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

Research output: Contribution to journalJournal articleResearchpeer-review

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.

Original languageEnglish
JournalBlood advances
Volume2
Issue number13
Pages (from-to)1542-1546
Number of pages5
ISSN2473-9529
DOIs
Publication statusPublished - 2018

Fingerprint

Lymphoma, Large B-Cell, Diffuse
B-Lymphocytes
Technology
Genes
Germinal Center
Gene Expression Profiling
Immunotherapy
Confidence Intervals
Biopsy
Gene Expression
Drug Therapy
Therapeutics

Bibliographical note

This article has been found as a 'Free Version' from the Publisher on November 12th 2018. When the access to the article closes, please notify vbn@aub.aau.dk.

Cite this

@article{4b98a89c0cd84daba4d6249aae0b54f9,
title = "A B-cell-associated gene signature classification of diffuse large B-cell lymphoma by NanoString technology",
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.",
author = "Michaelsen, {Thomas Yssing} and Julia Richter and Br{\o}ndum, {Rasmus Froberg} and Wolfram Klapper and Johnsen, {Hans Erik} and Mads Albertsen and Karen Dybk{\ae}r and Martin B{\o}gsted",
note = "This article has been found as a 'Free Version' from the Publisher on November 12th 2018. When the access to the article closes, please notify vbn@aub.aau.dk.",
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language = "English",
volume = "2",
pages = "1542--1546",
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A B-cell-associated gene signature classification of diffuse large B-cell lymphoma by NanoString technology. / Michaelsen, Thomas Yssing; Richter, Julia; Brøndum, Rasmus Froberg; Klapper, Wolfram; Johnsen, Hans Erik; Albertsen, Mads; Dybkær, Karen; Bøgsted, Martin.

In: Blood advances, Vol. 2, No. 13, 2018, p. 1542-1546.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - A B-cell-associated gene signature classification of diffuse large B-cell lymphoma by NanoString technology

AU - Michaelsen, Thomas Yssing

AU - Richter, Julia

AU - Brøndum, Rasmus Froberg

AU - Klapper, Wolfram

AU - Johnsen, Hans Erik

AU - Albertsen, Mads

AU - Dybkær, Karen

AU - Bøgsted, Martin

N1 - This article has been found as a 'Free Version' from the Publisher on November 12th 2018. When the access to the article closes, please notify vbn@aub.aau.dk.

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

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DO - 10.1182/bloodadvances.2018017988

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VL - 2

SP - 1542

EP - 1546

JO - Blood advances

JF - Blood advances

SN - 2473-9529

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ER -