ABSTRACT
Gene expression profiling (GEP) has identified genes whose expression levels predict patient survival in diffuse large-B-cell lymphoma (DLBCL). Such discovery techniques generally require frozen samples unavailable for most patients. We developed a quantitative nuclease protection assay to measure expression levels of prognostic DLBCL genes using formalin-fixed, paraffin-embedded (FFPE) tissue. FFPE tissue was sectioned, permeabilized, denatured in the presence of specific probes, and hybridized to mRNA in situ. Nuclease subsequently destroyed non-hybridized probe. Alkaline hydrolysis freed mRNA-bound probes from tissue, which were transferred to ArrayPlates for probe capture and chemiluminescent quantification. We validated assay performance using frozen, fresh, and FFPE DLBCL samples, then used 39 archived DLBCL, previously microarray analyzed, to correlate GEP and ArrayPlate results. We compared old (>18 years) with new (<2 months) paraffin blocks made from previously frozen tissue from the original biopsy. ArrayPlate gene expression results were confirmed with immunohistochemistry for BCL2, BCL6, and HLA-DR, showing agreement between mRNA species and the proteins they encode. Assay performance was linear to approximately 1 mg sample/well. RNase and DNase treatments demonstrated assay specificity for RNA detection, both fixed and soluble RNA detection. Comparisons were excellent for lysate vs snap-frozen vs FFPE (R(2)>0.98 for all comparisons). Coefficients of variation for quadruplicates on FFPE were generally <20%. Correlation between new and old paraffin blocks from the same biopsy was good (R(2)=0.71). Comparison of ArrayPlate to Affymetrix and cDNA microarrays showed reasonable correlations. Insufficient power from small sample size prevented successfully correlating results with patient survival, although hazard ratios trended the expected directions. We developed an assay to quantify expression levels of survival prediction genes in DLBCL using FFPE, fresh, or frozen tissue. While this technique cannot replace GEP for discovery, it indicates that expression differences identified by GEP can be replicated on a platform applicable to archived FFPE samples.
Subject(s)
Gene Expression Profiling/methods , Gene Expression Regulation, Neoplastic , Lymphoma, Large B-Cell, Diffuse/genetics , Nuclease Protection Assays/methods , Oligonucleotide Array Sequence Analysis , Cell Line, Tumor , Humans , Lymphoma, Large B-Cell, Diffuse/diagnosis , Lymphoma, Large B-Cell, Diffuse/metabolism , Paraffin Embedding , Prognosis , Proportional Hazards Models , RNA, Messenger/analysis , Tissue BanksABSTRACT
CONTEXT: Diffuse large B-cell lymphoma (DLBCL) can be assigned to prognostic subgroups, including germinal center B-cell (GCB) and activated B-cell subgroups, by using gene expression profiling and, reportedly, immunohistochemistry for CD10, Bcl-6, and multiple myeloma-1/interferon regulatory factor-4 (MUM1/IRF4). OBJECTIVE: To compare 2 commercial MUM1/IRF4 antibody formulations for accuracy in subtyping DLBCL against gene expression profiling, compare subtyping to patient survival, and evaluate the usefulness of GCB and non-GCB subtyping in relapsed and transformed DLBCL. DESIGN: Evaluation of 2 commercial MUM1/IRF4 antibodies, ICSTAT/M17 and Mum-1p, by using 40 cases of de novo, relapsed, and transformed DLBCL; and comparison of the results obtained with gene expression profiling and survival. RESULTS: Immunohistochemistry predicted the gene expression profiling subtype 71.8% and 69.2% of the time overall with use of the Mum-1p and ICSTAT/M17 antibodies, respectively, and 100% and 91.7% of the time when MUM1/IRF4 expression determined subtype. Gene expression profiling and immunohistochemistry revealed nearly identical 5-year overall survival rates for the GCB vs non-GCB subtypes (68.0% for GCB vs 24.7% for non-GCB with use of gene expression profiling [P = .03] and 70.2% vs 18.4%, respectively, with use of immunohistochemistry [P < .001]). When de novo, transformed, and relapsed cases were analyzed separately, 5-year overall survival rates were also significantly different. CONCLUSIONS: Immunohistochemistry can be used to subclassify DLBCL, including a very small series of transformed and relapsed cases, into GCB and non-GCB subtypes and predict survival rates similar to those predicted by use of gene expression profiling. The 2 MUM1/IRF4 antibodies performed similarly.
