ArticleNeuro-oncology2022
Detection of tumor-specific DNA methylation markers in the blood of patients with pituitary neuroendocrine tumors.
Article in Neuro-oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Is There a Role for Machine Learning in Liquid Biopsy for Brain Tumors? A Systematic Review.International journal of molecular sciences · 2023Pooled it
- Liquid Biopsy in Primary CNS Tumors: Bridging Biology, Technology, and Clinical Care.Molecular diagnosis & therapy · 2026Review
- The role of methylation in pituitary neuroendocrine tumors current insights and emerging perspectives.Molecular biology reports · 2026Review
- Review
- Blood-based tumor biomarkers: integrating biological layers and analytical strategies for precision cancer detection.Frontiers in medicine · 2026Review
- The PitNET Puzzle: From Zero to Linking Molecular Behavior with Neurosurgical Aspects.Medicina (Kaunas, Lithuania) · 2025Review
- Preanalytical variables and analytes in liquid biopsy approach for brain tumors: A comprehensive review and recommendations from the RANO Group and the Brain Liquid Biopsy Consortium.Neuro-oncology · 2025Review
- Review
- Identifying ovarian cancer with machine learning DNA methylation pattern analysis.Scientific reports · 2025Article
- Current understanding of the role of DNA methylation in pituitary neuroendocrine tumors.Neuro-oncology advances · 2025Article
- Molecular signatures of invasive and non-invasive pituitary adenomas: a comprehensive analysis of DNA methylation and gene expression.BMC medicine · 2025Article
- Liquid Biopsy in Pituitary Neuroendocrine Tumors-Potential Biomarkers for Diagnosis, Prognosis, and Therapy.International journal of molecular sciences · 2025Review
- A Nexus of Biomolecular Complexities in Pituitary Neuroendocrine Tumors: Insights into Key Molecular Drivers.Biomedicines · 2025Review
- A Brief Overview of Molecular Biology in Pituitary Adenomas with a Focus on Aggressive Lesions.International journal of molecular sciences · 2025Review
- DNA Methylation in Pituitary Adenomas: A Scoping Review.International journal of molecular sciences · 2025Article
- Review
- Genome-Wide DNA Methylation Profiling as a Prognostic Marker in Pituitary Adenomas-A Pilot Study.Cancers · 2024Article
- Artificial Intelligence, Radiomics, and Computational Modeling in Skull Base Surgery.Advances in experimental medicine and biology · 2024Review
- A rare case of double pituitary prolactinomas: the diagnostic application of intraoperative ultrasonography and DNA methylation markers.Archives of endocrinology and metabolism · 2024Article
- Recent Developments in Blood Biomarkers in Neuro-oncology.Current neurology and neuroscience reports · 2023Review
Corrections and comments
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Authors and funding
26 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDNA 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.
methodsWe 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.
resultsOur 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.
conclusionsOur 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.
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