DNA methylation–based classification has transformed the diagnosis of central nervous system (CNS) tumours. However, methylation profiling alone is insufficient for definitive diagnosis and must be integrated with genomic alterations such as single nucleotide variants, structural variants, and gene fusions. Molecular diagnostics are therefore moving towards unified sequencing approaches capable of simultaneously capturing epigenomic and genomic information within a single assay. Rapid nanopore sequencing has demonstrated the feasibility of combined methylation and genomic profiling within an intraoperative timeframe. Illumina 5-base whole-genome sequencing is a recently released short-read technology that distinguishes methylated from unmethylated cytosines, enabling integrated epigenomic and genomic analysis. Here, we compare the diagnostic performance of these long- and short-read methylation-aware sequencing platforms in CNS tumours.
We analysed a matched cohort of 30 CNS tumour samples previously characterised using a rapid nanopore diagnostic workflow. Illumina 5-base whole-genome sequencing was generated for each case, alongside conventional methylation array profiling. Tumour classification was performed using Random Forest, NanoDx, Sturgeon, and mnp-Flex, referencing Heidelberg classifier versions 11 and 12.8. Concordance between nanopore, Illumina 5-base, and standard-of-care methylation array classifications was assessed. Detection of diagnostically relevant genomic alterations, including single nucleotide variants, structural variants, and gene fusions, was compared across platforms.
Illumina 5-base sequencing demonstrated strong concordance with rapid nanopore classifications and established methylation array diagnoses. Agreement was consistent across classifiers and reference versions. Both approaches identified key diagnostic genomic alterations, supporting comprehensive molecular characterisation from a single assay.
Integrated methylation-aware sequencing platforms enabling simultaneous epigenomic and genomic profiling show robust cross-platform concordance and clinical feasibility for CNS tumour diagnostics.
S. Deacon, Inswasti Cahyani, Nadine Holmes et al.· Neuro-Oncology· 0 citations
Pediatric solid high-risk malignancies mostly lack established molecular biomarkers for early detection, minimal residual disease assessment, or treatment monitoring. Challenges include small patient numbers, limited sample volumes, low tumor mutational burden, and few recurrent alterations. Within the multicenter pediatric precision oncology program INFORM, we prospectively collected liquid biopsies from 130 pediatric patients and optimized cell-free DNA isolation and analysis. Whole-genome, whole-exome, and targeted panel sequencing were performed using liquid biopsy-adapted protocols. Integrating tissue-derived molecular profiles and orthogonal validation revealed that low-coverage whole-genome sequencing reliably detects circulating tumor DNA. An in silico ctDNA estimation score, combining fragment length and genome segment alterations, improved sensitivity and specificity to 95%, enabling plasma-based tumor detection in 93% of patients. Whole-exome and panel sequencing effectively identified clinically relevant, potentially druggable molecular targets. However, their utility varied substantially across different tumor entities, underscoring the need for entity-specific considerations in the interpretation and application of these methodologies. In-depth analyses demonstrated liquid biopsy’s potential to track tumor evolution, identifying common tumor ancestors and refining patient stratification. This study advances liquid biopsy methodologies in pediatric oncology and provides a rationale that, as SNVs are more sensitively captured by panel sequencing and WES, while CNVs are better represented by lcWGS and WES. The underlying tumor genomic profile should guide the selection of liquid biopsy assays to optimize clinical decision-making. Systematic liquid biopsy analyses within the pediatric precision oncology INFORM registry enabled a real-world, multicenter comparison of sequencing approaches across high-risk malignancies. By optimizing preanalytical and bioinformatic tools for pediatric settings, we improved plasma-based cancer detection, molecular tumor characterization, and identification of targetable alterations, laying the groundwork for integration into personalized medicine programs and clinical trials.
K. Maass, P. Puranachot, S. Volz et al.· Genome Medicine· 0 citations
