Joint fragmentomic and methylation signatures of cfDNA for cancer detection

Abstract

Non-invasive detection of cancer by analyzing cell-free DNA (cfDNA) is a rapidly growing field for liquid biopsies. Many methods focus on only one omic type (e.g. SNVs, SVs, methylation, fragmentomics) for discovery and validation of cancer-associated biomarkers. The utilization of more than one omic type is an ongoing challenge due to the lack of sufficient material in cfDNA for multiple assays.

Addressing these limitations, our study presents an innovative nanopore sequencing approach that analyzes cfDNA molecules at single molecule resolution for both methylation and fragmentomic data, requiring only single nanograms or less of cfDNA without PCR amplification. Leveraging novel data analytics and machine learning frameworks, we achieved single molecule resolution of methylation and fragment sizes.

Our analysis of nearly 1,000 individuals, including early-stage breast and colon cancer patients, revealed that integrating multi-omic cfDNA profiles enhances cancer detection. Our statistical framework evaluates both methylation and fragmentomic indicators, benefiting from nanopore sequencing's ability to simultaneously assess methylation and fragment size from the same molecule. We identified a correlation between cancer and the prevalence of mononucleosomes and smaller cfDNA fragments, improving early detection. We observed recurrent CpG sites across samples specific to nucleosome type, which were specific to cancer-associated pathways.

Overall, our study demonstrates the power of nanopore-based cfDNA sequencing for developing joint multi-omic profiles for cancer detection. This may have potentially significant future clinical utility for high accuracy non-invasive early detection of cancer from blood.

Biography

Dr. Billy Lau is an Instructor in the Division of Oncology at Stanford University School of Medicine. His research focus is on leveraging genome technology for cancer detection, and for studying human genomic variation. Dr. Lau received his doctorate from Harvard University in Engineering Sciences, and completed his post-doctoral training with Dr. Hanlee Ji at Stanford University. He has also received the NHGRI’s Genomic Innovator Award, where he focuses on building tools to maximize information from single molecules and cells.