Sun Yat Sen University Cancer Center, Laboratory of Oncology in South China, Guangzhou, China
Huiyan Luo , Pansong Li , Wei Wei , Yong-Bin Lin , Hong Yang , Han Yang , Kong-Jia Luo , Xiaoman Hu , Haibo Qiu , Shu-Qiang Yuan , Yuan-fang Li , Xiao-Jun Lin , Bo-kang Cui , Li Xu , Rong-Xin Zhang , Wenhua Fan , Chunyan Lan , Ting Wan , Qi-hua Zhang , Rui-Hua Xu
Background: Early screening effectively reduces mortality associated with cancer. Currently, most cancers lack effective screening paradigms. We developed blood-based multi-cancers early detection (MCED) and cancer signal origin (CSO) approaches in 8 types of cancers including esophageal, stomach, colorectal, pancreatic, liver, lung, breast and ovarian cancer. Methods: DNA methylation data generated based on GM-seq by public and internal whole genome methylation data. Based on these data, a panel of 155,362 CpG sites spanning the 2.0M genome was constructed and validated. We enrolled a case-control cohort of 746 participants (522 cancers, 224 non-cancers) for MCED model development. cell-free DNA (cfDNA) was isolated from 10 ml peripheral blood from each participant. A targeted methylation sequencing of cfDNA in plasma baseline was established using 224 non-cancers blood samples for 8 types of cancers. Finally, we developed a MCED model named AMBER for distinguishing cancer from non-cancer individuals. Results: DNA methylation data were from 8 types of cancers (cancer tissues: n=812, adjacent/normal tissues: n=416, cancer peripheral bloods: n=624, normal peripheral bloods: n=503) in internal and Infinium Human Methylation 450K array (cancer tissues: n=5000+, adjacent/normal tissues: n=1000+) from public data. 224 non-cancer individuals (healthy: n=196, cancer benign: n=28, male: female, 54.3%: 45.7%) were collected as control, while 522 cancer patients (male: female, 50.0%: 50.0%, stage I 26.9%, II 21.1%) from esophageal (n=56, stage I: n=10), stomach (n=47, stage I: n=11), colorectal (n=72, stage I: n=16), pancreatic (n=64, stage I: n=16), liver (n=69, stage I: n=22), lung (n=103, stage I: n=46), breast (n=41) and ovarian cancer (n=70, stage I: n=17). AMBER showed 99.1% specificity and total sensitivity 77.2% (95% confidence interval (CI): 73.4% to 80.7%). Of them, 56.8% (95% CI: 48.2% to 65.2%) of all stage I cases were detected, 70.6% (95% CI: 61.2% to 79.0%) for stage II, 84.5% (95% CI: 77.6% to 89.9%) for stage III, and 96.7% (95% CI: 91.8% to 99.1%) for stage IV. Strikingly, for stage I cancers, the sensitivity of esophageal, stomach, colorectal, pancreatic, liver, lung and ovarian cancer were 80.0%, 63.6%, 43.8%, 62.5%, 86.4%, 30.4% and 82.4% respectively. The sensitivity of esophageal, stomach, colorectal, pancreatic, liver, lung, breast and ovarian cancer reached 91.1%, 76.6%, 75.0%, 78.1%, 94.2%, 55.3%, 65.9% and 90.0%. For CSO model, the accuracy of TPO1 and TPO2 was 78.9% (95% CI: 74.6% to 82.8%) and 89.1% (95% CI: 85.6% to 92.0%). Conclusions: Our MCED tests demonstrated superior performance in detecting 8 types of cancers, especially early cancer screening, by utilizing cfDNA methylation information. It suggests the model can complement lack of multi-cancers early detection.
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