DNA methylation-based signatures classify sporadic pituitary tumors according to clinicopathological features

Abstract

Background: Distinct genome-wide methylation patterns cluster pituitary neuroendocrine tumors (PitNETs) into molecular groups associated with specific clinicopathological features. Here we aim to identify, characterize, and validate methylation signatures that objectively classify PitNET into clinicopathological groups.

Methods: Combining in-house and publicly available data, we conducted an analysis of the methylome profile of a comprehensive cohort of 177 tumors (Panpit cohort) and 20 nontumor specimens from the pituitary gland. We also retrieved methylome data from an independent PitNET cohort (N = 86) to validate our findings.

Results: We identified three methylation clusters associated with adenohypophyseal cell lineages and functional status using an unsupervised approach. Differentially methylated probes (DMP) significantly distinguished the Panpit clusters and accurately assigned the samples of the validation cohort to their corresponding lineage and functional subtypes memberships. The DMPs were annotated in regulatory regions enriched with enhancer elements, associated with pathways and genes involved in pituitary cell identity, function, tumorigenesis, and invasiveness. Some DMPs correlated with genes with prognostic and therapeutic values in other intra- or extracranial tumors.

Conclusions: We identified and validated methylation signatures, mainly annotated in enhancer regions that distinguished PitNETs by distinct adenohypophyseal cell lineages and functional status. These signatures provide the groundwork to develop an unbiased approach to classifying PitNETs according to the most recent classification recommended by the 2017 WHO and to explore their biological and clinical relevance in these tumors.

Keywords: DNA methylation; classification; enhancers; pituitary neuroendocrine tumors.

Fig. 1

Methylome landscape segregates pituitary neuroendocrine tumors (PitNET) into three distinct groups. (A) Consensus Clustering correlation heatmap depicting three methylation-based groups across PitNETs (n = 177). (B) Heatmap of the top most variant CpG-methylated probes (n = 4526) across 177 PitNETs and 20 nontumor pituitary specimens. Columns represent specimens; rows represent the CpG probes. (C) Mean DNA methylation of the top most variant probes across nontumor and PitNETs methylation groups.

Fig. 2

Differentially methylated probes (DMPs) define pituitary neuroendocrine tumors (PitNETs) according to adenohypophyseal cell lineage. (A) Heatmap displaying DMPs across pairwise methylation group comparisons. Left: Panpit cohort, discovery, n = 197; Right: Neou cohort, validation, n = 86. (B) Odds ratio depicting the frequencies of genomic location and enhancer overlap with DMPs relative to the expected genome-wide distribution of the HM450K probes. Hyper- or hypomethylated probes across clusters are displayed as red- and blue-shaded boxes. (C) Barplots showing the number of exclusive or common hypermethylated DMPs in relation to the intersection across the three DMP sets. (D) Barplots showing the number of exclusive or common hypomethylated DMPs in relation to the intersection across the three DMP sets.

Fig. 3

Differentially methylated probes overlapping regulatory regions (promoter and enhancers) are involved with relevant biological pathways and correlate with gene expression. (A) Gene Ontology analysis of the top paired methylated probe-genes, sorted by the ELMER tool, annotated in promoter and enhancer regions. (B) Paired DNA methylation and gene expression (RNA-seq) heatmaps of probe-gene pairs from (A), depicting probe methylation and paired gene expression, respectively. (C) Scatter plots of correlations between DNA methylation and gene expression, in promoter and enhancer gene-probe pairs, selected by biological meaning on PitNETs.

Fig. 4

Differentially methylated probes related to pituitary-specific transcription factors across pituitary neuroendocrine tumors (PitNET) methylation clusters. (A) Heatmap indicating significant differentially methylated probes associated with the SF1 (NR5A1) and TPIT (TBX19) TF across TPIT-e, SF1-e, and PIT1-e clusters. Left heatmap: Methylation patterns of Panpit cohort (discovery, n = 177); Right heatmap: Corresponding CpG methylation patterns applied to the Neou cohort (validation, n = 86). (B) Density plots on the distribution of methylation degree beta-value and suggested thresholds (vertical dashed lines) for SF1- and TPIT-related differentially methylated probes that distinguish the TPIT-e from SF1-e and TPIT-e from non-TPIT, respectively.