Detection of tumor-specific DNA methylation markers in the blood of patients with pituitary neuroendocrine tumors

Author:

Herrgott Grayson A12,Asmaro Karam P12,Wells Michael12,Sabedot Thais S12,Malta Tathiane M12,Mosella Maritza S12,Nelson Kevin1,Scarpace Lisa1,Barnholtz-Sloan Jill S3,Sloan Andrew E45,Selman Warren R4,deCarvalho Ana C1,Poisson Laila M6,Mukherjee Abir7,Robin Adam M1ORCID,Lee Ian Y1ORCID,Snyder James12,Walbert Tobias1ORCID,Rosenblum Mark1,Mikkelsen Tom1,Bhan Arti8,Craig John9ORCID,Kalkanis Steven1,Rock Jack1,Noushmehr Houtan12ORCID,Castro Ana Valeria12ORCID

Affiliation:

1. Department of Neurosurgery, Hermelin Brain Tumor Center, Henry Ford Health System , Detroit, Michigan , USA

2. Department of Neurosurgery, Omics Laboratory, Henry Ford Health System , Detroit, Michigan , USA

3. Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine , Cleveland, Ohio , USA

4. Department of Neurological Surgery, University Hospitals of Cleveland , Cleveland, Ohio , USA

5. Case Comprehensive Cancer Center , Cleveland, Ohio , USA

6. Department of Biostatistics, Henry Ford Health System , Detroit, Michigan , USA

7. Department of Pathology, Henry Ford Health System , Detroit, Michigan , USA

8. Department of Endocrinology, Henry Ford Health System , Detroit, Michigan , USA

9. Department of Otolaryngology, Skull Base, Pituitary and Endoscopy Center, Henry Ford Health System , Detroit, Michigan , USA

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.

Funder

Department of Neurosurgery

Hermelin Brain Tumor Center

Henry Ford Health System

Henry Ford Hospital

Kimble Family Foundation

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Neurology (clinical),Oncology

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