A gene-expression profiling score for outcome prediction disease in patients with follicular lymphoma: a retrospective analysis on three international cohorts

Abstract

Background

Patients with follicular lymphoma (FL) have heterogeneous outcomes. Predictor models able to distinguish, at diagnosis, patients at high versus low risk of progression are still needed.

Methods

The primary objective of this study was to use gene-expression profiling data to build a signature predictive of outcome in patients treated in the rituximab era. In a retrospectively assembled training cohort of 134 pretreatment FL patients from the prospective randomized PRIMA trial, we developed an expression-based predictor of progression-free survival (PFS) that was further evaluated in FFPE samples obtained from three independent international cohorts, using NanoString technology. The validation cohorts comprised a distinct set of patients from the PRIMA trial (n=178), a cohort from the University of Iowa/Mayo Clinic Lymphoma SPORE (n=201) and the Hospital Clinic University of Barcelona (n=109). All tissue samples consisted of pretreatment diagnostic biopsies and were confirmed as FL grade 1-3a. The patients were all treated with regimens containing rituximab and chemotherapy, possibly followed by either rituximab maintenance or ibritumomab-tiuxetan consolidation.

Findings

The expression levels of 395 genes were associated with a risk of progression. Twenty-three genes reflecting both B-cell biology and tumor microenvironment were retained to build a predictive model, which identified a population at an increased risk of progression (p<0.0001). In a multivariate Cox model for PFS adjusted on rituximab maintenance treatment and FLIPI-1, this predictor was found to independently predict progression (adjusted hazard ratio (HR) of the high-risk compared to the low-risk group: 3.68; 95%CI: 2.19-6.17). The digital gene expression data met quality criteria for 460/488 (94%) FFPE samples of the validation cohorts. The predictor performances were confirmed in each of the individual validation cohorts (adjusted HR [95%CI] comparing high risk to low risk groups were respectively 2.57 [1.65-4.01], 2.12 [1.32-3.39] and 2.11 [1.01-4.41]). In the combined validation cohort, the median PFS values were 3.1 (95%CI: 2.4-2.8) and 10.8 (95%CI: 10.1-NR) years in the high- and low-risk groups, respectively. The risk of lymphoma progression at 2 years was twice as high in the high-risk group (38% (95%CI: 29-46) versus 19% (95%CI: 15-24)). In a multivariate analysis, the score predicted PFS independently of anti-CD20 maintenance treatment and of the FLIPI score (hazard ratio for the combined cohort, 2.30; 95%CI, 1.72-3.07).

Interpretation

We developed a robust 23-gene expression-based predictor of PFS, applicable to routinely available FFPE biopsies from FL patients at diagnosis. This score may allow individualizing therapy for patients with FL according to the patient risk category.

Funding

Roche Company, SIRIC Lyric, LYSARC, NIH and the Henry J. Predolin Foundation, Spanish Plan Nacional de Investigacion SAF2015-64885-R.