PO.MCB06.01 · 分子与细胞生物学
MIRAGE:一种以ctDNA甲基化为驱动、旨在灵敏检测微小残留病灶的计算算法
MIRAGE: A ctDNA methylation-driven computational algorithm designed for sensitive detection of minimal residual disease
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景:手术切除或治疗方案后微小残留病灶(MRD)的检测仍是一项重大临床挑战,主要原因在于治疗后血液中循环肿瘤DNA(ctDNA)浓度通常极低。在循环肿瘤细胞(CTC)无法检出或ctDNA水平低于常规检测方法阈值的情况下,DNA甲基化分析已成为一种有前景的替代方案。借助计算算法可进一步提高在循环肿瘤分数低至0.001%的癌症中对肿瘤信号的检测能力。
方法:MIRAGE(利用全基因组表观基因组学的微小残留评估,Minimal Residual Assessment using Genome-wide Epigenomics)算法采用156份样本进行验证,其中16.7%(n=26)为对照参考样本。该算法评估全基因组差异甲基化区域(DMR)的DNA甲基化模式。算法通过评估每个CpG位点甲基化和非甲基化胞嘧啶的数量并将这些值整合为一个综合甲基化评分来量化甲基化,该评分反映整体的高甲基化或低甲基化状态。所得甲基化评分再依据从非癌性健康个体参考队列建立的预设临界值进行标准化,以实现标准化解读。
结果:MIRAGE在所检测的127份临床样本(64份肿瘤,63份非癌性健康对照)中达到96.8%的特异性。在临床肿瘤样本中,64%(n=41/64)被检测为ctDNA阳性,总体灵敏度为64.1%。
结论:本研究证明了MIRAGE算法在基于ctDNA分类的微小残留检测中的特异性,特异性高。仍需在更大队列中进一步验证以获得更多临床见解。
查看英文原文 English abstract
Background: Detection of minimal residual disease (MRD) following surgical resection or a treatment regimen remains a significant clinical challenge, primarily due to the typically low concentrations of circulating tumor DNA (ctDNA) in the bloodstream post-treatment. In situations where circulating tumor cells (CTCs) are undetectable or ctDNA levels fall below the thresholds of conventional detection methods, DNA methylation analysis has emerged as a promising alternative. Utilizing computational algorithms further improve the detection of tumor signal in cancers with as low as 0.001% circulating tumor fraction.
Methods: MIRAGE (Minimal Residual Assessment using Genome-wide Epigenomics) algorithm was validated using 156 samples, among which 16.7% (n=26) were control reference samples. The algorithm assessed DNA methylation patterns across genome-wide differentially methylated regions (DMRs). The algorithm quantifies methylation by evaluating the number of methylated and unmethylated cytosines at each CpG site and integrating these values into a composite methylation score, reflecting overall hyper- or hypomethylation. The resulting methylation score is further normalized against a predefined cut-off established from a reference cohort of non-cancerous healthy individuals to enable standardized interpretation.
Results: MIRAGE achieved a specificity of 96.8% from 127 clinical samples (64 tumor, 63 non-cancerous healthy controls) tested. Among the clinical tumor samples, 64% (n=41/64) were detected as ctDNA-positive which showed an overall sensitivity of 64.1%.
Conclusion: The study demonstrates the specificity of MIRAGE algorithm for ctDNA classification-based minimal residual detection with high specificity. Further validation on larger cohort is still warranted to show more clinical insights.
利益披露 Disclosure
G. Shafi, None..
A. Ramesh, None..
S. Iyer, None..
A. Sornapudi, None..
A. D'Souza, None..
S. Halder, None..
B. Jadhav, None..
S. Prajapati, None..
M. Uttarwar, None.