Comparative analysis of gene expression platforms for cell-of-origin classification of diffuse large B-cell lymphoma shows high concordance

被引:7
|
作者
Ahmed, Sophia [1 ]
Glover, Paul [2 ]
Taylor, Jan [2 ]
Sha, Chulin [1 ]
Care, Matthew A. [3 ]
Tooze, Reuben [2 ,3 ]
Davies, Andrew [4 ]
Westhead, David R. [1 ]
Johnson, Peter W. M. [4 ]
Burton, Catherine [2 ]
Barrans, Sharon L. [2 ]
机构
[1] Univ Leeds, Fac Biol Sci, Leeds, W Yorkshire, England
[2] St James Univ Hosp, Haematol Malignancy Diagnost Serv, Leeds LS9 7TF, W Yorkshire, England
[3] Univ Leeds, Fac Med, Leeds, W Yorkshire, England
[4] Univ Southampton, Canc Res UK Ctr, Southampton Clinical Trials Unit, Southampton, Hants, England
关键词
diffuse large B cell lymphoma; genetic subtyping; gene expression; cell of origin; lymphomas;
D O I
10.1111/bjh.17246
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Cell-of-origin subclassification of diffuse large B cell lymphoma (DLBCL) into activated B cell-like (ABC), germinal centre B cell-like (GCB) and unclassified (UNC) or type III by gene expression profiling is recommended in the latest update of the World Health Organization's classification of lymphoid neoplasms. There is, however, no accepted gold standard method or dataset for this classification. Here, we compare classification results using gene expression data for 68 formalin-fixed paraffin-embedded DLBCL samples measured on four different gene expression platforms (Illumina wG-DASL(TM) arrays, Affymetrix PrimeView arrays, Illumina TrueSeq RNA sequencing and the HTG EdgeSeq DLBCL Cell of Origin Assay EU using an established platform agnostic classification algorithm (DAC) and the classifier native to the HTG platform, which is CE marked for in vitro diagnostic use (CE-IVD). Classification methods and platforms show a high level of concordance, with agreement in at least 80% of cases and rising to much higher levels for classifications of high confidence. Our results demonstrate that cell-of-origin classification by gene expression profiling on different platforms is robust, and that the use of the confidence value alongside the classification result is important in clinical applications.
引用
收藏
页码:599 / 604
页数:6
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