Skip to content
DraconiticResearch
Search Sources API
189,280 studies31 sourcesUpdated just now
Peer-reviewedCC BY 4.0Acta Neuropathologica Communications

Diagnostic evaluation of long-read nanopore sequencing for pediatric CNS tumors

5 affiliations
  1. 1Sahlgrenska Center for Cancer Research, Department of Medical Biochemistry and Cell biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Medicinaregatan 1F, 405 30 Gothenburg, Sweden
  2. 2Department of Pediatrics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
  3. 3Childhood Cancer Centre, Queen Silvia Children’s Hospital, Sahlgrenska University Hospital, Gothenburg, Sweden
  4. 4Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
  5. 5Department of Clinical Pathology, Sahlgrenska University Hospital, Gothenburg, Sweden

Abstract

Long-read nanopore sequencing enables methylation-based CNS tumor classification while providing additional genomic information within a single assay. However, its performance across molecular features relevant to pediatric CNS tumor diagnostics and across available methylation classifiers remains incompletely characterized. We evaluated nanopore sequencing for integrated molecular characterization of pediatric CNS tumors and compared with data from DNA methylation arrays and Illumina short-read sequencing used in the clinical diagnostic work-up. Twenty tumor samples representing three major pediatric CNS tumor groups (gliomas, ependymomas and medulloblastomas) were subjected to long-read nanopore sequencing, which generated robust long-read data across all tumor groups, with a mean genome coverage of approximately 40x. Nanopore-derived copy-number profiles showed good concordance with methylation array-derived profiles (median Pearson r = 0.816). Nanopore evidence was identified for 74/78 (95%) clinically relevant small variants detected by Illumina sequencing, although 53/78 (68%) were recovered as exact high-confidence nanopore calls. Structural variant profiles showed limited breakpoint overlap and differed in the number, type, and size distribution of detected events between Illumina and Nanopore sequencing. Nanopore-derived methylation classifications were largely concordant with integrated WHO CNS5 diagnoses. Ependymomas, medulloblastomas, and pilocytic astrocytomas, were concordantly classified across all evaluated classifiers, although not all classifications reached the respective classifier-specific confidence thresholds. In contrast, diffuse gliomas showed greater variability in classification across classifiers. Downsampling indicated that concordance with integrated WHO CNS5 diagnoses remained high at substantially reduced sequencing depths, whereas the proportion of classifications reaching classifier-specific confidence thresholds was more classifier dependent. Long-read nanopore sequencing enables integrated molecular characterization of pediatric CNS tumors within a single assay, although concordance with established methods varied by genomic feature and tumor type. The preservation of methylation classification performance at reduced sequencing depth supports the feasibility of shorter sequencing workflows. Prospective studies are required to establish performance and turnaround time in routine clinical diagnostics.

Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s40478-026-02466-w.

Related

  1. Diagnostic delay as a prognostic factor for non-response to treatment and relapse in Mexican pediatric patients with central nervous system tumors
    Juan-Carlos Pérez-De Marcos, Manuel Castillejos-López, Arnoldo Aquino-Gálvez +6
    Frontiers in pediatricsPeer-reviewedCC BYFull textHuman geneticsEurope PMCPMC
  2. A prospective cross-sectional diagnostic feasibility study: musculoskeletal ultrasound for pediatric bone age evaluation
    Xingxu Zhou, Yifei Huang, Chunrong Liu +7
    Translational pediatricsPeer-reviewedCC BY-NC-NDFull textGeneral medicineEurope PMC
  3. Preclinical evaluation of ixazomib for high-risk pediatric brain tumors
    E. Janko, F. M. Walker, M. Slade +10
    bioRxivPreprintCC BY-NCFull textOncologybioRxiv
  4. Direct Amplification-Free Nanopore Sequencing of Leishmania from Cutaneous Biopsies
    F. Alkhaldi, A. S. Al Rashed, C. Frokjaer-Jensen
    medRxivPreprintAll rights reservedFull textInfectious diseasemedRxiv
  5. Production of abundant defective viral genomes by an insect-specific alphavirus revealed by nanopore sequencing
    Lu Tan, Zhihao Guo, Guoqian Gu +6
    Nature CommunicationsPeer-reviewedCC BY-NC-ND 4.0Full textEpidemiology & public healthCrossref
BibTeX
@article{vega2026diagnostic,
  title = {{Diagnostic evaluation of long-read nanopore sequencing for pediatric CNS tumors}},
  author = {Sandra Ferreyra Vega and Ryan Shun-Yuen Kwan and Ida Rahmqvist and Elizabeth Schepke and Magnus Sabel and Thomas Olsson Bontell and Teresia Kling and Helena Carén},
  journal = {Acta Neuropathologica Communications},
  year = {2026},
  month = oct,
  doi = {10.1186/s40478-026-02466-w},
  url = {https://doi.org/10.1186/s40478-026-02466-w},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Diagnostic evaluation of long-read nanopore sequencing for pediatric CNS tumors
AU  - Sandra Ferreyra Vega
AU  - Ryan Shun-Yuen Kwan
AU  - Ida Rahmqvist
AU  - Elizabeth Schepke
AU  - Magnus Sabel
AU  - Thomas Olsson Bontell
AU  - Teresia Kling
AU  - Helena Carén
PY  - 2026
DA  - 2026/10/27
JO  - Acta Neuropathologica Communications
DO  - 10.1186/s40478-026-02466-w
UR  - https://doi.org/10.1186/s40478-026-02466-w
AB  - Long-read nanopore sequencing enables methylation-based CNS tumor classification while providing additional genomic information within a single assay. However, its performance across molecular features relevant to pediatric CNS tumor diagnostics and across available methylation classifiers remains incompletely characterized. We evaluated nanopore sequencing for integrated molecular characterization of pediatric CNS tumors and compared with data from DNA methylation arrays and Illumina short-read sequencing used in the clinical diagnostic work-up. Twenty tumor samples representing three major pediatric CNS tumor groups (gliomas, ependymomas and medulloblastomas) were subjected to long-read nanopore sequencing, which generated robust long-read data across all tumor groups, with a mean genome coverage of approximately 40x. Nanopore-derived copy-number profiles showed good concordance with methylation array-derived profiles (median Pearson r = 0.816). Nanopore evidence was identified for 74/78 (95%) clinically relevant small variants detected by Illumina sequencing, although 53/78 (68%) were recovered as exact high-confidence nanopore calls. Structural variant profiles showed limited breakpoint overlap and differed in the number, type, and size distribution of detected events between Illumina and Nanopore sequencing. Nanopore-derived methylation classifications were largely concordant with integrated WHO CNS5 diagnoses. Ependymomas, medulloblastomas, and pilocytic astrocytomas, were concordantly classified across all evaluated classifiers, although not all classifications reached the respective classifier-specific confidence thresholds. In contrast, diffuse gliomas showed greater variability in classification across classifiers. Downsampling indicated that concordance with integrated WHO CNS5 diagnoses remained high at substantially reduced sequencing depths, whereas the proportion of classifications reaching classifier-specific confidence thresholds was more classifier dependent. Long-read nanopore sequencing enables integrated molecular characterization of pediatric CNS tumors within a single assay, although concordance with established methods varied by genomic feature and tumor type. The preservation of methylation classification performance at reduced sequencing depth supports the feasibility of shorter sequencing workflows. Prospective studies are required to establish performance and turnaround time in routine clinical diagnostics.  Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s40478-026-02466-w.
SN  - 2051-5960
ER  -