基于全基因组 DNA 甲基化的放射组学分析与脑胶质瘤分子表型及免疫特征的相关性。

Radiogenomic profiling of global DNA methylation associated with molecular phenotypes and immune features in glioma.

机构信息

Department of General Surgery (Colorectal Surgery), The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.

Guangdong Institute of Gastroenterology, Guangzhou, Guangdong, China.

出版信息

BMC Med. 2024 Sep 2;22(1):352. doi: 10.1186/s12916-024-03573-y.

DOI:10.1186/s12916-024-03573-y

PMID:39218882

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11367996/

Abstract

BACKGROUND

The radiogenomic analysis has provided valuable imaging biomarkers with biological insights for gliomas. The radiogenomic markers for molecular profile such as DNA methylation remain to be uncovered to assist the molecular diagnosis and tumor treatment.

METHODS

We apply the machine learning approaches to identify the magnetic resonance imaging (MRI) features that are associated with molecular profiles in 146 patients with gliomas, and the fitting models for each molecular feature (MoRad) are developed and validated. To provide radiological annotations for the molecular profiles, we devise two novel approaches called radiomic oncology (RO) and radiomic set enrichment analysis (RSEA).

RESULTS

The generated MoRad models perform well for profiling each molecular feature with radiomic features, including mutational, methylation, transcriptional, and protein profiles. Among them, the MoRad models have a remarkable performance in quantitatively mapping global DNA methylation. With RO and RSEA approaches, we find that global DNA methylation could be reflected by the heterogeneity in volumetric and textural features of enhanced regions in T2-weighted MRI. Finally, we demonstrate the associations of global DNA methylation with clinicopathological, molecular, and immunological features, including histological grade, mutations of IDH and ATRX, MGMT methylation, multiple methylation-high subtypes, tumor-infiltrating lymphocytes, and long-term survival outcomes.

CONCLUSIONS

Global DNA methylation is highly associated with radiological profiles in glioma. Radiogenomic global methylation is an imaging-based quantitative molecular biomarker that is associated with specific consensus molecular subtypes and immune features.

摘要

背景

放射基因组分析为脑胶质瘤提供了有价值的影像学生物标志物和生物学见解。用于分子谱的放射基因组标志物，如 DNA 甲基化，仍有待发现，以辅助分子诊断和肿瘤治疗。

方法

我们应用机器学习方法来识别 146 例脑胶质瘤患者的分子谱相关的 MRI 特征，并为每个分子特征（MoRad）开发和验证拟合模型。为了为分子谱提供放射学注释，我们设计了两种新方法，称为放射肿瘤学（RO）和放射组学富集分析（RSEA）。

结果

生成的 MoRad 模型在对每个分子特征（包括突变、甲基化、转录和蛋白谱）进行放射组学特征分析方面表现良好。其中，MoRad 模型在定量映射全基因组甲基化方面表现出色。通过 RO 和 RSEA 方法，我们发现 T2 加权 MRI 增强区域的体积和纹理特征的异质性可以反映全基因组甲基化。最后，我们证明了全基因组甲基化与临床病理、分子和免疫特征的相关性，包括组织学分级、IDH 和 ATRX 的突变、MGMT 甲基化、多个甲基化高亚型、肿瘤浸润淋巴细胞和长期生存结果。