基于 DNA 甲基化景观的阶段差异化集成建模揭示了结直肠癌进展中的显著生物标志物和预后特征。
Stage-differentiated ensemble modeling of DNA methylation landscapes uncovers salient biomarkers and prognostic signatures in colorectal cancer progression.
机构信息
Department of Bioinformatics, School of Chemical and BioTechnology, SASTRA Deemed University, Thanjavur, India.
出版信息
PLoS One. 2022 Feb 24;17(2):e0249151. doi: 10.1371/journal.pone.0249151. eCollection 2022.
BACKGROUND
Aberrant DNA methylation acts epigenetically to skew the gene transcription rate up or down, contributing to cancer etiology. A gap in our understanding concerns the epigenomics of stagewise cancer progression. In this study, we have developed a comprehensive computational framework for the stage-differentiated modelling of DNA methylation landscapes in colorectal cancer (CRC).
METHODS
The methylation β-matrix was derived from the public-domain TCGA data, converted into M-value matrix, annotated with AJCC stages, and analysed for stage-salient genes using an ensemble of approaches involving stage-differentiated modelling of methylation patterns and/or expression patterns. Differentially methylated genes (DMGs) were identified using a contrast against controls (adjusted p-value <0.001 and |log fold-change of M-value| >2), and then filtered using a series of all possible pairwise stage contrasts (p-value <0.05) to obtain stage-salient DMGs. These were then subjected to a consensus analysis, followed by matching with clinical data and performing Kaplan-Meier survival analysis to evaluate the impact of methylation patterns of consensus stage-salient biomarkers on disease prognosis.
RESULTS
We found significant genome-wide changes in methylation patterns in cancer cases relative to controls agnostic of stage. The stage-differentiated models yielded the following consensus salient genes: one stage-I gene (FBN1), one stage-II gene (FOXG1), one stage-III gene (HCN1) and four stage-IV genes (NELL1, ZNF135, FAM123A, LAMA1). All the biomarkers were significantly hypermethylated in the promoter regions, indicating down-regulation of expression and implying a putative CpG island Methylator Phenotype (CIMP) manifestation. A prognostic signature consisting of FBN1 and FOXG1 survived all the analytical filters, and represents a novel early-stage epigenetic biomarker / target.
CONCLUSIONS
We have designed and executed a workflow for stage-differentiated epigenomic analysis of colorectal cancer progression, and identified several stage-salient diagnostic biomarkers, and an early-stage prognostic biomarker panel. The study has led to the discovery of an alternative CIMP-like signature in colorectal cancer, reinforcing the role of CIMP drivers in tumor pathophysiology.
背景
异常的 DNA 甲基化通过表观遗传作用使基因转录率上升或下降，导致癌症的发生。我们对癌症阶段性进展的表观基因组学了解存在差距。在这项研究中，我们开发了一个全面的计算框架，用于对结直肠癌（CRC）的 DNA 甲基化景观进行阶段区分建模。
方法
甲基化 β 矩阵来自公共领域的 TCGA 数据，转换为 M 值矩阵，用 AJCC 分期注释，并使用涉及甲基化模式和/或表达模式阶段区分建模的集合方法分析分期突出的基因。使用对照（调整后的 p 值<0.001 和|M 值对数倍数变化|>2）的对比识别差异甲基化基因（DMG），然后使用一系列所有可能的两两分期对比（p 值<0.05）过滤差异甲基化基因，以获得分期突出的 DMG。然后对这些 DMG 进行共识分析，然后与临床数据匹配，并进行 Kaplan-Meier 生存分析，以评估共识分期突出生物标志物的甲基化模式对疾病预后的影响。
结果
我们发现相对于无分期的对照，癌症病例中存在全基因组范围内的甲基化模式的显著变化。阶段区分模型产生了以下共识突出的基因：一个 I 期基因（FBN1），一个 II 期基因（FOXG1），一个 III 期基因（HCN1）和四个 IV 期基因（NELL1、ZNF135、FAM123A、LAMA1）。所有生物标志物在启动子区域均显著高甲基化，表明表达下调，并暗示潜在的 CpG 岛甲基化表型（CIMP）表现。由 FBN1 和 FOXG1 组成的预后特征在所有分析过滤器中均幸存下来，代表一种新的早期表观遗传生物标志物/靶标。
结论
我们设计并执行了结直肠癌进展的阶段区分表观基因组学分析的工作流程，并鉴定了几个分期突出的诊断生物标志物和一个早期预后生物标志物组。该研究导致发现了结直肠癌中的替代 CIMP 样特征，加强了 CIMP 驱动因素在肿瘤病理生理学中的作用。
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