A B-cell-associated gene signature classification of diffuse large B-cell lymphoma by NanoString technology

Thomas Yssing Michaelsen, Julia Richter, Rasmus Froberg Brøndum, Wolfram Klapper, Hans Erik Johnsen, Mads Albertsen, Karen Dybkær, Martin Bøgsted

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

10 Citationer (Scopus)

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.

OriginalsprogEngelsk
TidsskriftBlood advances
Vol/bind2
Udgave nummer13
Sider (fra-til)1542-1546
Antal sider5
ISSN2473-9529
DOI
StatusUdgivet - 2018

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