DNA methylation profiling in nonfunctioning pituitary adenomas

Kober, Paulina; Boresowicz, Joanna; Rusetska, Natalia; Maksymowicz, Maria; Goryca, Krzysztof; Kunicki, Jacek; Bonicki, Wiesław; Siedlecki, Janusz A.; Bujko, Mateusz

doi:10.1016/j.mce.2018.01.020

Cited by 38 publications

(48 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DNA methylation data were retrieved from 3 publicly available cohort datasets (data retrieval freeze on August 2018) 7,13,14 and from our cohort at the Hermelin Brain Tumor Center (HBTC) of the Henry Ford Health System (Detroit, MI, USA) (n=23; HBTC cohort, unpublished). The final cohort consists of 20 non-neoplastic pituitary glands (non-tumor/NT) and 177 PT from patients over 18 years (Pan-pit), composed of 87 FPT and 90 NFPT.…”

Section: Methodsmentioning

confidence: 99%

“…Clinical information about this study cohort is summarized in Table 1 and detailed in Supplementary Table S1. The PT clinicopathological classification criteria of features such as invasion from our internal cohort were matched with the criteria provided by the authors of the external cohorts 7,13,14 . Specific transcription factor-based adenohypophyseal lineages were assigned to each PT subtype in accordance with the 2017 WHO classification 5 .…”

Section: Methodsmentioning

confidence: 99%

“…Specific transcription factor-based adenohypophyseal lineages were assigned to each PT subtype in accordance with the 2017 WHO classification 5 . All the studies were approved by their respective Institutional Review Boards and ethics committees and written consent obtained from each patient at the attending institutions 7,10,13,14 .…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…DNA from pituitary tissue was obtained from fresh-frozen (FF) 13,14 or formalin-fixed-paraffin-embedded specimens (FFPE) 7 . The method of DNA extraction, processing, and assays for each cohort included in this study is reported in the respective manuscripts 7,13,14 and for the HBTC cohort is available in the Supplementary Methods. The IDAT files for the DNA methylation bead arrays (450K or 850K/EPIC) from the Ling, Kober, and Capper cohorts 7,13,14 , were retrieved through the GEOquery package 18 and preprocessed simultaneously using minfi package 19 .…”

Section: Methodsmentioning

confidence: 99%

See 4 more Smart Citations

DNA Methylation-based Signatures Classify Sporadic Pituitary Tumors According to Clinicopathological Features

Mosella

Sabedot

Silva

et al. 2020

Preprint

View full text Add to dashboard Cite

BackgroundDistinct genome-wide methylation patterns have consistently clustered pituitary neuroendocrine tumors (PT) into molecular groups associated with specific clinicopathological features. Here we aim to identify, characterize and validate the methylation signatures that objectively classify PT into those molecular groups.MethodsCombining in-house and publicly available data, we conducted an analysis of the methylome profile of a comprehensive cohort of 177 tumor and 20 non-tumor specimens from the pituitary gland. We also retrieved methylome data from an independent pituitary tumor (PT) cohort (N=86) to validate our findings.ResultsWe identified three methylation clusters associated with functional status and adenohypophyseal cell lineages using an unsupervised approach. We also identified signatures based on differentially methylated CpG probes (DMP), some of which overlapped with pituitary-specific transcription factors genes (SF1 and Tpit), that significantly distinguished pairs of clusters related to functional status and adenohypophyseal cell lineage. These findings were reproduced in an independent cohort, validating these methylation signatures. The DMPs were mainly annotated in enhancer regions associated with pathways and genes involved in cell identity and tumorigenesis.ConclusionsWe identified and validated methylation signatures that distinguished PT by distinct functional status and adenohypophyseal cell lineages. These signatures, annotated in enhancer regions, indicate the importance of these elements in pituitary tumorigenesis. They also provide an unbiased approach to classify pituitary tumors according to the most recent classification recommended by the WHO 2017 using methylation profiling.Key-pointsDistinct methylation landscapes define PT groups with specific functional status/subtypes and adenohypophyseal lineages subtypes.Methylation abnormalities in each cluster mainly occur in CpG annotated in distal regions overlapping predicted enhancers regions associated with pathways and genes involved in cell identity and tumorigenesis.DNA methylation signatures provide an unbiased approach to classify PT.Importance of the studyThis study harnessed the largest methylome data to date from a comprehensive cohort of pituitary specimens obtained from four different institutions. We identified and validated methylation signatures that distinguished pituitary tumors into molecular groups that reflect the functionality and adenohypophyseal cell lineages of these tumors. These signatures, mainly located in enhancers, are associated with pathways and genes involved in cell identity and tumorigenesis. Our results show that methylome profiling provides an objective approach to classify PT according to the most recent classification of PT recommended by the 2017 WHO.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

DNA Methylation-based Signatures Classify Sporadic Pituitary Tumors According to Clinicopathological Features

Mosella

Sabedot

Silva

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

The use of mass spectrometry in a proteome‐centered multiomics study of human pituitary adenomas

Desiderio

Zhan

2021

Mass Spectrometry Reviews

View full text Add to dashboard Cite

A pituitary adenoma (PA) is a common intracranial neoplasm, and is a complex, chronic, and whole-body disease with multicausing factors, multiprocesses, and multiconsequences. It is very difficult to clarify molecular mechanism and treat PAs from the single-factor strategy model. The rapid development of multiomics and systems biology changed the paradigms from a traditional single-factor strategy to a multiparameter systematic strategy for effective management of PAs.A series of molecular alterations at the genome, transcriptome, proteome, peptidome, metabolome, and radiome levels are involved in pituitary tumorigenesis, and mutually associate into a complex molecular network system. Also, the center of multiomics is moving from structural genomics to phenomics, including proteomics and metabolomics in the medical sciences. Mass spectrometry (MS) has been extensively used in phenomics studies of human PAs to clarify molecular mechanisms, and to discover biomarkers and therapeutic targets/drugs. MS-based

show abstract