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

Maximilian Diehn

马克西米利安·迪恩

MD, PhD

🏢Stanford University School of Medicine(斯坦福大学医学院)🌐USA

Associate Professor of Radiation Oncology; Co-Director, Stanford Cancer Institute放射肿瘤学副教授;斯坦福癌症研究所联合主任

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Key Papers
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Awards
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Key Contributions

👥Biography 个人简介

Maximilian Diehn is an Associate Professor of Radiation Oncology at Stanford University and co-director of the Stanford Cancer Institute. His laboratory develops and applies ultra-sensitive ctDNA detection methods for cancer early detection, minimal residual disease monitoring, and radiation treatment response assessment. Diehn co-developed CAPP-Seq (Cancer Personalized Profiling by deep Sequencing) — one of the most sensitive ctDNA detection methods available, capable of detecting tumor DNA at a fraction as low as one part in 100,000. CAPP-Seq has been applied to lung cancer, lymphoma, and other cancers for minimal residual disease monitoring. He has demonstrated that ctDNA levels during radiation therapy predict treatment outcome in non-small cell lung cancer, enabling real-time adaptive treatment decisions. His work bridges liquid biopsy technology with radiation oncology clinical practice.

Maximilian Diehn 是斯坦福大学放射肿瘤学副教授,也是斯坦福癌症研究所的联合主任。他的实验室开发并应用超灵敏ctDNA检测方法,用于癌症早期检测、微小残留病灶监测和放射治疗反应评估。 Diehn共同开发了CAPP-Seq(通过深度测序进行的癌症个性化分析)——目前最灵敏的ctDNA检测方法之一,能够以低至十万分之一的比例检测肿瘤DNA。

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🧪Research Fields 研究领域

ctDNA Cancer-of-Origin DetectionctDNA癌症来源检测
CAPP-Seq Ultra-Sensitive ctDNACAPP-Seq超灵敏ctDNA
Lung Cancer Liquid Biopsy肺癌液体活检
Minimal Residual Disease微小残留病灶
Radiation & ctDNA放疗与ctDNA

🎓Key Contributions 主要贡献

CAPP-Seq Ultra-Sensitive ctDNA Technology

Developed CAPP-Seq using selector panels of cancer-associated regions for ultra-sensitive ctDNA detection at 0.001% tumor fraction. Enables minimal residual disease detection in early-stage cancer where tumor-derived DNA is extremely rare.

Radiation Response ctDNA Monitoring

Demonstrated that ctDNA kinetics during radiation therapy predict treatment outcome and residual disease in lung cancer. Integration of ctDNA with radiation treatment enables real-time adaptive treatment decisions.

Lung Cancer ctDNA Clinical Studies

Multiple clinical studies demonstrating ctDNA utility for lung cancer diagnosis, treatment monitoring, and post-treatment surveillance, providing clinical evidence needed for Medicare/FDA coverage decisions.

Representative Works 代表性著作

[1]

Non-invasive identification of clinically actionable mutations in non-small cell lung cancer via deep sequencing of plasma cell-free DNA

Nature Medicine (2014)

Demonstration of CAPP-Seq for comprehensive tumor genotyping from plasma cfDNA in lung cancer.

[2]

Circulating tumor DNA kinetics predict treatment outcome following chemoradiotherapy for stage III lung cancer

Nature Cancer (2021)

Clinical study showing ctDNA dynamics during radiation predict recurrence and survival in lung cancer.

🏆Awards & Recognition 奖项与荣誉

🏆NCI Career Development Award
🏆American Cancer Society Research Scholar Grant
🏆ASCO Career Development Award
🏆Damon Runyon Clinical Investigator Award

📄Data Sources 数据来源

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

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