Abstract 4996

Introduction

The indolent and incurable nature of follicular lymphoma (FL) is characterized by defects in cellular apoptosis. The ubiquitous overexpression of bcl-2 in FL favors cell survival, but differences in the expression levels and interactions with other bcl-2 family members may account for the clinical heterogeneity observed in FL. Regulation of apoptosis is the result of the interaction of multiple anti-apoptotic and pro-apoptotic members. We evaluated the use of high through-put quantitative immunofluorescence staining with automated quantitative analysis (AQUA) technology to evaluate multiple pro- and anti-apoptotic bcl-2 proteins on a FL tissue microarray. Quantitative levels of apoptotic proteins were correlated with IPI and FLIPI scores and survival.

Patients and methods

Seventy-six FL patients evaluated at our institution between 1986 and 1996 with diagnostic biopsies available in paraffin tissue were identified, and diagnostic biopsies incorporated into a tissue microarray. Immunofluorescent antibodies to the anti-apoptotic proteins bcl-2, mcl-1, bcl-XL and the pro-apoptotic proteins BAX, BAD, BAK were applied to the tissue microarray and expression quantified by AQUA technology. Each section was co-stained with CD20, and a CD20 mask or gate applied to limit examination of protein expression to tumor cells. Intensity of fluorescence staining in each sample was expressed as an AQUA score. The AQUA score was analyzed for each protein as a continuous variable.

Results

The mean age was 56.7 years (range 21.7-84.8), with 55% of patients under the age of 60. Sixty-two percent of patients were men and 66% of patients had stage ≥3 disease at diagnosis. Median duration of follow-up was 9.4 years (range 0.7-33.6 years). Complete data for determining IPI and FLIPI status were available for 63 patients. All bcl-2 family protein biomarkers were expressed as logarithms of the AQUA score. There was a wide range of expression of both pro- and anti-apoptotic proteins between cases, with up to 1000 fold differences in expression levels for all proteins, including bcl-2. In general, there was no association between levels of pro- and anti-apoptotic protein expression and IPI or FLIPI score or survival. In univariate analysis, the hazard ratio for individual biomarkers shows the estimated relative risk of dying for patients, estimating risk based on a one unit increase in the log expression for a biomarker. No individual biomarker was predictive of survival. Age and IPI and FLIPI risk groups were predictive of survival (Table 1). Multivariate analysis showed that biomarkers were not predictive for survival after adjusting for other variables.

Conclusions

AQUA quantification of pro- and anti-apoptotic proteins identified marked heterogeneity in protein expression, including bcl-2, in these follicular lymphoma samples. However, there was no clear relationship between the bcl-2 family of biomarkers and FLIPI/IPI status or survival. Use of AQUA technology on a microarray of paraffin-embedded tissue was feasible, but was not useful in predicting clinical outcome in these cases.

Table 1.

Univariate analysis for biomarkers, age, stage, IPI, and FLIPI using Cox hazard regression model.

VariableHazard ratio95% CIP-value
Log BAK 1.12 0.61-2.06 0.71 
Log BAX 1.23 0.84-1.80 0.28 
Log BAD 1.07 0.71-1.63 0.74 
Log bcl-XL 1.07 0.65-1.77 0.78 
Log mcl-1 0.84 0.46-1.53 0.57 
Log bcl-2 1.04 0.79-1.38 0.76 
Age ≥60 (vs <60) 2.32 1.32-4.06 0.003 
Stage ≥3 (vs stage <3) 0.99 0.56-1.76 0.97 
IPI intermediate/high risk (vs low risk) 2.04 1.14-3.66 0.02 
FLIPI intermediate risk (vs low risk) 0.77 0.39-1.55 0.47 
FLIPI high risk (vs low risk) 2.35 1.08-5.10 0.03 
VariableHazard ratio95% CIP-value
Log BAK 1.12 0.61-2.06 0.71 
Log BAX 1.23 0.84-1.80 0.28 
Log BAD 1.07 0.71-1.63 0.74 
Log bcl-XL 1.07 0.65-1.77 0.78 
Log mcl-1 0.84 0.46-1.53 0.57 
Log bcl-2 1.04 0.79-1.38 0.76 
Age ≥60 (vs <60) 2.32 1.32-4.06 0.003 
Stage ≥3 (vs stage <3) 0.99 0.56-1.76 0.97 
IPI intermediate/high risk (vs low risk) 2.04 1.14-3.66 0.02 
FLIPI intermediate risk (vs low risk) 0.77 0.39-1.55 0.47 
FLIPI high risk (vs low risk) 2.35 1.08-5.10 0.03 
Disclosures

No relevant conflicts of interest to declare.

Author notes

*

Asterisk with author names denotes non-ASH members.

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