Introduction: Cell-free DNA (cfDNA) contains multiple layers of biological information, including epigenetic modifications, genetic alterations and fragmentation patterns that are informative for cancer detection. However, these features are typically profiled using separate assays, increasing sample requirements and analytical complexity. We evaluated 6-base sequencing’s ability to simultaneously capture complementary cfDNA signals from a single sample and support multimodal biomarker discovery in colorectal cancer (CRC).
Methods: Using duet evoC, we sequenced 10 ng cfDNA from healthy individuals and patients with Stage I-IV CRC. The assay simultaneously identifies the four canonical bases, distinguishes 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) and preserves native fragmentomic information. This enabled concurrent extraction of epigenetic features derived from 5mC and 5hmC profiles, genetic features including sequence variation and mutational signatures, and fragmentomic features including fragment length distributions, nucleosome occupancy patterns and 6-base end motifs.
Results: Independent machine-learning classifiers trained on epigenetic, genetic or fragmentomic features discriminated CRC from healthy, demonstrating that all modalities capture disease-associated information. However, the relative contribution of biomarker classes varied across disease stages and samples, indicating that distinct cfDNA features reflect complementary aspects of tumour biology. Epigenetic, genetic and fragmentomic classifiers showed overlapping but non-identical classification patterns, suggesting substantial orthogonality between modalities. Integration of modality-specific predictions consistently improved performance compared with individual models, highlighting the value of combining multiple cfDNA-derived signals within a unified analytical framework.
Conclusions: These findings demonstrate that simultaneous profiling of methylation, hydroxymethylation, mutations and fragmentation patterns can provide a more comprehensive view of tumour-associated biology than any single modality alone. By preserving multiple complementary biomarker classes within a single workflow, 6-base sequencing enables adaptive multimodal liquid biopsy strategies that accommodate biological heterogeneity across patients and disease stages. This integrated approach provides a foundation for next-generation biomarker models that leverage the most informative cfDNA signals, supporting more precise strategies for cancer detection and monitoring.
