MRD4U: A path to development for personalized liquid biopsy for children with central nervous system tumors - Anthony R. Miller; Tithi Shah; Corinne N. Strawser; Adithe Rivaldi; Sarah A. Wilson; Huachun Zhong; Jocelyn M. Lucyshyn; Elizabeth AR Garfinkle; Makenna McCoy; Seth Cummins; Alejandro Otero Bravo; Peter Chang; et al. (BMC Cancer)
Abstract Background Liquid biopsy assays using cerebrospinal fluid (CSF) can revolutionize care for children with central nervous system (CNS) tumors by enabling precise monitoring of therapeutic responses and detecting recurrence or measurable residual disease (MRD). These assays can detect cell-free, circulating tumor DNA (ctDNA) via somatic alterations, though accurately measuring low-abundance ctDNA in CSF is challenging. Methods Our research focused on the optimization of next-generation sequencing library preparation from cell-free DNA (cfDNA), evaluating four commercial kits to address the low nucleic acid yield in CSF-derived cfDNA. The selected kit minimized false positives and detected somatic variants at 5% variant allele frequency using 0.1 ng input of synthetic cfDNA, suitable for low-volume CSF samples. Results We then applied our optimized workflow to six children with CNS tumors using a personalized hybrid-capture sequencing strategy (“MRD4U”), in which individualized panels were designed based on each patient’s tumor sequencing. Using MRD4U, we identified ctDNA in two samples, even though neither patient had radiographic or clinical evidence of disease at the time of liquid biopsy. Notably, one ctDNA-positive patient developed radiographic recurrence four months later, demonstrating the assay’s potential to detect molecular relapse ahead of conventional clinical measures. Conclusions These findings demonstrate applicability of our personalized MRD4U assay in early detection of disease recurrence. Unlike non-targeted or tumor-agnostic CSF liquid biopsy approaches, MRD4U leverages patient-specific genomic information to enable sensitive, tumor-informed monitoring that can be deployed across a wide range of pediatric CNS tumors. Our approach is broadly applicable to any tumor type with existing genomic data, enabling ctDNA detection across diverse diagnoses. Ultimately, this strategy may inform clinical decision-making and enable earlier therapeutic intervention.