DNA Methylation-based Signatures Classify Sporadic Pituitary Tumors According to Clinicopathological Features
Mosella MS, Sabedot TS, Silva TC, Malta TM, Segato FD, Asmaro KP, Wells M, Mukherjee A, Poisson LM, Snyder J, deCarvalho AC, Walbert T, Aho T, Kalkanis S, Elias PC, Antonini SR, Rock J, Noushmehr H, Castro M, and Castro AV. DNA Methylation-based Signatures Classify Sporadic Pituitary Tumors According to Clinicopathological Features. Neuro Oncol 2021.
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 CpG 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 of enhancer elements, associated with pathways and genes involved in pituitary cell identity, function, tumorigenesis, 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.
ePub ahead of print