BACKGROUND: The survival of patients with diffuse large-B-cell lymphoma after chemotherapy is influenced by molecular features of the tumors. We used the gene-expression profiles of these lymphomas to develop a molecular predictor of survival. METHODS: Biopsy samples of diffuse large-B-cell lymphoma from 240 patients were examined for gene expression with the use of DNA microarrays and analyzed for genomic abnormalities. Subgroups with distinctive gene-expression profiles were defined on the basis of hierarchical clustering. A molecular predictor of risk was constructed with the use of genes with expression patterns that were associated with survival in a preliminary group of 160 patients and was then tested in a validation group of 80 patients. The accuracy of this predictor was compared with that of the international prognostic index. RESULTS: Three gene-expression subgroups--germinal-center B-cell-like, activated B-cell-like, and type 3 diffuse large-B-cell lymphoma--were identified. Two common oncogenic events in diffuse large-B-cell lymphoma, bcl-2 translocation and c-rel amplification, were detected only in the germinal-center B-cell-like subgroup. Patients in this subgroup had the highest five-year survival rate. To identify other molecular determinants of outcome, we searched for individual genes with expression patterns that correlated with survival in the preliminary group of patients. Most of these genes fell within four gene-expression signatures characteristic of germinal-center B cells, proliferating cells, reactive stromal and immune cells in the lymph node, or major-histocompatibility-complex class II complex. We used 17 genes to construct a predictor of overall survival after chemotherapy. This gene-based predictor and the international prognostic index were independent prognostic indicators. CONCLUSIONS: DNA microarrays can be used to formulate a molecular predictor of survival after chemotherapy for diffuse large-B-cell lymphoma.
BACKGROUND: The survival of patients with diffuse large-B-cell lymphoma after chemotherapy is influenced by molecular features of the tumors. We used the gene-expression profiles of these lymphomas to develop a molecular predictor of survival. METHODS: Biopsy samples of diffuse large-B-cell lymphoma from 240 patients were examined for gene expression with the use of DNA microarrays and analyzed for genomic abnormalities. Subgroups with distinctive gene-expression profiles were defined on the basis of hierarchical clustering. A molecular predictor of risk was constructed with the use of genes with expression patterns that were associated with survival in a preliminary group of 160 patients and was then tested in a validation group of 80 patients. The accuracy of this predictor was compared with that of the international prognostic index. RESULTS: Three gene-expression subgroups--germinal-center B-cell-like, activated B-cell-like, and type 3 diffuse large-B-cell lymphoma--were identified. Two common oncogenic events in diffuse large-B-cell lymphoma, bcl-2 translocation and c-rel amplification, were detected only in the germinal-center B-cell-like subgroup. Patients in this subgroup had the highest five-year survival rate. To identify other molecular determinants of outcome, we searched for individual genes with expression patterns that correlated with survival in the preliminary group of patients. Most of these genes fell within four gene-expression signatures characteristic of germinal-center B cells, proliferating cells, reactive stromal and immune cells in the lymph node, or major-histocompatibility-complex class II complex. We used 17 genes to construct a predictor of overall survival after chemotherapy. This gene-based predictor and the international prognostic index were independent prognostic indicators. CONCLUSIONS: DNA microarrays can be used to formulate a molecular predictor of survival after chemotherapy for diffuse large-B-cell lymphoma.
Authors: Mi-Ae Lyu; Deepak Rai; Kwang Seok Ahn; Bokyung Sung; Lawrence H Cheung; John W Marks; Bharat B Aggarwal; Ricardo C T Aguiar; Varsha Gandhi; Michael G Rosenblum Journal: Neoplasia Date: 2010-05 Impact factor: 5.715
Authors: Sarah T Wilkinson; Kristie A Vanpatten; Diane R Fernandez; Patrick Brunhoeber; Karl E Garsha; Betty J Glinsmann-Gibson; Thomas M Grogan; Julie Teruya-Feldstein; Lisa M Rimsza Journal: Blood Date: 2011-12-13 Impact factor: 22.113
Authors: Carsten Zwick; Gerhard Held; Vera Hammermeister; Adnan Alahmad; Boris Kubuschok; Joerg Bittenbring; Manfred Ahlgrimm; Frank Neumann; Klaus-Dieter Preuss; Michael Pfreundschuh Journal: J Cancer Res Clin Oncol Date: 2009-02-21 Impact factor: 4.553