Chen Yike, Zhao Ningning, Zhang Jiahao, Wu Xinyi, Huang Jian, Xu Xiaohui, Cai Feng, Chen Sheng, Xu Liyin, Yan Wei, Hong Yuan, Wang Yunfei, Ling Hui, Ji Jianxiong, Chen Gao, Gu Hongcang, Zhang Jianmin, Wu Qun
Department of Neurosurgery, School of Medicine, Second Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang, 310000, P. R. China.
Key Laboratory of Precise Treatment and Clinical Translational Research of Neurological Diseases, Hangzhou, Zhejiang, 310000, P. R. China.
BMC Med. 2025 Jul 1;23(1):373. doi: 10.1186/s12916-025-04164-1.
Pituitary adenomas (PAs) are benign tumors in the pituitary gland. However, 30-40% of these tumors are invasive, complicating diagnosis and treatment. Invasive pituitary adenomas (IPAs) often respond poorly to conventional therapies, emphasizing the need for better diagnostic and therapeutic strategies. Understanding DNA methylation patterns in IPAs may reveal new biomarkers and therapeutic targets, leading to more effective management of this challenging disease.
Reduced representation bisulfite sequencing (RRBS) and RNA sequencing (RNA-seq) were performed on 129 samples from the Second Affiliated Hospital of Zhejiang University, including 69 tissue samples from invasive and non-invasive pituitary adenomas (NPA) and 60 blood samples from IPA, NPA and healthy individuals. Differentially methylated regions (DMRs) and differentially expressed genes (DEGs) were identified in tissues. Pearson correlation analysis was used to identify associations between DNA methylation status and gene expression, as well as the effect of methylation on gene expression at different sites. Blood samples were analyzed to detect DMRs and DEGs, correlating with tissue-derived findings. Finally, ROC analysis and a random forest model were used to identify biomarkers for discriminating invasive from non-invasive phenotypes.
We identified 347 DMRs between IPA and NPA, of which 63% (219/347) were hypomethylated. Additionally, 543 mRNAs showed differential expression, with 350 upregulated and 193 downregulated. 17 genes demonstrated concurrent aberrant methylation and expression, primarily within introns, promoters, and CpG islands (CGIs). Notably, only protein tyrosine phosphatase receptor type T (PTPRT) exhibited a remarkably high correlation (r = 0.81) between its DNA methylation levels and mRNA expression levels. This correlation was observed within the intronic region/opensea of the gene's CGIs. Plasma sample analysis revealed 852 DMRs between IPA and NPA, with 52% (447/852) being hypomethylated. Three tumor tissue-derived blood biomarkers (MIR4535, SLC8A1-AS1, and TTC34) accurately discriminated between IPA and NPA patients with a combined AUC of 0.980. These markers also differentiated NPA from healthy controls, though with different methylation patterns.
The relationship between DNA methylation and gene expression is complex. Plasma-based DNA methylation markers can effectively discriminate between IPA and NPA, as well as between NPA and healthy individuals (N group).
垂体腺瘤（PAs）是垂体中的良性肿瘤。然而，这些肿瘤中有30%-40%具有侵袭性，使诊断和治疗变得复杂。侵袭性垂体腺瘤（IPAs）对传统疗法的反应通常较差，这凸显了对更好的诊断和治疗策略的需求。了解IPAs中的DNA甲基化模式可能会揭示新的生物标志物和治疗靶点，从而更有效地管理这种具有挑战性的疾病。
对浙江大学医学院附属第二医院的129个样本进行了简化代表性亚硫酸氢盐测序（RRBS）和RNA测序（RNA-seq），其中包括69个侵袭性和非侵袭性垂体腺瘤（NPA）的组织样本，以及60个IPA、NPA和健康个体的血液样本。在组织中鉴定出差异甲基化区域（DMRs）和差异表达基因（DEGs）。使用Pearson相关分析来确定DNA甲基化状态与基因表达之间的关联，以及甲基化对不同位点基因表达的影响。对血液样本进行分析以检测DMRs和DEGs，并与组织来源的结果进行关联。最后，使用ROC分析和随机森林模型来鉴定区分侵袭性和非侵袭性表型的生物标志物。
我们在IPA和NPA之间鉴定出347个DMRs，其中63%（219/347）为低甲基化。此外，543个mRNA显示出差异表达，其中350个上调，193个下调。17个基因表现出同时存在异常甲基化和表达，主要在内含子、启动子和CpG岛（CGIs）中。值得注意的是，只有蛋白酪氨酸磷酸酶受体T型（PTPRT）在其DNA甲基化水平和mRNA表达水平之间表现出非常高的相关性（r = 0.81）。这种相关性在该基因CGIs的内含子区域/开放海域中观察到。血浆样本分析显示IPA和NPA之间有852个DMRs，其中52%（447/852）为低甲基化。三种肿瘤组织来源的血液生物标志物（MIR4535、SLC8A1-AS1和TTC34）能够准确区分IPA和NPA患者，联合AUC为0.980。这些标志物也能将NPA与健康对照区分开来，尽管甲基化模式不同。
DNA甲基化与基因表达之间的关系很复杂。基于血浆的DNA甲基化标志物可以有效区分IPA和NPA，以及NPA和健康个体（N组）。
