DNA methylation profiling of pituitary neuroendocrine tumors identifies distinct clinical and pathological subtypes based on epigenetic differentiation.

IF 16.4 1区 医学 Q1 CLINICAL NEUROLOGY
Sarra Belakhoua, Varshini Vasudevaraja, Chanel Schroff, Kristyn Galbraith, Misha Movahed-Ezazi, Jonathan Serrano, Yiying Yang, Daniel Orringer, John G Golfinos, Chandra Sen, Donato Pacione, Nidhi Agrawal, Matija Snuderl
{"title":"DNA methylation profiling of pituitary neuroendocrine tumors identifies distinct clinical and pathological subtypes based on epigenetic differentiation.","authors":"Sarra Belakhoua, Varshini Vasudevaraja, Chanel Schroff, Kristyn Galbraith, Misha Movahed-Ezazi, Jonathan Serrano, Yiying Yang, Daniel Orringer, John G Golfinos, Chandra Sen, Donato Pacione, Nidhi Agrawal, Matija Snuderl","doi":"10.1093/neuonc/noaf109","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Pituitary neuroendocrine tumors (PitNETs) are the most common intracranial neuroendocrine tumors. PitNETs can be challenging to classify, and current recommendations include a large immunohistochemical panel to differentiate among 14 WHO-recognized categories.</p><p><strong>Methods: </strong>In this study, we analyzed clinical, immunohistochemical and DNA methylation data of 118 PitNETs to develop a clinico-molecular approach to classifying PitNETs and identify epigenetic classes.</p><p><strong>Results: </strong>CNS DNA methylation classifier has an excellent performance in recognizing PitNETs and distinguishing the three lineages when the calibrated score is ≥0.3. Unsupervised DNA methylation analysis separated PitNETs into two major clusters. The first was composed of silent gonadotrophs, which form a biologically distinct group of PitNETs characterized by clinical silencing, weak hormonal expression on immunohistochemistry, and simple copy number profile. The second major cluster was composed of corticotrophs and Pit1 lineage PitNETs, which could be further classified using DNA methylation into distinct subclusters that corresponded to clinically functioning and silent tumors and are consistent with transcription factor expression. Analysis of promoter methylation patterns correlated with lineage for corticotrophs and Pit1 lineage subtypes. However, the gonadotrophic genes did not show a distinct promoter methylation pattern in gonadotroph tumors compared to other lineages. Promoter of the NR5A1 gene, which encodes SF1, was hypermethylated across all PitNETs clinical and molecular subtypes including gonadotrophs with strong SF1 protein expression indicating alternative epigenetic regulation.</p><p><strong>Conclusion: </strong>Our findings suggest that classification of PitNETs may benefit from DNA methylation for clinicopathological stratification.</p>","PeriodicalId":19377,"journal":{"name":"Neuro-oncology","volume":" ","pages":""},"PeriodicalIF":16.4000,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuro-oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/neuonc/noaf109","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Pituitary neuroendocrine tumors (PitNETs) are the most common intracranial neuroendocrine tumors. PitNETs can be challenging to classify, and current recommendations include a large immunohistochemical panel to differentiate among 14 WHO-recognized categories.

Methods: In this study, we analyzed clinical, immunohistochemical and DNA methylation data of 118 PitNETs to develop a clinico-molecular approach to classifying PitNETs and identify epigenetic classes.

Results: CNS DNA methylation classifier has an excellent performance in recognizing PitNETs and distinguishing the three lineages when the calibrated score is ≥0.3. Unsupervised DNA methylation analysis separated PitNETs into two major clusters. The first was composed of silent gonadotrophs, which form a biologically distinct group of PitNETs characterized by clinical silencing, weak hormonal expression on immunohistochemistry, and simple copy number profile. The second major cluster was composed of corticotrophs and Pit1 lineage PitNETs, which could be further classified using DNA methylation into distinct subclusters that corresponded to clinically functioning and silent tumors and are consistent with transcription factor expression. Analysis of promoter methylation patterns correlated with lineage for corticotrophs and Pit1 lineage subtypes. However, the gonadotrophic genes did not show a distinct promoter methylation pattern in gonadotroph tumors compared to other lineages. Promoter of the NR5A1 gene, which encodes SF1, was hypermethylated across all PitNETs clinical and molecular subtypes including gonadotrophs with strong SF1 protein expression indicating alternative epigenetic regulation.

Conclusion: Our findings suggest that classification of PitNETs may benefit from DNA methylation for clinicopathological stratification.

垂体神经内分泌肿瘤的DNA甲基化谱识别基于表观遗传分化的不同临床和病理亚型。
背景:垂体神经内分泌肿瘤(PitNETs)是最常见的颅内神经内分泌肿瘤。PitNETs分类可能具有挑战性,目前的建议包括一个大型免疫组织化学小组,以区分世卫组织认可的14个类别。方法:在这项研究中,我们分析了118个PitNETs的临床、免疫组织化学和DNA甲基化数据,以建立临床分子方法对PitNETs进行分类并确定表观遗传分类。结果:当标定分数≥0.3时,CNS DNA甲基化分类器在识别PitNETs和区分三个谱系方面表现优异。无监督的DNA甲基化分析将PitNETs分为两个主要集群。第一组由沉默的促性腺激素组成,它们形成了一组生物学上独特的PitNETs,其特征是临床沉默,免疫组织化学上激素表达弱,拷贝数谱简单。第二个主要簇由促肾上腺皮质激素和PitNETs组成,可以通过DNA甲基化进一步分类为不同的亚簇,这些亚簇对应于临床功能和沉默的肿瘤,并与转录因子表达一致。促皮质细胞和Pit1谱系亚型启动子甲基化模式与谱系相关的分析。然而,与其他谱系相比,促性腺功能基因在促性腺功能肿瘤中没有表现出明显的启动子甲基化模式。编码SF1的NR5A1基因的启动子在所有PitNETs临床和分子亚型中都被超甲基化,包括促性腺激素,具有强烈的SF1蛋白表达,表明有其他表观遗传调控。结论:我们的研究结果表明,PitNETs的分类可能受益于DNA甲基化的临床病理分层。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Neuro-oncology
Neuro-oncology 医学-临床神经学
CiteScore
27.20
自引率
6.30%
发文量
1434
审稿时长
3-8 weeks
期刊介绍: Neuro-Oncology, the official journal of the Society for Neuro-Oncology, has been published monthly since January 2010. Affiliated with the Japan Society for Neuro-Oncology and the European Association of Neuro-Oncology, it is a global leader in the field. The journal is committed to swiftly disseminating high-quality information across all areas of neuro-oncology. It features peer-reviewed articles, reviews, symposia on various topics, abstracts from annual meetings, and updates from neuro-oncology societies worldwide.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信