Unintrusive multi-cancer detection by circulating cell-free DNA methylation sequencing (THUNDER): development and independent validation studies

Early detection of cancer offers the opportunity to identify candidates when curative treatments are achievable. The THUNDER study (THe UNintrusive Detection of EaRly-stage cancers, NCT04820868) aimed to evaluate the performance of enhanced linear-splinter amplification sequencing, a previously described cell-free DNA (cfDNA) methylation-based technology, in the early detection and localization of six types of cancers in the colorectum, esophagus, liver, lung, ovary, and pancreas.A customized panel of 161 984 CpG sites was constructed and validated by public and in-house (cancer: n = 249; non-cancer: n = 288) methylome data, respectively. The cfDNA samples from 1693 participants (cancer: n = 735; non-cancer: n = 958) were retrospectively collected to train and validate two multi-cancer detection blood test (MCDBT-1/2) models for different clinical scenarios. The models were validated on a prospective and independent cohort of age-matched 1010 participants (cancer: n = 505; non-cancer: n = 505). Simulation using the cancer incidence in China was applied to infer stage shift and survival benefits to demonstrate the potential utility of the models in the real world.MCDBT-1 yielded a sensitivity of 69.1% (64.8%-73.3%), a specificity of 98.9% (97.6%-99.7%), and tissue origin accuracy of 83.2% (78.7%-87.1%) in the independent validation set. For early-stage (I-III) patients, the sensitivity of MCDBT-1 was 59.8% (54.4%-65.0%). In the real-world simulation, MCDBT-1 achieved a sensitivity of 70.6% in detecting the six cancers, thus decreasing late-stage incidence by 38.7%-46.4%, and increasing 5-year survival rate by 33.1%-40.4%, respectively. In parallel, MCDBT-2 was generated at a slightly low specificity of 95.1% (92.8%-96.9%) but a higher sensitivity of 75.1% (71.9%-79.8%) than MCDBT-1 for populations at relatively high risk of cancers, and also had ideal performance.In this large-scale clinical validation study, MCDBT-1/2 models showed high sensitivity, specificity, and accuracy of predicted origin in detecting six types of cancers.