PURPOSE: Overexpression of cyclin D1 mRNA and protein as a result of the chromosomal translocation t(11;14)(q13;q32) is a highly specific molecular marker of mantle cell lymphoma, but cyclin D1 dysregulation can also be found in other B-cell neoplasias. The aim of the study was to develop a precise and reliable tool for quantitation of cyclin D1 mRNA suitable for archival clinical specimens. EXPERIMENTAL DESIGN: A real-time reverse transcription-PCR (RT-PCR) assay was used to quantitate cyclin D1 mRNA copy numbers. Using 2000 microdissected cells as template, 104 formalin-fixed, paraffin-embedded lymph node, spleen, and decalcified bone marrow biopsies from a panel of 95 cases of B-cell non-Hodgkin's lymphomas (B-NHLs) were analyzed. In addition, cyclin D1 protein expression was assessed by immunohistochemistry. RESULTS: Strong cyclin D1 mRNA overexpression was detected in mantle cell lymphomas (23 of 23), hairy cell leukemias (5 of 19), and multiple myelomas (7 of 23) with particularly high levels in 2 of the latter cases. Intermediate transcript levels were found in 5 of 23 multiple myelomas and 7 of 19 hairy cell leukemias. B-cell chronic lymphocytic leukemias (10 of 10), follicular lymphomas (9 of 9), mucosa-associated lymphoid tissue lymphomas (5 of 5) and reactive lymphoid tissues with the exception of normal spleen had no or very low cyclin D1 expression. In comparison with real-time RT-PCR, immunohistochemistry showed a lower level of sensitivity, more variability, and did not allow accurate quantitation. CONCLUSIONS: Real-time RT-PCR for cyclin D1 mRNA is an excellent tool for the differential diagnosis of B-NHLs and, in combination with microdissection, a powerful approach for retrospective trials using archival clinical specimens as tissue source. Furthermore, real-time RT-PCR may help to identify subgroups of B-NHLs according to cyclin D1 mRNA copy numbers and to investigate the possible influence of different chromosomal breakpoints on cyclin D1 expression.
PURPOSE: Overexpression of cyclin D1 mRNA and protein as a result of the chromosomal translocation t(11;14)(q13;q32) is a highly specific molecular marker of mantle cell lymphoma, but cyclin D1 dysregulation can also be found in other B-cell neoplasias. The aim of the study was to develop a precise and reliable tool for quantitation of cyclin D1 mRNA suitable for archival clinical specimens. EXPERIMENTAL DESIGN: A real-time reverse transcription-PCR (RT-PCR) assay was used to quantitate cyclin D1 mRNA copy numbers. Using 2000 microdissected cells as template, 104 formalin-fixed, paraffin-embedded lymph node, spleen, and decalcified bone marrow biopsies from a panel of 95 cases of B-cell non-Hodgkin's lymphomas (B-NHLs) were analyzed. In addition, cyclin D1 protein expression was assessed by immunohistochemistry. RESULTS: Strong cyclin D1 mRNA overexpression was detected in mantle cell lymphomas (23 of 23), hairy cell leukemias (5 of 19), and multiple myelomas (7 of 23) with particularly high levels in 2 of the latter cases. Intermediate transcript levels were found in 5 of 23 multiple myelomas and 7 of 19 hairy cell leukemias. B-cell chronic lymphocytic leukemias (10 of 10), follicular lymphomas (9 of 9), mucosa-associated lymphoid tissue lymphomas (5 of 5) and reactive lymphoid tissues with the exception of normal spleen had no or very low cyclin D1 expression. In comparison with real-time RT-PCR, immunohistochemistry showed a lower level of sensitivity, more variability, and did not allow accurate quantitation. CONCLUSIONS: Real-time RT-PCR for cyclin D1 mRNA is an excellent tool for the differential diagnosis of B-NHLs and, in combination with microdissection, a powerful approach for retrospective trials using archival clinical specimens as tissue source. Furthermore, real-time RT-PCR may help to identify subgroups of B-NHLs according to cyclin D1 mRNA copy numbers and to investigate the possible influence of different chromosomal breakpoints on cyclin D1 expression.
Authors: Julia Slotta-Huspenina; Ina Koch; Laurence de Leval; Gisela Keller; Margit Klier; Karin Bink; Marcus Kremer; Mark Raffeld; Falko Fend; Leticia Quintanilla-Martinez Journal: Haematologica Date: 2012-02-07 Impact factor: 9.941
Authors: Kathryne Melissa Keays; Gregory P Owens; Alanna M Ritchie; Donald H Gilden; Mark P Burgoon Journal: J Immunol Methods Date: 2005-07 Impact factor: 2.303
Authors: Leticia Quintanilla-Martinez; Julia Slotta-Huspenina; Ina Koch; Margit Klier; Eric D Hsi; Laurence de Leval; Wolfram Klapper; Stefan Gesk; Reiner Siebert; Falko Fend Journal: Haematologica Date: 2009-07-16 Impact factor: 9.941