Epigenetic prediction of aging and metabolic traits provides insight into tumor biology in multi-focal ileal neuroendocrine tumors (A27)

Introduction: Approximately half of small intestinal neuroendocrine tumors (siNETs) are multifocal,
and recent investigations into the genetic architecture of these tumors have found that they are not
clonal. Due to the low mutational rate and slow growing nature of these small tumors, the ‘timing’ of
the development of individual tumors has not been possible.

Aim(s): To assess the epigenetic age and predicted metabolic traits of multifocal siNETs.

Materials and methods: Using genome-wide DNA methylation data, we assessed the epigenetic age profiles of 100 samples from 11 patients and compared these with matched whole genome sequencing (WGS) data. We applied the epigenetic clock and several other epigenetic predictors to the dataset, then compared these outcomes with matched WGS data.

Results: The epigenetic clock predicted normal epithelia samples to be consistently younger than tumor samples. Metastases were found to be very close in epigenetic age to the primary tumor they were predicted to derive from based on WGS analyses, indicating that metastatic tumors retain epigenetic age profiles of the primary tumor they originated from. The number of somatic mutations identified in WGS also correlated significantly with the epigenetic age predictions. During investigation of metabolic traits, cancer samples showed distinct prediction profiles indicating a ‘starvation phenotype’, which was reflected in the gene-wide methylation of known metabolic genes including ABCG1 and CPT1A. We believe these profiles are reflecting the metabolic behaviour of siNETs which may be contributing to tumour development and disease pathology.

Conclusion: We have used the epigenetic clock to predict the order of siNET development and identified a novel ‘starvation phenotype’ in tumors.

Keywords: dna methylation, epigenetics, multifocal ileal neuroendocrine tumor, multifocal small instestinal net, metabolic traits