Ultra-low-input cell-free DNA sequencing for tumor detection and characterization in a real-world pediatric brain...

Molecular profiling of pediatric central nervous system (CNS) tumors has important clinical utility for guiding diagnostic and therapeutic strategies. Cell-free DNA (cfDNA) from liquid biopsies has been used for minimally invasive tumor profiling and longitudinal disease assessment in adult oncology and pediatric hematology. However, in pediatric neuro-oncology, low cfDNA yields pose a major barrier to translating these assays from bench to bedside. Here, we implemented a low-coverage whole genome sequencing (lcWGS) assay for picogram-level cfDNA inputs and applied it to liquid biopsies from a sizeable, population-based, cross-entity pediatric CNS tumor cohort (n = 56 patients). Applying this protocol, cfDNA whole genome profiles were successfully acquired from all liquid biopsy samples (n = 61/61 serum, n = 56/56 CSF, 100%). Based on copy number variations (CNVs), circulating-tumor DNA (ctDNA) was detected in 2/61 serum (3%) and in 25/56 CSF (45%) samples across various brain tumor entities. The integration of cfDNA results with clinical data demonstrated the utility of CSF lcWGS as a biomarker assay at diagnosis to distinguish cancerous from non-cancerous pineal region lesions (n = 6 patients). Additionally, serial CSF assessment in n = 9 patients (n = 29 CSF samples) enabled minimally invasive disease monitoring, with the added value of molecular profile availability in n = 4/6 (67%) patients at relapse. Proof-of-concept data show the feasibility of serial CSF lcWGS to reveal tumor evolution, tumor heterogeneity and potential therapeutic vulnerabilities in a case of medulloblastoma and germ cell tumor. Our study underscores the clinical utility of a robust lcWGS-based liquid biopsy assay optimized for low-input samples. We identify use-cases for implementing liquid biopsies in the clinical management of pediatric CNS tumor patients and provide a strong rationale for integration into future trials.