PURPOSE: Current therapies fail to cure a significant proportion of patients with Hodgkin's lymphoma (HL). Predictive systems for stratification of the disease and selection of treatment based on sets of clinical variables, such as the international prognostic score (IPS), are of relatively small practical value. The predictive use of biologic parameters has so far provided limited and inconsistent results. Here we explore the influence of a set of molecular markers on the outcome of HL. PATIENTS AND METHODS: Forty molecular markers involved in B-cell differentiation and activation, signal transduction, cell cycle, and apoptosis control were analyzed in 259 classic HL patient cases by using tissue microarrays. Univariate analysis was performed to evaluate the influence of markers on favorable outcome (complete remission of > 12 months). Significant variables were included in a multivariate logistic regression analysis, and the probability of favorable outcome was estimated. RESULTS: Univariate analysis revealed four molecular markers that predicted outcome, and the multivariate analysis showed p53, Bcl-X(L), and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate-biotin nick-end labeling (TUNEL) to have independent significance. The combination of these factors determined two groups of patients (group I, zero to one factor; group II, two to three factors) with a probability of a favorable outcome of.948 and.687, respectively. A multivariate Cox's model shows that these biologic risk groups have special predictive power in low-IPS patients. CONCLUSION: The data from this exploratory study suggest that the accumulation of molecular events seems to influence the outcome of HL, particularly in the low-IPS group.
PURPOSE: Current therapies fail to cure a significant proportion of patients with Hodgkin's lymphoma (HL). Predictive systems for stratification of the disease and selection of treatment based on sets of clinical variables, such as the international prognostic score (IPS), are of relatively small practical value. The predictive use of biologic parameters has so far provided limited and inconsistent results. Here we explore the influence of a set of molecular markers on the outcome of HL. PATIENTS AND METHODS: Forty molecular markers involved in B-cell differentiation and activation, signal transduction, cell cycle, and apoptosis control were analyzed in 259 classic HL patient cases by using tissue microarrays. Univariate analysis was performed to evaluate the influence of markers on favorable outcome (complete remission of > 12 months). Significant variables were included in a multivariate logistic regression analysis, and the probability of favorable outcome was estimated. RESULTS: Univariate analysis revealed four molecular markers that predicted outcome, and the multivariate analysis showed p53, Bcl-X(L), and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate-biotin nick-end labeling (TUNEL) to have independent significance. The combination of these factors determined two groups of patients (group I, zero to one factor; group II, two to three factors) with a probability of a favorable outcome of.948 and.687, respectively. A multivariate Cox's model shows that these biologic risk groups have special predictive power in low-IPSpatients. CONCLUSION: The data from this exploratory study suggest that the accumulation of molecular events seems to influence the outcome of HL, particularly in the low-IPS group.
Authors: Ljubomir R Jakovic; Biljana S Mihaljevic; Maja D Perunicic Jovanovic; Andrija D Bogdanovic; Vesna M Cemerikic Martinovic; Tamara K Kravic; Vladimir Z Bumbasirevic Journal: Med Oncol Date: 2007 Impact factor: 3.064
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Authors: Beatriz Sánchez-Espiridión; Ana M Martín-Moreno; Carlos Montalbán; Vianihuini Figueroa; Francisco Vega; Anas Younes; L Jeffrey Medeiros; Francisco J Alvés; Miguel Canales; Mónica Estévez; Javier Menarguez; Pilar Sabín; María C Ruiz-Marcellán; Andrés Lopez; Pedro Sánchez-Godoy; Fernando Burgos; Carlos Santonja; José L López; Miguel A Piris; Juan F Garcia Journal: Br J Haematol Date: 2013-06-01 Impact factor: 6.998
Authors: Luis de la Cruz-Merino; Marylène Lejeune; Esteban Nogales Fernández; Fernando Henao Carrasco; Ana Grueso López; Ana Illescas Vacas; Mariano Provencio Pulla; Cristina Callau; Tomás Álvaro Journal: Clin Dev Immunol Date: 2012-08-15