[1391] Comparing Immunohistochemical Methods for Predicting Gene Expression Profile and Survival of Diffuse Large B-Cell Lymphoma Treated with Rituximab

PN Meyer, LM Smith, K Fu, TC Greiner, P Aoun, J Delabie, RD Gascoyne, A Rosenwald, RM Braziel, E Campo, JM Vose, G Lenz, LM Staudt, WC Chan, DD Weisenburger. University of Nebraska Medical Center, Omaha, NE; Leukemia/Lymphoma Molecular Profiling Project, Omaha, NE

Background: Diffuse large B-cell lymphomas (DLBCL) have variation in survival. Gene expression profiling (GEP) shows DLBCL from germinal center B-cells (GCB) have better prognosis than activated B-cells (ABC). Immunohistochemical algorithms to predict cell of origin have been published. Our goal was to compare these algorithms and evaluate new methods to predict GEP and survival.
Design: Tissue microarrays (TMA) were created from 216 cases of DLBCL treated with rituximab and CHOP-like therapies. Clinical data were available for all cases. TMA were analyzed for GCET1, CD10, BCL6, MUM1, FOXP1, and LMO2. GEP were available on 168 of these cases. Sensitivity, specificity, positive predictive value, negative predictive value, and concordance with GEP were calculated. Overall survival for each method was determined by Kaplan-Meier curves, with differences evaluated by log-rank test.
Results: Concordance, sensitivity, and specificity were high with Hans and Choi algorithms. LMO2 alone had lower concordance, sensitivity, and specificity. The Muris or Nyman algorithms had low specificity or sensitivity, respectively. Removal of BCL6 from Hans (Hans*) and Choi (Choi*) algorithms did not lose predictive value. A tally system counting positive GCB markers (GCET1, CD10, and LMO2) versus positive ABC markers (MUM1 and FOXP1) had highest concordance and specificity while maintaining high sensitivity. All methods examined, except the Nyman algorithm, divided DLBCL patients into statistically significant prognostic groups.

SensitivitySpecificityPPVNPVConcordanceSurvival
Tally8599988692p=0.0056
Choi8489898486p<0.001
Choi*8489898486p=0.026
Hans*8983858886p=0.0073
Hans80898881840.0015
Nyman6596947280p=0.17
LMO27974777677p=0.003
Muris9949679774p<0.001



Conclusions: Our results demonstrate the Hans and Choi algorithms (with or without BCL6) were best in predicting GEP results and survival. A tally system counting specific GCB and ABC antigens showed better ability to predict GEP results than any of the algorithms. This tally system, like most of the algorithms, also predicted survival of DLBCL patients.
Category: Hematopathology

Wednesday, March 24, 2010 9:30 AM

Poster Session V # 185, Wednesday Morning

 

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