Systematic benchmarking of multi-modal approaches for tumor-naive ctDNA detection and quantification
Qi, T.; Odinokov, D.; Lakshmanan, L. N.; Grachet, N. G.; Lou, M.; Saelee, S.; Garcia-Montoya, G.; Mun, W. P.; Rahman, R. C.; Asgharian, H.; Yi, A. T. X.; Pyone, N. H. Y.; Wang, L. Y.; Tan, G. T.; Carrie, H.; Lim, A.; Ting, L. Y.; Hsia, A. G. H.; Yean, P. P. S.; Ngo, S.; Snyder, J.; Kaur, H.; Tan, A.; Yap, Y. S.; Tan, D. S.; Tan, I. B. H.; Penkler, J.-A.; Utiramerur, S.; Kumar, D.; Skanderup, A. J.
Show abstract
Longitudinal monitoring of circulating tumor DNA (ctDNA) has emerged as a promising framework for characterizing treatment response dynamics in cancer. Scalable tumor-naive approaches for quantifying ctDNA often involve whole-genome sequencing (WGS) or DNA methylation profiling, but their comparative performance and capacity for complementary integration remain poorly understood. Here we systematically benchmarked tumor-naive WGS- and methylation-based ctDNA quantification methods using plasma from 150 patients with colorectal, lung and breast cancer. Using paired high-depth WGS and EM-seq data, we generated 40,000 in silico samples and evaluated detection accuracy, limits of detection (LoD) and quantification (LoQ) across cancer types and sequencing depths (0.1x-30x). We further assessed single- and multimodal method combinations, identifying conditions under which integrated approaches enhance analytical performance for detection and quantification relative to single modalities. This benchmark delineates key performance trade-offs and provides a practical framework to support method development and guide future research applications in ctDNA-based biomarker studies.
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