Paraffin-Based 6-Gene Model Predicts Outcome of Diffuse Large B-Cell Lymphoma Patients Treated with R-CHOP.

Background: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease characterized by highly variable clinical outcomes. It is therefore of paramount importance to be able to predict the outcome of patients at the time of diagnosis. Previously, we constructed a 6 gene model for outcome prediction of DLBCL patients treated with anthracycline-based chemotherapies (Lossos et al NEJM 2004, 350:1829). However, the standard therapy has evolved to rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone (R-CHOP). Subset analyses of clinical trials have suggested that some of the prognostic factors lose their predictive power in R-CHOP treated patients. Consequently, the molecular gold standard for survival prediction in R-CHOP treated patients has not been established. Herein, we evaluated the predictive power of the 6-gene model in R-CHOP treated DLBCL patients. We have employed new methodology that allows quantitation of gene expression from paraffin embedded, fixed tissues.

Methods: RNA was extracted from 100 paraffin-embedded specimens (Chen et al Diagn Mol Pathol 2007, 16:61), from patients with DLBCL treated with R-CHOP in British Columbia (73) and at the University of Miami (27). Expression of the 6 genes comprising the model was measured in these samples and the mortality-prediction score was calculated for each patient, as reported previously.

Results: The study group consisted of 100 patients with a median age of 58 y (range, 16–92y) that were followed for a median of 2.1 years (range, 0.1–5.6). Distribution according to IPI: 0–1 factor, 42; 2 factors, 24; 3 factors, 19; and ≥4 factors, 14. RNA of sufficient quality and quantity was successfully extracted from all the 100 paraffin embedded specimens tested, some of which had been stored for up to 6 years. The mortality-prediction score derived from the model divided patients into low-risk (50%) and high-risk (50%) subgroups with significantly different overall survival (OS) (p=0.02) and progression free survival (PFS) (p=0.02). Notably the OS was similar between the groups during the 1^st year, due to the inclusion of patients with advanced age and poor performance status, but it was markedly different beyond the first 2 years, with the 3 year OS of 80% and 50% in the low risk and high risk groups, respectively. The predictive power of the 6-gene model was independent of the IPI prognostic factors for prediction of OS (P=0.06) and PFS (p=0.01) in these patients.

Conclusions: The prognostic value of the 6-gene model remains significant in the era of R-CHOP treatment. Further, using the new RNA extraction methodology, we demonstrate that the model can be applied to routinely available formalin-fixed paraffin blocks from initial diagnostic biopsies, even after long term storage. Following validation in an independent cohort of patients, the six gene model may be practically applied in routine clinical practice.