Liquid biopsies and cell-free DNA (cfDNA) offer minimally invasive methods for the diagnosis and monitoring of Ewing Sarcoma (EwS). EwS have a low tumour mutational burden and their detection with plasma cfDNA is challenging. We hypothesised that analysing the cfDNA methylome and fragmentome could enhance sensitivity for detecting EwS and identifying disease recurrence. Using T7-MBD-seq, we conducted whole-genome and methylome sequencing of cfDNA from 87 serial samples of 23 patients with EwS and 3 patients with CIC-rearranged sarcoma (CIC). With EwingSign, a new machine learning model, we identified EwS or CIC in a test set for 11 out of 16 patients at diagnosis and 15 out of 18 clinically confirmed relapse events. 0 out of 24 non-cancer controls (NCC) were detected positive with EwingSign. When combined with global and regional fragmentome analysis, all 18 relapse cases were detected, with 15/18 detected by 2 or more modalities, and 1 out of 24 NCC was detected by one modality. These findings indicate that cfDNA methylome and fragmentome analysis, if validated in a larger cohort, could improve disease detection, monitoring and relapse identification in patients with EwS.
THE PAPER EXPLAINED
Problem
Ewing sarcoma (EwS) is a rare and aggressive cancer with a low tumour mutational burden, making its detection through plasma cell-free DNA (cfDNA) challenging. Current liquid biopsy approaches often lack sensitivity for early diagnosis and relapse monitoring, creating an unmet need for improved non-invasive biomarkers.
Results
Eighty-seven plasma cfDNA from 23 patients with EwS and three patients with CIC-rearranged sarcoma were sequenced with T7-MBD seq, a method enabling the recovery of the genome, methylome and fragmentome of cfDNA.
EwingSign, a machine learning model to identify EwS or CIC, was developed, trained and tested using methylome datasets. Applied to plasma cfDNA, EwingSign identified the majority of patients with EwS and CIC at diagnosis and relapse, with no false positive.
cfDNA size distribution, regional and local fragmentation patterns can be modified in cancer patients. Such fragmentomic signals were altered and detectable using T7-MBD seq in most plasma of patients with EwS or CIC at diagnosis and relapse. Integrating methylome and fragmentome data detected all cases at relapse.
Impact
Our findings suggest that cfDNA methylome and fragmentome profiling can improve sensitivity for EwS detection and relapse identification. If validated in larger cohorts, this strategy could enable more accurate, minimally invasive disease monitoring and guide timely clinical interventions for patients with EwS.
