一致性
弥漫性大B细胞淋巴瘤
基因表达谱
计算生物学
基因表达
生物
基因
分类器(UML)
淋巴瘤
起源细胞
生发中心
生物信息学
遗传学
B细胞
计算机科学
抗体
人工智能
免疫学
作者
Sophia Ahmed,Paul Glover,Jan Taylor,Chulin Sha,Matthew A. Care,Reuben Tooze,Andrew Davies,David R. Westhead,Peter Johnson,Catherine Burton,Sharon Barrans
摘要
Summary 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.
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