Detection of tumor-specific DNA methylation markers in the blood of patients with pituitary neuroendocrine tumors. Issue 7 (25th February 2022)

• Record Type: Journal Article
• Authors: Herrgott, Grayson A; Asmaro, Karam P; Wells, Michael; Sabedot, Thais S; Malta, Tathiane M; Mosella, Maritza S; Nelson, Kevin; Scarpace, Lisa; Barnholtz-Sloan, Jill S; Sloan, Andrew E; Selman, Warren R; deCarvalho, Ana C; Poisson, Laila M; Mukherjee, Abir; Robin, Adam M; Lee, Ian Y; Snyder, James; Walbert, Tobias; Rosenblum, Mark; Mikkelsen, Tom; Bhan, Arti; Craig, John; Kalkanis, Steven; Rock, Jack; Noushmehr, Houtan; Castro, Ana Valeria
• Is Part Of: Neuro-oncology. Volume 24:Issue 7(2022)
• Page Start: 1126
• Page End: 1139
• Publication Date: 2022-02-25
• Subjects: liquid biopsy -- methylation -- PitNET -- plasma -- serum; Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noac050
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Background: DNA methylation abnormalities are pervasive in pituitary neuroendocrine tumors (PitNETs). The feasibility to detect methylome alterations in circulating cell-free DNA (cfDNA) has been reported for several central nervous system (CNS) tumors but not across PitNETs. The aim of the study was to use the liquid biopsy (LB) approach to detect PitNET-specific methylation signatures to differentiate these tumors from other sellar diseases. Methods: We profiled the cfDNA methylome (EPIC array) of 59 serum and 41 plasma LB specimens from patients with PitNETs and other CNS diseases (sellar tumors and other pituitary non-neoplastic diseases, lower-grade gliomas, and skull-base meningiomas) or nontumor conditions, grouped as non-PitNET. Results: Our results indicated that despite quantitative and qualitative differences between serum and plasma cfDNA composition, both sources of LB showed that patients with PitNETs presented a distinct methylome landscape compared to non-PitNETs. In addition, LB methylomes captured epigenetic features reported in PitNET tissue and provided information about cell-type composition. Using LB-derived PitNETs-specific signatures as input to develop machine-learning predictive models, we generated scores that distinguished PitNETs from non-PitNETs conditions, including sellar tumor and non-neoplastic pituitary diseases, with accuracies above ~93% in independent cohort sets. Conclusions: Our results underpin the potential application of methylation-based LB profiling as a noninvasive approach to identify clinically relevant epigenetic markers to diagnose and potentially impact the prognostication and management of patients with PitNETs.