在癌症和无细胞DNA中全基因组重复的景观
Akshaya V Annapragada1, Noushin Niknafs1, James R White1
1Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Science translational medicine
|March 13, 2024
概括
我们开发了ARTEMIS来分析癌症基因组中的重复元素,发现新的瘤特异性变化. 这种方法有助于早期发现癌症,并从无细胞DNA识别瘤起源.
科学领域:
- 基因组学就是基因组学.
- 癌症生物学 癌症生物学
- 生物信息学是一种生物信息学.
背景情况:
- 在癌症中,重复性DNA序列的遗传变化很常见,但很难用标准测序来研究.
- 描述这些重复的元素对于理解癌症的发展和进展至关重要.
研究的目的:
- 开发一种新的计算方法,用于识别和分析全基因组测序数据中的重复元素.
- 在各种癌症类型的重复元素景观中调查瘤特异性变化.
- 探索重复元件分析在早期癌症检测和来源识别方面的潜力.
主要方法:
- 开发了ARTEMIS (dISease中重复元素的分析),这是全基因组测序数据的 de novo kmer 发现方法.
- 从1975名癌症患者的2837个组织和血样本中分析了12亿公里.
- 在全基因组重复景观和无细胞DNA碎片化概况上利用机器学习.
主要成果:
- 确定了1280种瘤特异性的重复元素类型,包括820种在人类癌症中改变的新元素.
- 发现重复元素在驱动基因区域中得到丰富,并受到结构和表观遗传变化的影响.
- 在cfDNA中的重复景观上使用机器学习实现了早期肺癌和肝癌的检测.
- 证明了非侵入性地识别瘤组织起源的能力.
结论:
- 重复元素景观的广泛变化是人类癌症的特征.
- 阿特米斯提供了一种强大的方法来检测和表征癌症中重复元素的变化.
- 重复元素分析对改善早期癌症检测,诊断和疾病监测具有显著的前景.
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