category
bioRxiv
date
Feb 24, 2026
slug
status
Published
summary
开发了整合全基因组甲基化组与转录组数据的基因中心化平台,通过背景感知过滤和变异阈值筛选,实现复杂样本中肿瘤特异性甲基化标志物的精准识别;利用甲基化敏感限制酶qPCR验证,成功区分多种肿瘤类型并发现亚型特异性标志物。
tags
测序技术
核酸蛋白工具酶
type
Post

📄 原文题目

Systematic identification of DNA methylation biomarkers for tumor-type-specific detection

🔗 原文链接

💡 AI 核心解读

开发了整合全基因组甲基化组与转录组数据的基因中心化平台,通过背景感知过滤和变异阈值筛选,实现复杂样本中肿瘤特异性甲基化标志物的精准识别;利用甲基化敏感限制酶qPCR验证,成功区分多种肿瘤类型并发现亚型特异性标志物。

📝 英文原版摘要

DNA methylation biomarkers for cancer diagnostics often underperform when tumor and background tissues share epigenetic programs, or when complex specimens with mixed cellular composition dilute tumor-derived signals and increase variability. To address these limitations, we developed a gene-centric, browser-based discovery platform that integrates genome-wide methylomes with matched transcriptomes and reference layers spanning pan-cancer tissues and leukocytes, enabling background-aware filtering beyond binary tumor-normal contrasts. Candidate loci are prioritized using combined thresholds on methylation effect size and intra-group variability to penalize stochastic and heterogeneous variation. In colorectal cancer, methylation-sensitive restriction enzyme quantitative PCR (MSRE-qPCR) validation in independent tissue cohorts confirmed multiple candidate loci with AUCs of 0.81-1.00. Using the same framework, MSRE-qPCR validation distinguished hepatocellular carcinoma from cirrhotic liver, and analysis of public tumor methylomes identified subtype-specific markers in lung adenocarcinoma and squamous-cell carcinoma. This resource bridges genome-scale epigenomic discovery with clinically accessible PCR-based methylation assays.
促肾上腺皮质激素类似物ACTH(4-7)PGP通过减少神经炎症并挽救神经传递、突触生成和轴突脱髓鞘,延迟黏多糖贮积症III型谱系疾病的神经系统表现超越对齐:多模态细胞基础模型需要协同整合
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