A circulating tumor DNA profiling approach based on in silico background elimination guides prognosis and chemosensitivity evaluation of multiple cancers independent of matched white blood cell sequencing

Circulating tumor DNA (ctDNA) analysis increasingly provides a promising minimally invasive alternative to tissue biopsies in precision oncology. However, current methods of ctDNA mutation profiling have limited resolution because of the high background noises and false-positive rate caused by benign variants in serum cell-free DNA (cfDNA), majorly generated during clonal hematopoiesis. Although the personalized parallel white blood cells (WBC) genome sequencing suppresses the noise of clonal hematopoiesis variances (CHV) on ctDNA based liquid biopsy, the system cost and complexity restrict its application in clinical settings. To address this challenge, we introduced a Matched WBC Genome sequencing Independent CtDNA profiling (MaGIC) approach to capture informative ctDNA mutations from cfDNA background based on hybrid capture deep sequencing and in silico data mining. The MaGIC-Enricher was firstly designed to identify the scope of ctDNA representatives in serum recapitulating the recurrent mutations of tumor tissues, reaching a patient coverage of 97.7%. Then the MaGIC-Suppressor was further developed by eliminating potential benign mutant regions identified from the whole-exon-sequencing information of healthy cohorts. Moreover, the MaGIC-Measurer consisting of a key mutant region (KMR) count was designed to increase the signal-to-noise ratio of ctDNA sequencing data. As proof of principles, the MaGIC approach enables the prediction of prognosis and chemosensitivity for patients with multiple cancers when analyzing either tissue or liquid biopsy samples. We anticipate that this new approach could promote the potential utility of ctDNA detection in multiple clinical cancer contexts, thus facilitating precise cancer therapy.