DNA甲基化
仿形(计算机编程)
甲基化
生物
计算生物学
表观遗传学
生物信息学
DNA
计算机科学
遗传学
基因
基因表达
操作系统
作者
Antonios Papanicolau‐Sengos,Kenneth Aldape
出处
期刊:Annual Review of Pathology-mechanisms of Disease
[Annual Reviews]
日期:2022-01-24
卷期号:17 (1): 295-321
被引量:133
标识
DOI:10.1146/annurev-pathol-042220-022304
摘要
Histomorphology has been a mainstay of cancer diagnosis in anatomic pathology for many years. DNA methylation profiling is an additional emerging tool that will serve as an adjunct to increase accuracy of pathological diagnosis. Genome-wide interrogation of DNA methylation signatures, in conjunction with machine learning methods, has allowed for the creation of clinical-grade classifiers, most prominently in central nervous system and soft tissue tumors. Tumor DNA methylation profiling has led to the identification of new entities and the consolidation of morphologically disparate cancers into biologically coherent entities, and it will progressively become mainstream in the future. In addition, DNA methylation patterns in circulating tumor DNA hold great promise for minimally invasive cancer detection and classification. Despite practical challenges that accompany any new technology, methylation profiling is here to stay and will become increasingly utilized as a cancer diagnostic tool across a range of tumor types.
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