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基于DNA甲基化的分析揭示了富含巨细胞的成人型胶质母细胞瘤中表观遗传衰老加速。

DNA methylation-based analysis reveals accelerated epigenetic aging in giant cell-enriched adult-type glioblastoma.

作者信息

Cakmak Pinar, Jurmeister Philipp, Divé Iris, Zeiner Pia S, Steinbach Joachim P, Fenton Tim R, Plate Karl H, Czabanka Marcus, Harter Patrick N, Weber Katharina J

机构信息

Goethe University Frankfurt, University Hospital, Neurological Institute (Edinger Institute), Frankfurt, Germany.

Goethe University Frankfurt, Frankfurt Cancer Institute (FCI), Frankfurt, Germany.

出版信息

Clin Epigenetics. 2024 Dec 11;16(1):179. doi: 10.1186/s13148-024-01793-w.

DOI:10.1186/s13148-024-01793-w
PMID:39663543
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11636044/
Abstract

BACKGROUND

Giant cell (gc)-enriched glioblastoma (gcGB) represents a distinct histological variant of isocitrate dehydrogenase wild-type adult-type glioblastoma with notable enlarged mono- or multinuclear tumor cells. While some studies suggest a survival advantage for gcGB patients, the underlying causes remain elusive. GcGBs are associated with TP53 mutations, and gcs were shown to accumulate DNA double-strand breaks and show deficient mitosis, potentially triggering cellular senescence programs. Epigenetic clocks have emerged as valuable tools for assessing tumor-induced age acceleration (DNAMethAgeAcc), which has lately proved itself as prognostic biomarker in glioblastoma. Our study aimed to comprehensively analyze the methylome and key metabolic proteins of gcGBs, hypothesizing that they undergo cellular aging programs compared to non-gcGBs.

RESULTS

A total of 310 epigenetically classified GBs, including 26 gcGBs, and nine adults with malignant gliomas allocating to pediatric high-grade glioma molecular subclasses (summarized as "pediatric GB") were included. DNAMethAgeAcc was computed by subtraction of chronological patient ages from DNA methylome-derived age estimations and its increase was associated with better survival within gcGB and non-gcGB. GcGBs were significantly more often allocated to the subgroup with increased DNAMethAgeAcc and demonstrated the highest DNAMethAgeAcc. Hypothetical senescence/aging-induced changes of the tumor microenvironment were addressed by tumor deconvolution, which was able to identify a cluster enriched for tumors with increased DNAMethAgeAcc. Key metabolic protein expression did not differ between gcGB and non-gcGB and tumor with versus without increased DNAMethAgeAcc but for elevated levels of one single mitochondrial marker, anti-mitochondrial protein MT-C02, in gcGBs.

CONCLUSIONS

With its sped-up epigenetic aging, gcGB presented as the epigenetic oldest GB variant in our cohort. Whereas the correlation between accelerated tumor-intrinsic epigenetic aging and cellular senescence in gcGB stays elusive, fostering epigenetic aging programs in GB might be of interest for future exploration of alternative treatment options in GB patients.

摘要

背景

富含巨细胞(gc)的胶质母细胞瘤(gcGB)是异柠檬酸脱氢酶野生型成人型胶质母细胞瘤的一种独特组织学变体,具有明显增大的单核或多核肿瘤细胞。虽然一些研究表明gcGB患者具有生存优势,但其潜在原因仍不清楚。GcGB与TP53突变相关,并且已证明巨细胞会积累DNA双链断裂并表现出有丝分裂缺陷,这可能触发细胞衰老程序。表观遗传时钟已成为评估肿瘤诱导的年龄加速(DNAMethAgeAcc)的有价值工具,最近它已被证明是胶质母细胞瘤的预后生物标志物。我们的研究旨在全面分析gcGB的甲基化组和关键代谢蛋白,假设与非gcGB相比,它们会经历细胞衰老程序。

结果

共纳入310例经表观遗传学分类的胶质母细胞瘤,包括26例gcGB,以及9例分配到儿童高级别胶质瘤分子亚类的成人恶性胶质瘤(总结为“儿童GB”)。DNAMethAgeAcc通过从DNA甲基化组衍生的年龄估计值中减去患者实际年龄来计算,其增加与gcGB和非gcGB患者的更好生存相关。GcGB更常被分配到DNAMethAgeAcc增加的亚组,并且表现出最高的DNAMethAgeAcc。通过肿瘤解卷积研究了肿瘤微环境的假设性衰老/老化诱导变化,该方法能够识别出富含DNAMethAgeAcc增加的肿瘤的一个簇。gcGB与非gcGB以及DNAMethAgeAcc增加与未增加的肿瘤之间,关键代谢蛋白表达没有差异,但gcGB中有一个单一线粒体标志物抗线粒体蛋白MT-C02水平升高。

结论

gcGB以其加速的表观遗传衰老,在我们的队列中表现为表观遗传上最老的GB变体。虽然gcGB中加速的肿瘤内在表观遗传衰老与细胞衰老之间的相关性仍不清楚,但促进GB中的表观遗传衰老程序可能是未来探索GB患者替代治疗方案的一个有意义的方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61b3/11636044/a0dd31ddd592/13148_2024_1793_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61b3/11636044/0228e6bf5615/13148_2024_1793_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61b3/11636044/ce35ba2facc8/13148_2024_1793_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61b3/11636044/fe21c05fc976/13148_2024_1793_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61b3/11636044/a0dd31ddd592/13148_2024_1793_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61b3/11636044/0228e6bf5615/13148_2024_1793_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61b3/11636044/ce35ba2facc8/13148_2024_1793_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61b3/11636044/fe21c05fc976/13148_2024_1793_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61b3/11636044/a0dd31ddd592/13148_2024_1793_Fig4_HTML.jpg

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