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AI in Cancer Research / AI+癌症研究Liquid Biopsy & ctDNA

Nitzan Rosenfeld

尼曾·罗森菲尔德

PhD

🏢University of Cambridge / CRUK Cambridge Institute(剑桥大学 / 英国癌症研究剑桥研究所)🌐UK

Professor; Senior Group Leader教授;高级研究组组长

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Key Papers
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Awards
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Key Contributions

👥Biography 个人简介

Nitzan Rosenfeld is a Professor and Senior Group Leader at the CRUK Cambridge Institute, University of Cambridge. He is one of the world's leading developers of circulating cell-free DNA (cfDNA) and ctDNA analytical technologies for cancer early detection and monitoring. Rosenfeld's laboratory has made key discoveries about the biological properties of cfDNA including nucleosome positioning patterns, DNA fragmentation size distributions, and methylation signatures that differ between cancer patients and healthy individuals. These insights enabled development of low-tumor-fraction detection methods. He was a co-founder and early scientific contributor to GRAIL (now Illumina GRAIL), the company developing the Galleri multi-cancer early detection blood test now in clinical trials and CE-marked in Europe. His work bridges fundamental cancer biology with clinical liquid biopsy technology.

Nitzan Rosenfeld 是剑桥大学英国癌症研究剑桥研究所的教授和高级研究组组长。他是液体活检(cfDNA/ctDNA)分析技术用于癌症早期检测和监测领域的世界顶级开发者之一。 Rosenfeld的实验室对cfDNA的生物学特性做出了关键发现,包括核小体定位模式、DNA片段化大小分布以及癌症患者与健康人之间不同的甲基化特征。这些发现推动了低肿瘤分数检测方法的开发。

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🧪Research Fields 研究领域

ctDNA Technology DevelopmentctDNA技术开发
Methylation Liquid Biopsy甲基化液体活检
Cancer-Specific DNA Fragmentation癌症特异性DNA片段化
GRAIL & Multi-Cancer Early DetectionGRAIL与多癌种早期检测
Tumor Evolution from cfDNA从cfDNA研究肿瘤进化

🎓Key Contributions 主要贡献

cfDNA Fragmentation & Nucleosome Positioning Analysis

Discovered that tumor-derived cfDNA has distinct fragmentation size distributions and nucleosome positioning patterns that differ from normal cfDNA, enabling cancer detection from fragmentation pattern analysis without mutation calling.

Methylation-Based Cancer Detection

Developed tissue-of-origin methylation signatures from cfDNA enabling simultaneous cancer detection and tumor site prediction from blood — the basis for the Galleri MCED test's tissue of origin signal.

Ultra-Sensitive ctDNA Detection Methods

Developed INVAR and other statistical methods for detecting ultra-rare ctDNA variants in low-burden settings, pushing liquid biopsy sensitivity to detect 1 cancer cell equivalent in 100,000 normal cells.

GRAIL Galleri Test Contribution

Co-founded and provided key scientific contributions to GRAIL, whose Galleri multi-cancer early detection blood test detects 50+ cancer types and is in multiple large clinical trials.

Representative Works 代表性著作

[1]

Circulating tumor DNA analysis detects minimal residual disease and predicts recurrence in patients with Stage II colon cancer

Science Translational Medicine (2016)

Demonstrated ctDNA for minimal residual disease detection with clinical utility for adjuvant therapy decisions.

[2]

Genome-wide cell-free DNA fragmentation in patients with cancer

Nature (2019)

Landmark study revealing that cancer patients have distinctive genome-wide cfDNA fragmentation patterns linked to nucleosome positioning, enabling cancer detection from fragmentation alone.

🏆Awards & Recognition 奖项与荣誉

🏆European Research Council Consolidator Grant
🏆AACR Cancer Research Fellow
🏆CRUK Programme Award
🏆Royal Society Wolfson Research Merit Award

📄Data Sources 数据来源

Last updated: 2026-04-05 | All information from publicly available academic sources

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