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Methylation microarray-based detection of clinical copy-number aberrations in CLL benchmarked to standard FISH analysis

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  • Dianna Hussmann
  • ,
  • Anna Starnawska
  • Louise Kristensen, University of Southern Denmark
  • ,
  • Iben Daugaard
  • Oriane Cédile, University of Southern Denmark
  • ,
  • Vivi Quoc Nguyen, University of Southern Denmark
  • ,
  • Tina E. Kjeldsen
  • Christine Søholm Hansen, iPSYCH -The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Statens Serum Institut, Mount Sinai
  • ,
  • Jonas Bybjerg-Grauholm, iPSYCH -The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Statens Serum Institut
  • ,
  • Thomas Kristensen, University of Southern Denmark
  • ,
  • Thomas Stauffer Larsen, University of Southern Denmark
  • ,
  • Michael Boe Møller, University of Southern Denmark
  • ,
  • Charlotte Guldborg Nyvold, University of Southern Denmark
  • ,
  • Lise Lotte Hansen
  • Tomasz K. Wojdacz

Copy-number aberrations (CNAs) are assessed using FISH analysis in diagnostics of chronic lymphocytic leukemia (CLL), but CNAs can also be extrapolated from Illumina BeadChips developed for genome-wide methylation microarray screening. Increasing numbers of microarray data-sets are available from diagnostic samples, making it useful to assess the potential in CNA diagnostics. We benchmarked the limitations of CNA testing from two Illumina BeadChips (EPIC and 450k) and using two common packages for analysis (conumee and ChAMP) to FISH-based assessment of 11q, 13q, and 17p deletions in 202 CLL samples. Overall, the two packages predicted CNAs with similar accuracy regardless of the microarray type, but lower than FISH-based assessment. We showed that the bioinformatics analysis needs to be adjusted to the specific CNA, as no general settings were identified. Altogether, we were able to predict CNAs using methylation microarray data, however, with limited accuracy, making FISH-based assessment of deletions the superior diagnostic choice.

Original languageEnglish
Article number110510
Publication statusPublished - Nov 2022

Bibliographical note

Publisher Copyright:
© 2022

    Research areas

  • 450k, Chronic lymphocytic leukemia, CNA assessment, Copy-number aberration, EPIC, Methylation microarray

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