Format

Send to

Choose Destination
Sci Transl Med. 2020 Jan 1;12(524). pii: eaax7533. doi: 10.1126/scitranslmed.aax7533.

Circulating tumor DNA methylation profiles enable early diagnosis, prognosis prediction, and screening for colorectal cancer.

Author information

1
Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, P. R. China.
2
Guangzhou Youze Biological Pharmaceutical Technology Company Ltd., Guangzhou 510005, P.R. China.
3
Huazhong University of Science and Technology Tongji Medical College, Wuhan 430030, P. R. China.
4
Guangzhou Women and Children's Medical Center, Guangzhou 510623, P. R. China.
5
Shanghai General Hospital, Shanghai 200080, P. R. China.
6
Molecular Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China.
7
Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, P. R. China.
8
Faculty of Medicine, Macau University of Science and Technology, Macau 999078, P. R. China.
9
Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, P. R. China. xurh@sysucc.org.cn.

Abstract

Circulating tumor DNA (ctDNA) has emerged as a useful diagnostic and prognostic biomarker in many cancers. Here, we conducted a study to investigate the potential use of ctDNA methylation markers for the diagnosis and prognostication of colorectal cancer (CRC) and used a prospective cohort to validate their effectiveness in screening patients at high risk of CRC. We first identified CRC-specific methylation signatures by comparing CRC tissues to normal blood leukocytes. Then, we applied a machine learning algorithm to develop a predictive diagnostic and a prognostic model using cell-free DNA (cfDNA) samples from a cohort of 801 patients with CRC and 1021 normal controls. The obtained diagnostic prediction model discriminated patients with CRC from normal controls with high accuracy (area under curve = 0.96). The prognostic prediction model also effectively predicted the prognosis and survival of patients with CRC (P < 0.001). In addition, we generated a ctDNA-based molecular classification of CRC using an unsupervised clustering method and obtained two subgroups of patients with CRC with significantly different overall survival (P = 0.011 in validation cohort). Last, we found that a single ctDNA methylation marker, cg10673833, could yield high sensitivity (89.7%) and specificity (86.8%) for detection of CRC and precancerous lesions in a high-risk population of 1493 participants in a prospective cohort study. Together, our findings showed the value of ctDNA methylation markers in the diagnosis, surveillance, and prognosis of CRC.

Supplemental Content

Full text links

Icon for HighWire
Loading ...
Support Center