BACKGROUND: Chronic lymphocytic leukemia (CLL) is heterogeneous with respect to prognosis and clinical outcome. The mutational status of the immunoglobulin variable heavy chain region (IGHV) has been used to classify patients into 2 groups in terms of overall survival (OS) and clinical characteristics, but the labor-intensive nature and the cost of this time-consuming analysis has prompted investigations of surrogate markers. METHODS: We developed a standardized quantitative real-time reverse transcription-PCR (qPCR) method to measure zeta-chain (TCR)-associated protein kinase (ZAP70) mRNA in purified CD19(+) cells. We evaluated this and other methods (flow cytometry analyses of ZAP70 and CD38 proteins and qPCR analysis of lipoprotein lipase mRNA) in a cohort of 108 patients (median follow-up, 82 months) to evaluate any associations with IGHV mutational status, OS, and treatment-free survival (TFS). RESULTS: The association between qPCR-measured ZAP70 and IGHV mutational status was statistically significant [chi(2) (1) = 50.95; P <0.0001], and the value of Cramer's V statistic (0.72) indicated a very strong relation. This method also demonstrated sensitivity, specificity, and positive and negative predictive values of 87.8%, 85.7%, 87.5%, and 86%, respectively. ZAP70 expression was significantly associated with OS (P = 0.0021) and TFS (P <0.0001). ZAP70(+) patients had significantly shorter median TFS (24 months) than ZAP70(-) patients (157 months) (P <0.0001). Moreover, qPCR-measured ZAP70 expression has greater prognostic power than IGHV mutational status and the other prognostic markers tested. CONCLUSIONS: ZAP70 mRNA quantification via qPCR is a strong surrogate marker of IGHV mutational status and a powerful prognostic factor.
BACKGROUND:Chronic lymphocytic leukemia (CLL) is heterogeneous with respect to prognosis and clinical outcome. The mutational status of the immunoglobulin variable heavy chain region (IGHV) has been used to classify patients into 2 groups in terms of overall survival (OS) and clinical characteristics, but the labor-intensive nature and the cost of this time-consuming analysis has prompted investigations of surrogate markers. METHODS: We developed a standardized quantitative real-time reverse transcription-PCR (qPCR) method to measure zeta-chain (TCR)-associated protein kinase (ZAP70) mRNA in purified CD19(+) cells. We evaluated this and other methods (flow cytometry analyses of ZAP70 and CD38 proteins and qPCR analysis of lipoprotein lipase mRNA) in a cohort of 108 patients (median follow-up, 82 months) to evaluate any associations with IGHV mutational status, OS, and treatment-free survival (TFS). RESULTS: The association between qPCR-measured ZAP70 and IGHV mutational status was statistically significant [chi(2) (1) = 50.95; P <0.0001], and the value of Cramer's V statistic (0.72) indicated a very strong relation. This method also demonstrated sensitivity, specificity, and positive and negative predictive values of 87.8%, 85.7%, 87.5%, and 86%, respectively. ZAP70 expression was significantly associated with OS (P = 0.0021) and TFS (P <0.0001). ZAP70(+) patients had significantly shorter median TFS (24 months) than ZAP70(-) patients (157 months) (P <0.0001). Moreover, qPCR-measured ZAP70 expression has greater prognostic power than IGHV mutational status and the other prognostic markers tested. CONCLUSIONS:ZAP70 mRNA quantification via qPCR is a strong surrogate marker of IGHV mutational status and a powerful prognostic factor.
Authors: Mohd Arifin Kaderi; Meena Kanduri; Anne Mette Buhl; Marie Sevov; Nicola Cahill; Rebeqa Gunnarsson; Mattias Jansson; Karin Ekström Smedby; Henrik Hjalgrim; Jesper Jurlander; Gunnar Juliusson; Larry Mansouri; Richard Rosenquist Journal: Haematologica Date: 2011-04-20 Impact factor: 9.941
Authors: Basile Stamatopoulos; Michaël Van Damme; Emerence Crompot; Barbara Dessars; Hakim El Housni; Philippe Mineur; Nathalie Meuleman; Dominique Bron; Laurence Lagneaux Journal: Mol Med Date: 2015-01-09 Impact factor: 6.354
Authors: Lingzhi Zhang; Fiona Murray; Laura Z Rassenti; Minya Pu; Colleen Kelly; Joan R Kanter; Andrew Greaves; Karen Messer; Thomas J Kipps; Paul A Insel Journal: Int J Cancer Date: 2011-02-11 Impact factor: 7.396
Authors: Etienne Moussay; Valérie Palissot; Laurent Vallar; Hélène A Poirel; Thomas Wenner; Victoria El Khoury; Nasséra Aouali; Kris Van Moer; Bernadette Leners; François Bernardin; Arnaud Muller; Pascale Cornillet-Lefebvre; Alain Delmer; Caroline Duhem; Fernand Ries; Eric van Dyck; Guy Berchem Journal: Mol Cancer Date: 2010-05-20 Impact factor: 27.401