Gene expression-based model using formalin-fixed paraffin-embedded biopsies predicts overall survival in advanced-stage classical Hodgkin lymphoma

Abstract

Purpose: Our aim was to reliably identify patients with advanced-stage classical Hodgkin lymphoma (cHL) at increased risk of death by developing a robust predictor of overall survival (OS) using gene expression measured in routinely available formalin-fixed paraffin-embedded tissue (FFPET).

Methods: Expression levels of 259 genes, including those previously reported to be associated with outcome in cHL, were determined by digital expression profiling of pretreatment FFPET biopsies from 290 patients enrolled onto the E2496 Intergroup trial comparing doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) and Stanford V regimens in locally extensive and advanced-stage cHL. A model for OS separating patients into low- and high-risk groups was produced using penalized Cox regression. The model was tested in an independent cohort of 78 patients enriched for treatment failure but otherwise similar to patients in a population-based registry of patients treated with ABVD. Weighted analysis methods generated unbiased estimates of predictor performance in the population-based registry.

Results: A 23-gene outcome predictor was generated. The model identified a population at increased risk of death in the validation cohort. There was a 29% absolute difference in 5-year OS between the high- and low-risk groups (63% v 92%, respectively; log-rank P < .001; hazard ratio, 6.7; 95% CI, 2.6 to 17.4). The predictor was superior to the International Prognostic Score and CD68 immunohistochemistry in multivariate analyses.

Conclusion: A gene expression-based predictor, developed in and applicable to routinely available FFPET biopsies, identifies patients with advanced-stage cHL at increased risk of death when treated with standard-intensity up-front regimens.

Fig 1.

Gene expression associated with overall survival (OS) in locally extensive and advanced-stage classical Hodgkin lymphoma. z scores are shown for the 52 genes whose expression levels are significantly associated with OS in the training cohort by univariate Cox regression analysis. The gray dotted lines represent a z score of ± 1.96. False discovery rates were calculated using the Benjamini-Hochberg method, controlling for 229 comparisons in the training cohort and 52 comparisons in the validation cohort, respectively. (*) Indicates false discovery rate of less than 10%.

Fig 2.

Kaplan-Meier estimates of overall survival among patients with locally extensive and advanced-stage classical Hodgkin lymphoma. (A) The training cohort. (B) Weighted analysis of the independent validation cohort giving an unbiased estimate of the predictor's performance in the population-based registry cohort from which the independent validation cohort was drawn. The numbers at risk indicate the number of patients in the validation cohort contributing to the weighted analysis estimates.

Fig 3.

The gene expression–based predictor for locally extensive and advanced-stage classical Hodgkin lymphoma tested in the validation cohort. The predictor is a linear equation, adding the log₂ transformed normalized gene expression multiplied by the gene coefficient. (A) The relative gene expression levels of the 23 genes in the predictive model are presented in the form of a heat map. Each column represents a single patient from the validation cohort, arranged according to the predictor score, with lowest score on the left. Each row represents a gene from the model, ordered by hierarchical clustering. The coefficients for each gene, determined in the training cohort, are shown on the right. The vertical dotted blue line separates patients into low- and high-risk groups according to the threshold predictor score. (B) The score from the predictor for patients in the independent validation cohort. The patients are arranged as in panel A. The dotted blue line is placed at the threshold predictor score (0.6235) determined in the training cohort. (C) The clinical and pathology characteristics of the patients in the validation cohort. The patients are ordered as in panel A. EBER, Epstein-Barr virus–encoded RNA; HRS, Hodgkin Reed-Sternberg; IPS, International Prognostic Score; NOS, not otherwise specified.