Gene Expression–Based Model Using Formalin-Fixed Paraffin-Embedded Biopsies Predicts Overall Survival in Advanced-Stage Classical Hodgkin Lymphoma

Author:

Scott David W.1,Chan Fong Chun1,Hong Fangxin1,Rogic Sanja1,Tan King L.1,Meissner Barbara1,Ben-Neriah Susana1,Boyle Merrill1,Kridel Robert1,Telenius Adele1,Woolcock Bruce W.1,Farinha Pedro1,Fisher Richard I.1,Rimsza Lisa M.1,Bartlett Nancy L.1,Cheson Bruce D.1,Shepherd Lois E.1,Advani Ranjana H.1,Connors Joseph M.1,Kahl Brad S.1,Gordon Leo I.1,Horning Sandra J.1,Steidl Christian1,Gascoyne Randy D.1

Affiliation:

1. David W. Scott, Fong Chun Chan, King L. Tan, Barbara Meissner, Susana Ben-Neriah, Merrill Boyle, Robert Kridel, Adele Telenius, Bruce W. Woolcock, Joseph M. Connors, Christian Steidl, and Randy D. Gascoyne, Centre for Lymphoid Cancer, BC Cancer Agency; Sanja Rogic, Centre for High-Throughput Biology, University of British Columbia, Vancouver, British Columbia; Lois E. Shepherd, National Cancer Institute of Canada Clinical Trials Group, Queen's University, Kingston, Ontario, Canada; Fangxin Hong, Dana...

Abstract

PurposeOur 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).MethodsExpression 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.ResultsA 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.ConclusionA 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.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

Cancer Research,Oncology

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