| Literature DB >> 29967255 |
Thomas Yssing Michaelsen1,2, Julia Richter3, Rasmus Froberg Brøndum1, Wolfram Klapper3, Hans Erik Johnsen1,4, Mads Albertsen2, Karen Dybkær1,4, Martin Bøgsted1,4.
Abstract
Gene expression profiling (GEP) by microarrays of diffuse large B-cell lymphoma (DLBCL) has enabled the categorization of DLBCL into activated B-cell-like and germinal center B-cell-like subclasses. However, as this does not fully embrace the great diversity of B-cell subtypes, we recently developed a gene expression assay for B-cell-associated gene signature (BAGS) classification. To facilitate quick and easy-to-use BAGS profiling, we developed in this study the NanoString-based BAGS2Clinic assay. Microarray data from 4 different cohorts (n = 970) were used to select genes and train the assay. The locked assay was validated in an independent cohort of 88 sample biopsies. The assay showed good correspondence with the original BAGS classifier, with an overall accuracy of 84% (95% confidence interval, 72% to 93%) and a subtype-specific accuracy ranging between 80% and 99%. BAGS classification has the potential to provide valuable insight into tumor biology as well as differences in resistance to immuno- and chemotherapy that can lead to novel treatment strategies for DLBCL patients. BAGS2Clinic can facilitate this and the implementation of BAGS classification as a routine clinical tool to improve prognosis and treatment guidance for DLBCL patients.Entities:
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Year: 2018 PMID: 29967255 PMCID: PMC6039667 DOI: 10.1182/bloodadvances.2018017988
Source DB: PubMed Journal: Blood Adv ISSN: 2473-9529