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

Dianna Hussmann; Anna Starnawska; Louise Kristensen; Iben Daugaard; Oriane Cédile; Vivi Quoc Nguyen; Tina E. Kjeldsen; Christine Søholm Hansen; Jonas Bybjerg-Grauholm; Thomas Kristensen; Thomas Stauffer Larsen; Michael Boe Møller; Charlotte Guldborg Nyvold; Lise Lotte Hansen; Tomasz K. Wojdacz

doi:10.1016/j.ygeno.2022.110510

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

Dianna Hussmann, Anna Starnawska, Louise Kristensen, Iben Daugaard, Oriane Cédile, Vivi Quoc Nguyen, Tina E. Kjeldsen, Christine Søholm Hansen, Jonas Bybjerg-Grauholm, Thomas Kristensen, Thomas Stauffer Larsen, Michael Boe Møller, Charlotte Guldborg Nyvold, Lise Lotte Hansen, Tomasz K. Wojdacz^*

^*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

1 Citationer (Scopus)

Abstract

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.

Originalsprog	Engelsk
Artikelnummer	110510
Tidsskrift	Genomics
Vol/bind	114
Nummer	6
ISSN	0888-7543
DOI	https://doi.org/10.1016/j.ygeno.2022.110510
Status	Udgivet - nov. 2022

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10.1016/j.ygeno.2022.110510Licens: CC BY-NC-ND

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Hussmann, D., Starnawska, A., Kristensen, L., Daugaard, I., Cédile, O., Nguyen, V. Q., Kjeldsen, T. E., Hansen, C. S., Bybjerg-Grauholm, J., Kristensen, T., Larsen, T. S., Møller, M. B., Nyvold, C. G., Hansen, L. L., & Wojdacz, T. K. (2022). Methylation microarray-based detection of clinical copy-number aberrations in CLL benchmarked to standard FISH analysis. Genomics, 114(6), Artikel 110510. https://doi.org/10.1016/j.ygeno.2022.110510

@article{0bf6aed3c9e243408e809acb3a6dd8da,

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

abstract = "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.",

keywords = "450k, Chronic lymphocytic leukemia, CNA assessment, Copy-number aberration, EPIC, Methylation microarray",

author = "Dianna Hussmann and Anna Starnawska and Louise Kristensen and Iben Daugaard and Oriane C{\'e}dile and Nguyen, {Vivi Quoc} and Kjeldsen, {Tina E.} and Hansen, {Christine S{\o}holm} and Jonas Bybjerg-Grauholm and Thomas Kristensen and Larsen, {Thomas Stauffer} and M{\o}ller, {Michael Boe} and Nyvold, {Charlotte Guldborg} and Hansen, {Lise Lotte} and Wojdacz, {Tomasz K.}",

note = "Publisher Copyright: {\textcopyright} 2022",

year = "2022",

month = nov,

doi = "10.1016/j.ygeno.2022.110510",

language = "English",

volume = "114",

journal = "Genomics",

issn = "0888-7543",

publisher = "Academic Press Inc.",

number = "6",

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Hussmann, D, Starnawska, A, Kristensen, L, Daugaard, I, Cédile, O, Nguyen, VQ, Kjeldsen, TE, Hansen, CS, Bybjerg-Grauholm, J, Kristensen, T, Larsen, TS, Møller, MB, Nyvold, CG, Hansen, LL & Wojdacz, TK 2022, 'Methylation microarray-based detection of clinical copy-number aberrations in CLL benchmarked to standard FISH analysis', Genomics, bind 114, nr. 6, 110510. https://doi.org/10.1016/j.ygeno.2022.110510

TY - JOUR

T1 - Methylation microarray-based detection of clinical copy-number aberrations in CLL benchmarked to standard FISH analysis

AU - Hussmann, Dianna

AU - Starnawska, Anna

AU - Kristensen, Louise

AU - Daugaard, Iben

AU - Cédile, Oriane

AU - Nguyen, Vivi Quoc

AU - Kjeldsen, Tina E.

AU - Hansen, Christine Søholm

AU - Bybjerg-Grauholm, Jonas

AU - Kristensen, Thomas

AU - Larsen, Thomas Stauffer

AU - Møller, Michael Boe

AU - Nyvold, Charlotte Guldborg

AU - Hansen, Lise Lotte

AU - Wojdacz, Tomasz K.

PY - 2022/11

Y1 - 2022/11

N2 - 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.

AB - 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.

KW - 450k

KW - Chronic lymphocytic leukemia

KW - CNA assessment

KW - Copy-number aberration

KW - EPIC

KW - Methylation microarray

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U2 - 10.1016/j.ygeno.2022.110510

DO - 10.1016/j.ygeno.2022.110510

M3 - Journal article

C2 - 36272495

AN - SCOPUS:85140607195

SN - 0888-7543

VL - 114

JO - Genomics

JF - Genomics

IS - 6

M1 - 110510

ER -

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

Abstract

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