Abstract

BACKGROUND: Several reports have indicated that distinct epigenomic patterns of pituitary tumors (PT), specifically DNA methylation, distinguish these tumor tissues according to their functionality and could be involved in their pathogenesis. Thus far, molecular diagnosis and classification criteria that guide clinical management of these tumors rely on the tissue profiling obtained by invasive surgical approaches (e.g. excision). However, increasing evidence confirmed that central nervous system (CNS) tumors release cell material into the circulation creating an opportunity for molecular profiling of these tumors using a blood-based liquid biopsy. Considering that 1) the pituitary portal system and the invasion of the cavernous system by PT may facilitate the spillage of tumor cell material into the bloodstream and 2) the stability, cell-specificity and reportedly the role of DNA methylation in PT, we hypothesized that liquid biopsy would be feasible to detect and define specific methylation-based signatures in the serum of patients harboring PT. Methods and Findings: We conducted analyses of the methylomes of paired serum circulating cell-free DNA (cfDNA) and tumor tissue from patients harboring PT (EPIC array) to identify serum-derived pituitary tumor-specific methylation-based signatures (sPTMet n=37) in a cohort comprised by 13 patients with pituitary macroadenomas (9 males; median age: 62; 9 Nonfunctioning/4functioning, 6 invasive/7noninvasive), 4 controls (non-tumor) and patients with other CNS tumors or conditions (114 gliomas, 6 meningiomas, 1 brain metastasis, 1 colloid cyst, 6 radiation necrosis). Unsupervised and supervised analysis indicated that the serum methylome from patients harboring PT was distinct from controls and other CNS diseases. Using the sPTMet as input into a machine learning algorithm, we generated a PT score that classified the serum of an independent cohort as PT or non-PT, with high accuracy. We identified serum-derived differentially methylated probes (DMP, n=3288) that distinguished PT according to their function (functioning and nonfunctioning). When overlapped with an independent cohort, these DMP also distinguished PT tissue according to their functional status. Conclusion: Our results showed the feasibility to identify PT-specific methylation signatures by profiling the methylome of serum cfDNA from patients with PT. These signatures distinguished PT from other CNS tumors and according to their subtypes. These results underpin the potential role of methylation profile and liquid biopsy as a noninvasive approach to assess clinically relevant molecular features. Potentially, tumor-specific serum-derived methylation signature may be used as a diagnostic, prognostic and surveillance tool as well to identify actionable molecular markers in patients with PT.

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