| Literature DB >> 22437443 |
C Visco1, Y Li, Z Y Xu-Monette, R N Miranda, T M Green, Y Li, A Tzankov, W Wen, W-m Liu, B S Kahl, E S G d'Amore, S Montes-Moreno, K Dybkær, A Chiu, W Tam, A Orazi, Y Zu, G Bhagat, J N Winter, H-Y Wang, S O'Neill, C H Dunphy, E D Hsi, X F Zhao, R S Go, W W L Choi, F Zhou, M Czader, J Tong, X Zhao, J H van Krieken, Q Huang, W Ai, J Etzell, M Ponzoni, A J M Ferreri, M A Piris, M B Møller, C E Bueso-Ramos, L J Medeiros, L Wu, K H Young.
Abstract
Gene expression profiling (GEP) has stratified diffuse large B-cell lymphoma (DLBCL) into molecular subgroups that correspond to different stages of lymphocyte development-namely germinal center B-cell like and activated B-cell like. This classification has prognostic significance, but GEP is expensive and not readily applicable into daily practice, which has lead to immunohistochemical algorithms proposed as a surrogate for GEP analysis. We assembled tissue microarrays from 475 de novo DLBCL patients who were treated with rituximab-CHOP chemotherapy. All cases were successfully profiled by GEP on formalin-fixed, paraffin-embedded tissue samples. Sections were stained with antibodies reactive with CD10, GCET1, FOXP1, MUM1 and BCL6 and cases were classified following a rationale of sequential steps of differentiation of B cells. Cutoffs for each marker were obtained using receiver-operating characteristic curves, obviating the need for any arbitrary method. An algorithm based on the expression of CD10, FOXP1 and BCL6 was developed that had a simpler structure than other recently proposed algorithms and 92.6% concordance with GEP. In multivariate analysis, both the International Prognostic Index and our proposed algorithm were significant independent predictors of progression-free and overall survival. In conclusion, this algorithm effectively predicts prognosis of DLBCL patients matching GEP subgroups in the era of rituximab therapy.Entities:
Mesh:
Substances:
Year: 2012 PMID: 22437443 PMCID: PMC3637886 DOI: 10.1038/leu.2012.83
Source DB: PubMed Journal: Leukemia ISSN: 0887-6924 Impact factor: 11.528