Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment.

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole-genome sequencing (WGS). Here we now introduce MRD-EDGE, a machine-learning-guided WGS ctDNA single-nucleotide variant (SNV) and copy-number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by ~300× compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, vastly expanding its applicability within solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in TF in response to neoadjuvant immunotherapy in lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables plasma-only (non-tumor-informed) disease monitoring in advanced melanoma and lung cancer, yielding clinically informative TF monitoring for patients on immune-checkpoint inhibition.

Genomic landscape of virus-associated cancers.

It has been estimated that 15%-20% of human cancers are attributable to infections, mostly by carcinogenic viruses. The incidence varies worldwide, with a majority affecting developing countries. Here, we present a comparative analysis of virus-positive and virus-negative tumors in nine cancers linked to five viruses. We find that virus-positive tumors occur more frequently in males and show geographical disparities in incidence. Genomic analysis of 1,658 tumors reveals virus-positive tumors exhibit distinct mutation signatures and driver gene mutations and possess a lower somatic mutation burden compared to virus-negative tumors of the same cancer type. For example, compared to the respective virus-negative counterparts, virus-positive cases across different cancer histologies had less often mutations of TP53 and deletions of 9p21.3/ CDKN2 A- CDKN1A ; Epstein-Barr virus-positive (EBV+) gastric cancer had more frequent mutations of EIF4A1 and ARID1A and less marked mismatch repair deficiency signatures; and EBV-positive cHL had fewer somatic genetic lesions of JAK-STAT, NF-κB, PI3K-AKT and HLA-I genes and a less pronounced activity of the aberrant somatic hypermutation signature. In cHL, we also identify germline homozygosity in HLA class I as a potential risk factor for the development of EBV-positive Hodgkin lymphoma. Finally, an analysis of clinical trials of PD-(L)1 inhibitors in four virus-associated cancers suggested an association of viral infection with higher response rate in patients receiving such treatments, which was particularly evident in gastric cancer and head and neck squamous cell carcinoma. These results illustrate the epidemiological, genetic, prognostic, and therapeutic trends across virus-associated malignancies.

Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring.

In many areas of oncology, we lack sensitive tools to track low-burden disease. Although cell-free DNA (cfDNA) shows promise in detecting cancer mutations, we found that the combination of low tumor fraction (TF) and limited number of DNA fragments restricts low-disease-burden monitoring through the prevailing deep targeted sequencing paradigm. We reasoned that breadth may supplant depth of sequencing to overcome the barrier of cfDNA abundance. Whole-genome sequencing (WGS) of cfDNA allowed ultra-sensitive detection, capitalizing on the cumulative signal of thousands of somatic mutations observed in solid malignancies, with TF detection sensitivity as low as 10-5. The WGS approach enabled dynamic tumor burden tracking and postoperative residual disease detection, associated with adverse outcome. Thus, we present an orthogonal framework for cfDNA cancer monitoring via genome-wide mutational integration, enabling ultra-sensitive detection, overcoming the limitation of cfDNA abundance and empowering treatment optimization in low-disease-burden oncology care.