Immunohistochemical Prognostic Markers in Diffuse Large B-Cell Lymphoma: Validation of Tissue Microarray As a Prerequisite for Broad Clinical Applications—A Study From the Lunenburg Lymphoma Biomarker Consortium

Abstract

Purpose The results of immunohistochemical class prediction and prognostic stratification of diffuse large B-cell lymphoma (DLBCL) have been remarkably various thus far. Apart from biologic variations, this may be caused by differences in laboratory techniques, scoring definitions, and inter- and intraobserver variations. In this study, an international collaboration of clinical lymphoma research groups from Europe, United States, and Canada concentrated on validation and standardization of immunohistochemistry of the currently potentially interesting prognostic markers in DLBCL. Patients and Methods Sections of a tissue microarray from 36 patients with DLBCL were stained in eight laboratories with antibodies to CD20, CD5, bcl-2, bcl-6, CD10, HLA-DR, MUM1, and MIB-1 according to local methods. The study was performed in two rounds firstly focused on the evaluation of laboratory staining variation and secondly on the scoring variation. Results Different laboratory staining techniques resulted in unexpectedly highly variable results and very poor reproducibility in scoring for almost all markers. No single laboratory stood out as uniformly poor or excellent. With elimination of variation due to staining, high agreement was found for CD20, HLA-DR, and CD10. Poor agreement was found for bcl-6 and Ki-67. Optimization of techniques and uniformly agreed on scoring criteria improved reproducibility. Conclusion This study shows that semiquantitative immunohistochemistry for subclassification of DLBCL is feasible and reproducible, but exhibits varying rates of concordance for different markers. These findings may explain the wide variation of biomarker prognostic impact reported in the literature. Harmonization of techniques and centralized consensus review appears mandatory when using immunohistochemical biomarkers for treatment stratification.