Literature DB >> 20479282

A molecular risk score based on 4 functional pathways for advanced classical Hodgkin lymphoma.

Beatriz Sánchez-Espiridión1, Carlos Montalbán, Angel López, Javier Menárguez, Pilar Sabín, Carmen Ruiz-Marcellán, Andrés Lopez, Rafael Ramos, Jose Rodríguez, Araceli Cánovas, Carmen Camarero, Miguel Canales, Javier Alves, Reyes Arranz, Agustín Acevedo, Antonio Salar, Sergio Serrano, Agueda Bas, Jose M Moraleda, Pedro Sánchez-Godoy, Fernando Burgos, Concepción Rayón, Manuel F Fresno, José García Laraña, Mónica García-Cosío, Carlos Santonja, Jose L López, Marta Llanos, Manuela Mollejo, Joaquín González-Carrero, Ana Marín, Jerónimo Forteza, Ramón García-Sanz, Jose F Tomás, Manuel M Morente, Miguel A Piris, Juan F García.   

Abstract

Despite improvement in the treatment of advanced classical Hodgkin lymphoma, approximately 30% of patients relapse or die as result of the disease. Current predictive systems, determined by clinical and analytical parameters, fail to identify these high-risk patients accurately. We took a multistep approach to design a quantitative reverse-transcription polymerase chain reaction assay to be applied to routine formalin-fixed paraffin-embedded samples, integrating genes expressed by the tumor cells and their microenvironment. The significance of 30 genes chosen on the basis of previously published data was evaluated in 282 samples (divided into estimation and validation sets) to build a molecular risk score to predict failure. Adequate reverse-transcription polymerase chain reaction profiles were obtained from 262 of 282 cases (92.9%). Best predictor genes were integrated into an 11-gene model, including 4 functional pathways (cell cycle, apoptosis, macrophage activation, and interferon regulatory factor 4) able to identify low- and high-risk patients with different rates of 5-year failure-free survival: 74% versus 44.1% in the estimation set (P < .001) and 67.5% versus 45.0% in the validation set (P = .022). This model can be combined with stage IV into a final predictive model able to identify a group of patients with very bad outcome (5-year failure-free survival probability, 25.2%).

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Year:  2010        PMID: 20479282     DOI: 10.1182/blood-2010-02-270009

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


  13 in total

1.  Immunohistochemical markers for tumor associated macrophages and survival in advanced classical Hodgkin's lymphoma.

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

2.  Macrophages predict treatment outcome in Hodgkin's lymphoma.

Authors:  Christian Steidl; Pedro Farinha; Randy D Gascoyne
Journal:  Haematologica       Date:  2011-02       Impact factor: 9.941

3.  Hodgkin's Lymphomas: A Tumor Recognized by Its Microenvironment.

Authors:  S Montes-Moreno
Journal:  Adv Hematol       Date:  2010-10-24

4.  Expression of FOXP3, CD68, and CD20 at diagnosis in the microenvironment of classical Hodgkin lymphoma is predictive of outcome.

Authors:  Paul Greaves; Andrew Clear; Rita Coutinho; Andrew Wilson; Janet Matthews; Andrew Owen; Milensu Shanyinde; T Andrew Lister; Maria Calaminici; John G Gribben
Journal:  J Clin Oncol       Date:  2012-10-08       Impact factor: 44.544

Review 5.  Diagnostic and predictive biomarkers for lymphoma diagnosis and treatment in the era of precision medicine.

Authors:  Ruifang Sun; L Jeffrey Medeiros; Ken H Young
Journal:  Mod Pathol       Date:  2016-08-01       Impact factor: 7.842

Review 6.  The tumour microenvironment in B cell lymphomas.

Authors:  David W Scott; Randy D Gascoyne
Journal:  Nat Rev Cancer       Date:  2014-07-10       Impact factor: 60.716

7.  MicroRNA signatures and treatment response in patients with advanced classical Hodgkin lymphoma.

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

8.  Gene expression-based model using formalin-fixed paraffin-embedded biopsies predicts overall survival in advanced-stage classical Hodgkin lymphoma.

Authors:  David W Scott; Fong Chun Chan; Fangxin Hong; Sanja Rogic; King L Tan; Barbara Meissner; Susana Ben-Neriah; Merrill Boyle; Robert Kridel; Adele Telenius; Bruce W Woolcock; Pedro Farinha; Richard I Fisher; Lisa M Rimsza; Nancy L Bartlett; Bruce D Cheson; Lois E Shepherd; Ranjana H Advani; Joseph M Connors; Brad S Kahl; Leo I Gordon; Sandra J Horning; Christian Steidl; Randy D Gascoyne
Journal:  J Clin Oncol       Date:  2012-11-26       Impact factor: 44.544

Review 9.  Role of immune escape mechanisms in Hodgkin's lymphoma development and progression: a whole new world with therapeutic implications.

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

10.  Predicting treatment outcome in classical Hodgkin lymphoma: genomic advances.

Authors:  Enrico Derenzini; Anas Younes
Journal:  Genome Med       Date:  2011-04-28       Impact factor: 11.117

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