PURPOSE: Despite major advances in the treatment of classic Hodgkin's lymphoma (cHL), approximately 30% of patients in advanced stages may eventually die as result of the disease, and current methods to predict prognosis are rather unreliable. Thus, the application of robust techniques for the identification of biomarkers associated with treatment response is essential if new predictive tools are to be developed. EXPERIMENTAL DESIGN: We used gene expression data from advanced cHL patients to identify transcriptional patterns from the tumoral cells and their nonneoplastic microenvironment, associated with lack of maintained treatment response. Gene-Set Enrichment Analysis was used to identify functional pathways associated with unfavorable outcome that were significantly enriched in either the Hodgkin's and Reed-Sternberg cells (regulation of the G2-M checkpoint, chaperones, histone modification, and signaling pathways) or the reactive cell microenvironment (mainly represented by specific T-cell populations and macrophage activation markers). RESULTS: To explore the pathways identified previously, we used a series of 52 formalin-fixed paraffin-embedded advanced cHL samples and designed a real-time PCR-based low-density array that included the most relevant genes. A large majority of the samples (82.7%) and all selected genes were analyzed successfully with this approach. CONCLUSIONS: The results of this assay can be combined in a single risk score integrating these biological pathways associated with treatment response and eventually used in a larger series to develop a new molecular outcome predictor for advanced cHL.
PURPOSE: Despite major advances in the treatment of classic Hodgkin's lymphoma (cHL), approximately 30% of patients in advanced stages may eventually die as result of the disease, and current methods to predict prognosis are rather unreliable. Thus, the application of robust techniques for the identification of biomarkers associated with treatment response is essential if new predictive tools are to be developed. EXPERIMENTAL DESIGN: We used gene expression data from advanced cHL patients to identify transcriptional patterns from the tumoral cells and their nonneoplastic microenvironment, associated with lack of maintained treatment response. Gene-Set Enrichment Analysis was used to identify functional pathways associated with unfavorable outcome that were significantly enriched in either the Hodgkin's and Reed-Sternberg cells (regulation of the G2-M checkpoint, chaperones, histone modification, and signaling pathways) or the reactive cell microenvironment (mainly represented by specific T-cell populations and macrophage activation markers). RESULTS: To explore the pathways identified previously, we used a series of 52 formalin-fixed paraffin-embedded advanced cHL samples and designed a real-time PCR-based low-density array that included the most relevant genes. A large majority of the samples (82.7%) and all selected genes were analyzed successfully with this approach. CONCLUSIONS: The results of this assay can be combined in a single risk score integrating these biological pathways associated with treatment response and eventually used in a larger series to develop a new molecular outcome predictor for advanced cHL.
Authors: Beatriz Sánchez-Espiridión; Ana M Martin-Moreno; Carlos Montalbán; L Jeffrey Medeiros; Francisco Vega; Anas Younes; Miguel A Piris; Juan F Garcia Journal: Haematologica Date: 2012-02-07 Impact factor: 9.941
Authors: William A Truitt; Sheketha R Hauser; Gerald A Deehan; Jamie E Toalston; Jessica A Wilden; Richard L Bell; William J McBride; Zachary A Rodd Journal: Psychopharmacology (Berl) Date: 2014-08-26 Impact factor: 4.530
Authors: Maja Kodani; Genyan Yang; Laura M Conklin; Tatiana C Travis; Cynthia G Whitney; Larry J Anderson; Stephanie J Schrag; Thomas H Taylor; Bernard W Beall; Robert F Breiman; Daniel R Feikin; M Kariuki Njenga; Leonard W Mayer; M Steven Oberste; Maria Lucia C Tondella; Jonas M Winchell; Stephen L Lindstrom; Dean D Erdman; Barry S Fields Journal: J Clin Microbiol Date: 2011-04-06 Impact factor: 5.948
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