Journal Article DKFZ-2017-05542

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Next-generation sequencing in routine brain tumor diagnostics enables an integrated diagnosis and identifies actionable targets.

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2016
Springer Berlin

Acta neuropathologica 131(6), 903 - 910 () [10.1007/s00401-015-1519-8]
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Abstract: With the number of prognostic and predictive genetic markers in neuro-oncology steadily growing, the need for comprehensive molecular analysis of neuropathology samples has vastly increased. We therefore developed a customized enrichment/hybrid-capture-based next-generation sequencing (NGS) gene panel comprising the entire coding and selected intronic and promoter regions of 130 genes recurrently altered in brain tumors, allowing for the detection of single nucleotide variations, fusions, and copy number aberrations. Optimization of probe design, library generation and sequencing conditions on 150 samples resulted in a 5-workday routine workflow from the formalin-fixed paraffin-embedded sample to neuropathological report. This protocol was applied to 79 retrospective cases with established molecular aberrations for validation and 71 prospective cases for discovery of potential therapeutic targets. Concordance of NGS compared to established, single biomarker methods was 98.0 %, with discrepancies resulting from one case where a TERT promoter mutation was not called by NGS and three ATRX mutations not being detected by Sanger sequencing. Importantly, in samples with low tumor cell content, NGS was able to identify mutant alleles that were not detectable by traditional methods. Information derived from NGS data identified potential targets for experimental therapy in 37/47 (79 %) glioblastomas, 9/10 (90 %) pilocytic astrocytomas, and 5/14 (36 %) medulloblastomas in the prospective target discovery cohort. In conclusion, we present the settings for high-throughput, adaptive next-generation sequencing in routine neuropathology diagnostics. Such an approach will likely become highly valuable in the near future for treatment decision making, as more therapeutic targets emerge and genetic information enters the classification of brain tumors.

Classification:

Contributing Institute(s):
  1. KKE Pädiatrische Onkologie (G340)
  2. KKE Neuropathologie (G380)
  3. Pädiatrische Neuroonkologie (B062)
  4. KKE Neuroonkologie (G370)
  5. Angewandte Bioinformatik (G200)
  6. Biostatistik (C060)
  7. Microarray Unit (W110)
  8. Neuroimmunologie und Hirntumorimmunologie (G160)
  9. DKTK Heidelberg (L101)
Research Program(s):
  1. 317 - Translational cancer research (POF3-317) (POF3-317)

Appears in the scientific report 2016
Database coverage:
Medline ; BIOSIS Previews ; Current Contents - Life Sciences ; Ebsco Academic Search ; IF >= 10 ; JCR ; NCBI Molecular Biology Database ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection
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 Record created 2017-11-17, last modified 2024-02-28



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