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A new diagnostic algorithm for Burkitt and diffuse large B-cell lymphomas based on the expression of CSE1L and STAT3 and on MYC rearrangement predicts outcome


Soldini, D; Montagna, C; Schüffler, P; Martin, V; Georgis, A; Thiesler, T; Curioni-Fontecedro, A; Went, P; Bosshard, G; Dehler, Silvia; Mazzuchelli, L; Tinguely, M (2013). A new diagnostic algorithm for Burkitt and diffuse large B-cell lymphomas based on the expression of CSE1L and STAT3 and on MYC rearrangement predicts outcome. Annals of Oncology, 24(1):193-201.

Abstract

BackgroundAggressive mature B-cell non-Hodgkin's lymphomas (BCL) sharing features of Burkitt's lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL) (intermediate BL/DLBCL) but deviating with respect to one or more characteristics are increasingly recognized. The limited knowledge about these biologically heterogeneous lymphomas hampers their assignment to a known entity, raising incertitude about optimal treatment approaches. We therefore searched for discriminative, prognostic, and predictive factors for their better characterization.Patients and methodsWe analyzed 242 cytogenetically defined aggressive mature BCL for differential protein expression. Marker selection was based on recent gene-expression profile studies. Predictive models for diagnosis were established and validated by a different set of lymphomas. ResultsCSE1L- and inhibitor of DNA binding-3 (ID3)-overexpression was associated with the diagnosis of BL and signal transduction and transcription-3 (STAT3) with DLBCL (P < 0.001 for all markers). All three markers were associated with patient outcome in DLBCL. A new algorithm discriminating BL from DLBCL emerged, including the expression of CSE1L, STAT3, and MYC translocation. This 'new classifier' enabled the identification of patients with intermediate BL/DLBCL who benefited from intensive chemotherapy regimens. ConclusionThe proposed algorithm, which is based on markers with reliable staining properties for routine diagnostics, represents a novel valid tool in separating BL from DLBCL. Most interestingly, it allows segregating intermediate BL/DLBCL into groups with different treatment requirements.

Abstract

BackgroundAggressive mature B-cell non-Hodgkin's lymphomas (BCL) sharing features of Burkitt's lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL) (intermediate BL/DLBCL) but deviating with respect to one or more characteristics are increasingly recognized. The limited knowledge about these biologically heterogeneous lymphomas hampers their assignment to a known entity, raising incertitude about optimal treatment approaches. We therefore searched for discriminative, prognostic, and predictive factors for their better characterization.Patients and methodsWe analyzed 242 cytogenetically defined aggressive mature BCL for differential protein expression. Marker selection was based on recent gene-expression profile studies. Predictive models for diagnosis were established and validated by a different set of lymphomas. ResultsCSE1L- and inhibitor of DNA binding-3 (ID3)-overexpression was associated with the diagnosis of BL and signal transduction and transcription-3 (STAT3) with DLBCL (P < 0.001 for all markers). All three markers were associated with patient outcome in DLBCL. A new algorithm discriminating BL from DLBCL emerged, including the expression of CSE1L, STAT3, and MYC translocation. This 'new classifier' enabled the identification of patients with intermediate BL/DLBCL who benefited from intensive chemotherapy regimens. ConclusionThe proposed algorithm, which is based on markers with reliable staining properties for routine diagnostics, represents a novel valid tool in separating BL from DLBCL. Most interestingly, it allows segregating intermediate BL/DLBCL into groups with different treatment requirements.

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11 citations in Web of Science®
11 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Institute of Pathology and Molecular Pathology
04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
04 Faculty of Medicine > University Hospital Zurich > Clinic for Oncology
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2013
Deposited On:18 Dec 2012 16:16
Last Modified:13 Jan 2017 11:38
Publisher:Oxford University Press
ISSN:0923-7534
Publisher DOI:https://doi.org/10.1093/annonc/mds209
PubMed ID:22967991

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