American Society of Hematology

Predicting Clinical Outcome in Patients With Hodgkin Lymphoma

Peter Johnson, MD
Cancer Research UK Centre, University of Southampton, UK

Published on: March 01, 2013

Dr. Johnson indicated no relevant conflicts of interest.

Scott DW, Chan FC, Hong F, et al. Gene expression-based model using formalin-fixed paraffin-embedded biopsies predicts overall survival in advanced-stage classical Hodgkin lymphoma. J Clin Oncol. 2012. Epub ahead of print.

Until recently, the systems for predicting outcome in patients with Hodgkin lymphoma have been based upon relatively straightforward clinical criteria such as age, gender, anatomical stage, and routine measurements, including the sedimentation rate, blood count, and serum albumin concentration. These parameters reflect indirectly on the biologic heterogeneity of the disease, but only at one remove. Such baseline prognostic indices, however, have proven inferior to predictors based on functional imaging with FDG-PET performed as a measurement of response during chemotherapy. Despite this shift toward using in-treatment imaging as the prognostic benchmark, the recent description of the clinical implications of macrophage infiltration has revived interest in pathobiology both as an indicator of outcome and as a potential target for therapy. But enumeration of macrophages is difficult to reproduce using immunohistochemistry, especially on tissue microarrays that may sample only a small region of each biopsy. Now, a collaboration between the Department of Pathology and Experimental Therapeutics of the British Columbia Cancer Agency and four North American cooperative groups has tested a method of multigene expression analysis to derive a prognostic score from routine diagnostic biopsy material. This approach holds the prospect of a new means of predicting outcome based upon molecular phenotype.

In this study, requiring as little as 200 ng of RNA extracted in most cases from a single 10 mm section of formalin-fixed, paraffin-embedded tissue, the authors used a new technique called NanoString technology to examine the pattern of expression of 259 genes. Cases for a training set were drawn from the recently reported intergroup E2496 trial that showed equivalent outcomes in patients with advanced Hodgkin lymphoma treated with either ABVD or the Stanford V regimen. From a total of 794 available biopsies, 290 were studied, and based on overall survival of the patients from whom the samples were derived, a 52 gene prognostic set was developed. Next, this prognostic set was tested on a validation cohort consisting of 78 patients treated with ABVD. This validation cohort was enriched for treatment failure but was otherwise similar to patients treated with ABVD in a population-based registry. From the original 52 gene set, analysis of expression of 23 genes was found to generate a robust prognostic index. Of those 23 genes, 20 were overexpressed and three were underexpressed in the group at highest risk of death. The genes overexpressed reflected the presence of increased macrophage numbers, such as CD68, IL15RA, and STAT1; genes indicative of a Th1 response such as IFN-γ; the targets of IFN-γ such as CXCL11, IRF1, and TNFSF10; genes of HLA class I; and genes expressed by cytotoxic T cells or NK cells. The high-risk group was found to have an excess of patients with a high international prognostic score, positive Epstein-Barr virus-encoded RNA (EBER) expression, and a histology other than nodular sclerosis, although the molecular signature remained independently predictive in multivariate analysis.

Gene-expression profiling, which is already making a significant impact on our understanding of the molecular basis of non-Hodgkin lymphoma, has until now given relatively little information about the heterogeneity of Hodgkin lymphoma. It is clear to clinicians that such heterogeneity exists, and, given the complex infiltrate seen on histology, it is not surprising that the microenvironment in general, and the presence of macrophages and NK cells in particular, would play a central role in the natural history of the disease. This study represents an important contribution to our understanding of the key interactions that drive Hodgkin lymphoma and suggests that therapies that specifically target the inflammatory component of the disease may be capable of improving outcome for those destined to fare poorly with conventional chemotherapy. The NanoString technology used in this study holds the promise of a broader application for gene-expression profiling because RNA sufficient for analysis can be obtained routinely from a single formalin-fixed, paraffin-embedded tissue sample, whereas the need to acquire relatively larger amounts of RNA from formalin-fixed, paraffin-embedded tissue has limited the applicability of standard microarray analysis as a clinical tool. If the results of this study can be replicated by other groups, it may be possible to apply this type of analysis to more routine biopsy specimens in the future, bringing the prospect of real-time molecular phenotyping closer to the bedside.

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