChip technology on FFPE tissues from lung NET treated at two academic centers. We aimed to investigate the methylation profiles of known prognostic subgroups. In total, 54 tissue samples from primary lung NET were analyzed, of which 37 were typical carcinoids (TC) and 17 atypical carcinoids (AC). Overall, 25/53 patients (47.2%) developed metastases throughout the disease course, 14/26 (53.8%) had a positive somatostatin receptor (SSTR) scan, and 7/28 patients (25.0%) had documented endocrine activity. Analysis of the DNA methylation data showed substantial differences between TC and AC samples and revealed three distinct clusters (C1–C3): C3 (n = 29) with 100% TC and 89.7% non-metastasized, C2 (n = 22) with 63.6% AC and 95.5% metastasized, and C1 with three AC samples (2/3 metastasized). In subgroup analyses, distinct methylation patterns were observed based on histology, metastases, SSTR status, and endocrine activity. In the functional gene classification, the genes affected by differential methylation were mainly involved in cell signaling. DNA methylation could potentially aid in the diagnostic process of lung NET. The differences in methylation observed with respect to clinical features like SSTR expression and endocrine activity could translate into improved management of lung NET.

The online version contains supplementary material available at 10.1007/s12022-025-09847-2.

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