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 (LLBC)

Abstract

The results of class prediction and the determination of prognostic markers in DLBCL have been variably reported. Apart from biological variations, this may be caused by differences in laboratory techniques, scoring definitions and inter- and intra-observer variation. In this study, an international collaboration of clinical lymphoma research groups has concentrated on validation and standardization of immunohistochemistry of the currently potentially interesting prognostic markers in DLBCL.

Sections of a tissue microarray with 36 cases of DLBCL were stained in 8 laboratories with antibodies to CD20, CD5, bcl-2, bcl-6, CD10, HLA-DR, MUM1 and Ki-67 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.

Different techniques resulted in highly variable results and poor reproducibility for almost all markers. Reproducibility of the nuclear markers was highly sensitive to technical variations, including immunological enhancement techniques (agreements 34%). With elimination of variation due to staining and uniformly agreed upon scoring criteria, significant improvement was seen, however less so for bcl-6 and Ki-67 (agreement 53-58%). Absence of internal controls that preclude scoring, significantly influenced the results for CD10 and bcl-6.

This study shows that semi-quantitative immunohistochemistry for subclassification of DLBCL is feasible, but with varying rates of concordance for different markers and only using optimized techniques and strict scoring criteria. These findings may explain the wide variation in prognostic impact reported in the literature. Harmonization of techniques and centralized consensus review appears mandatory when using immunohistochemical biomarkers for treatment stratification.