ABSTRACT
Despite improvement in the treatment of advanced classical Hodgkin lymphoma, approximately 30% of patients relapse or die as result of the disease. Current predictive systems, determined by clinical and analytical parameters, fail to identify these high-risk patients accurately. We took a multistep approach to design a quantitative reverse-transcription polymerase chain reaction assay to be applied to routine formalin-fixed paraffin-embedded samples, integrating genes expressed by the tumor cells and their microenvironment. The significance of 30 genes chosen on the basis of previously published data was evaluated in 282 samples (divided into estimation and validation sets) to build a molecular risk score to predict failure. Adequate reverse-transcription polymerase chain reaction profiles were obtained from 262 of 282 cases (92.9%). Best predictor genes were integrated into an 11-gene model, including 4 functional pathways (cell cycle, apoptosis, macrophage activation, and interferon regulatory factor 4) able to identify low- and high-risk patients with different rates of 5-year failure-free survival: 74% versus 44.1% in the estimation set (P < .001) and 67.5% versus 45.0% in the validation set (P = .022). This model can be combined with stage IV into a final predictive model able to identify a group of patients with very bad outcome (5-year failure-free survival probability, 25.2%).
Subject(s)
Biomarkers, Tumor/genetics , Hodgkin Disease/diagnosis , Hodgkin Disease/genetics , Neoplasm Recurrence, Local/diagnosis , Neoplasm Recurrence, Local/genetics , Signal Transduction/drug effects , Algorithms , Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Biomarkers, Tumor/metabolism , Female , Gene Expression Profiling , Hodgkin Disease/drug therapy , Humans , Male , Middle Aged , Models, Statistical , Neoplasm Recurrence, Local/drug therapy , Neoplasm, Residual/diagnosis , Neoplasm, Residual/drug therapy , Neoplasm, Residual/genetics , Oligonucleotide Array Sequence Analysis , Paraffin Embedding , RNA, Messenger/genetics , Remission Induction , Reverse Transcriptase Polymerase Chain Reaction , Risk Assessment , Survival Rate , Treatment OutcomeABSTRACT
PURPOSE: Current therapies fail to cure a significant proportion of patients with Hodgkin's lymphoma (HL). Predictive systems for stratification of the disease and selection of treatment based on sets of clinical variables, such as the international prognostic score (IPS), are of relatively small practical value. The predictive use of biologic parameters has so far provided limited and inconsistent results. Here we explore the influence of a set of molecular markers on the outcome of HL. PATIENTS AND METHODS: Forty molecular markers involved in B-cell differentiation and activation, signal transduction, cell cycle, and apoptosis control were analyzed in 259 classic HL patient cases by using tissue microarrays. Univariate analysis was performed to evaluate the influence of markers on favorable outcome (complete remission of > 12 months). Significant variables were included in a multivariate logistic regression analysis, and the probability of favorable outcome was estimated. RESULTS: Univariate analysis revealed four molecular markers that predicted outcome, and the multivariate analysis showed p53, Bcl-X(L), and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate-biotin nick-end labeling (TUNEL) to have independent significance. The combination of these factors determined two groups of patients (group I, zero to one factor; group II, two to three factors) with a probability of a favorable outcome of.948 and.687, respectively. A multivariate Cox's model shows that these biologic risk groups have special predictive power in low-IPS patients. CONCLUSION: The data from this exploratory study suggest that the accumulation of molecular events seems to influence the outcome of HL, particularly in the low-IPS group.
