AMP 2025

Integrating molecular data is pivotal in CNS tumour diagnostics, yet conventional assays are constrained by technical complexity, cost, and long turnaround times. We developed Rapid-CNS2, an adaptive-sampling based nanopore sequencing workflow, and clinically validated it in a multicentre study of 301 archival and prospective cases, including 18 sequenced intraoperatively. The optimised pipeline delivers real-time methylation classification and genome-wide copy-number profiling within a 30-minute intraoperative window, and completes molecular profiling within 24 hours, reporting mutations, copy-number variants, gene fusions, and MGMT promoter status. Across the study, misleading results were rare (<2%), supporting reliability for routine and intraoperative use.  To expand access to methylation-based diagnosis, we developed MNP-Flex, a platform-agnostic classifier covering 184 CNS tumour classes compatible with the latest version of the Heidelberg classifier. In validation across a global cohort of >78,000 frozen and FFPE samples spanning five technologies, MNP-Flex achieved 99.6% accuracy at the methylation-family level and 99.2% at the class level using clinically actionable thresholds.  Together, these results demonstrate rapid end-to-end turnaround (minutes for intraoperative calls;24 hours for full profiling), high analytical performance with very low rates of misleading outputs, and broad technical compatibility, enabling scalable deployment across centres. This clinically validated workflow provides timely, comprehensive molecular characterisation to underpin evidence-based decision-making in CNS tumour care.

Despite the critical role of DNA methylation, clinical implementations harnessing its promise have not been described in acute myeloid leukemia. Utilizing DNA methylation from 3314 leukemia patient samples across 11 harmonized cohorts, we describe the Acute Leukemia Methylome Atlas, which includes robust models capable of accurately predicting AML subtypes. A genome-wide prognostic model as well as a targeted panel of 38 CpGs significantly predict five-year survival in our pediatric and adult test cohorts. To accelerate rapid clinical utility, we develop a specimen-to-result protocol that uses long-read nanopore sequencing and machine learning to characterize patients’ whole genomes and epigenomes. Clinical validation on patient samples confirms high concordance between epigenomic signatures and genomic lesions, though uniquely rare karyotypes remained challenging due to limited available training data. These results unveil the potential for increased affordability, speed, and accuracy for patients in need of complex molecular diagnosis and prognosis.

Asuragen’s recently launched Carrier Plus assay leverages amplification-based nanopore sequencing to enable high-confidence characterization of technically challenging genes included in the ACMG Tier 3 carrier screening recommendations in a single workflow. This presentation will highlight results from a global multisite evaluation of the assay’s performance and share preliminary data on expanded content designed to address additional complex regions and genes that remain difficult to resolve with conventional methods.

Facioscapulohumeral muscular dystrophy (FSHD) is caused by contractions in the D4Z4 repeat array on chromosome 4 and epigenetic dysregulation of the DUX4 gene. Current diagnostic methods rely on a combination of optical genome mapping, methylation-sensitive Southern blotting, and NGS. These approaches can be labor-intensive and have limited resolution. Here, we present an Oxford Nanopore sequencing-based approach that accurately resolves both short pathogenic and long wild-type D4Z4 arrays, using 30 kb reads to generate haplotype-resolved local assemblies. Ultra-long (100 kb+) reads that span the entirety of some arrays were used to confirm the results, up to 58 repeat units. In addition, methylation analysis revealed hypomethylation in short affected alleles, and hypermethylation in unaffected copies, revealing additional mechanistic confirmation in FSHD1. Finally, FSHD2-like samples with DNMT3B mutations showed global reduction in D4Z4 methylation, demonstrating pathogenic variant detection, D4Z4 measurement, and methylation readout from a single assay. This workflow offers a scalable, high-resolution alternative to traditional methods, with potential for future streamlined clinical FSHD analysis.