Dataset Information

DNA methylation-based signatures classify sporadic pituitary tumors according to clinicopathological features.

ABSTRACT:

Background

Distinct genome-wide methylation patterns cluster pituitary neuroendocrine tumors (PitNETs) into molecular groups associated with specific clinicopathological features. Here we aim to identify, characterize, and validate methylation signatures that objectively classify PitNET into clinicopathological groups.

Methods

Combining in-house and publicly available data, we conducted an analysis of the methylome profile of a comprehensive cohort of 177 tumors (Panpit cohort) and 20 nontumor specimens from the pituitary gland. We also retrieved methylome data from an independent PitNET cohort (N = 86) to validate our findings.

Results

We identified three methylation clusters associated with adenohypophyseal cell lineages and functional status using an unsupervised approach. Differentially methylated probes (DMP) significantly distinguished the Panpit clusters and accurately assigned the samples of the validation cohort to their corresponding lineage and functional subtypes memberships. The DMPs were annotated in regulatory regions enriched with enhancer elements, associated with pathways and genes involved in pituitary cell identity, function, tumorigenesis, and invasiveness. Some DMPs correlated with genes with prognostic and therapeutic values in other intra- or extracranial tumors.

Conclusions

We identified and validated methylation signatures, mainly annotated in enhancer regions that distinguished PitNETs by distinct adenohypophyseal cell lineages and functional status. These signatures provide the groundwork to develop an unbiased approach to classifying PitNETs according to the most recent classification recommended by the 2017 WHO and to explore their biological and clinical relevance in these tumors.

SUBMITTER: Mosella MS

PROVIDER: S-EPMC8328022 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Publications

DNA methylation-based signatures classify sporadic pituitary tumors according to clinicopathological features.

Mosella Maritza S MS Sabedot Thais S TS Silva Tiago C TC Malta Tathiane M TM Dezem Felipe Segato FS Asmaro Karam P KP Wells Michael M Mukherjee Abir A Poisson Laila M LM Snyder James J deCarvalho Ana C AC Walbert Tobias T Aho Todd T Kalkanis Steven S Elias Paula C PC Antonini Sonir R SR Rock Jack J Noushmehr Houtan H Castro Margaret M Castro Ana Valeria AV

Neuro-oncology 20210801 8

<h4>Background</h4>Distinct genome-wide methylation patterns cluster pituitary neuroendocrine tumors (PitNETs) into molecular groups associated with specific clinicopathological features. Here we aim to identify, characterize, and validate methylation signatures that objectively classify PitNET into clinicopathological groups.<h4>Methods</h4>Combining in-house and publicly available data, we conducted an analysis of the methylome profile of a comprehensive cohort of 177 tumors (Panpit cohort) an ...[more]

PMID: 33631002

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Project description:Pituitary neuroendocrine tumors (PitNETs) are classified according to cell lineage, which requires immunohistochemistry for adenohypophyseal hormones and the transcription factors (TFs) PIT1, SF1, and TPIT. According to the current WHO 2022 classification, PitNETs with co-expression of multiple TFs are termed "plurihormonal". Previously, PIT1/SF1 co-expression was prevailingly reported in PitNETs, which otherwise correspond to the somatotroph lineage. However, little is known about such tumors and the WHO classification has not recognized their significance. We compiled an in-house case series of 100 tumors, previously diagnosed as somatotroph PitNETs. Following TF staining, histopathological features associated with PIT1/SF1 co-expression were assessed. Integration of in-house and publicly available sample data allowed for a meta-analysis of SF1-associated clinicopathological and molecular features across a total of 270 somatotroph PitNETs. The majority (74%, 52/70) of our densely granulated somatotroph PitNETs (DGST) unequivocally co-expressed PIT1 and SF1 (DGST-PIT1/SF1). None (0%, 0/30) of our sparsely granulated somatotroph PitNETs (SGST) stained positive for SF1 (SGST-PIT1). Among DGST, PIT1/SF1 co-expression was significantly associated with scarce FSH/LH expression and fewer fibrous bodies compared to DGST-PIT1. Integrated molecular analyses including publicly available samples confirmed that DGST-PIT1/SF1, DGST-PIT1 and SGST-PIT1 represent distinct tumor subtypes. Clinicopathological meta-analyses indicated that DGST-PIT1 respond more favorably towards treatment with somatostatin analogs compared to DGST-PIT1/SF1, while both these subtypes show an overall less aggressive clinical course than SGST-PIT1. In this study, we spotlight that DGST with co-expression of PIT1 and SF1 represent a common, yet underrecognized, distinct PitNET subtype. Our study questions the rationale of generally classifying such tumors as "plurihormonal", and calls for a refinement of the WHO classification. We propose the term "somatogonadotroph PitNET".

Project description:BackgroundSporadic breast cancer like many other cancers is proposed to be a manifestation of abnormal genetic and epigenetic changes. For the past decade our laboratory has identified genes involved in DNA damage response (DDR), apoptosis and immunosurveillance pathways to influence sporadic breast cancer risk in north Indian population. Further to enhance our knowledge at the epigenetic level, we performed DNA methylation study involving 17 gene promoter regions belonging to DNA damage response (DDR) and death receptor apoptotic pathway in 162 paired normal and cancerous breast tissues from 81 sporadic breast cancer patients, using a high throughput quantitative DNA methylation analysis technology.ResultsThe study identified five genes with statistically significant difference between normal and tumor tissues. Hypermethylation of DR5 (P=0.001), DCR1 (P=0.00001), DCR2 (P=0.0000000005) and BRCA2 (P=0.007) and hypomethylation of DR4 (P=0.011) in sporadic breast tumor tissues suggested a weak/aberrant activation of the DDR/apoptotic pathway in breast tumorigenesis. Negative correlation was observed between methylation status and transcript expression levels for TRAIL, DR4, CASP8, ATM, CHEK2, BRCA1 and BRCA2 CpG sites. Categorization of the gene methylation with respect to the clinicopathological parameters showed an increase in aberrant methylation pattern in advanced tumors. These uncharacteristic methylation patterns corresponded with decreased death receptor apoptosis (P=0.047) and DNA damage repair potential (P=0.004) in advanced tumors. The observation of BRCA2 -26 G/A 5'UTR polymorphism concomitant with the presence of methylation in the promoter region was novel and emerged as a strong candidate for susceptibility to sporadic breast tumors.ConclusionOur study indicates that methylation of DDR-apoptotic gene promoters in sporadic breast cancer is not a random phenomenon. Progressive epigenetic alterations in advancing tumors result in aberrant DDR-apoptotic pathway thereby promoting tumor development. We propose, since pathological epigenetic changes of the DDR-apoptotic genes are reversible modifications, these could further be targeted for therapeutic interventions.

Dataset Information

DNA methylation-based signatures classify sporadic pituitary tumors according to clinicopathological features.

Background

Methods

Results

Conclusions

Publications

DNA methylation-based signatures classify sporadic pituitary tumors according to clinicopathological features.

Similar Datasets

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