TY - JOUR
T1 - A TaqMan low-density array to predict outcome in advanced hodgkin's Lymphoma using paraffin-embedded samples
AU - Sánchez-Espiridión, Beatriz
AU - Sánchez-Aguilera, Abel
AU - Montalbán, Carlos
AU - Martin, Carmen
AU - Martinez, Rafael
AU - González-Carrero, Joaquin
AU - Poderos, Concepción
AU - Bellas, Carmen
AU - Fresno, Manuel F.
AU - Morante, Cesar
AU - Mestre, Maria J.
AU - Mendez, Miguel
AU - Mazorra, Francisco
AU - Conde, Eulogio
AU - Castaño, Angel
AU - Sánchez-Godoy, Pedro
AU - Tomas, José F.
AU - Morente, Manolo M.
AU - Piris, Miguel A.
AU - Garcfa, Juan F.
PY - 2009/2/15
Y1 - 2009/2/15
N2 - Purpose: Despite major advances in the treatment of classic Hodgkin's lymphoma (cHL), ∼ 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 bio- markers 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) orthe reactive cell microenvironment (mainly represented by specificT-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 todevel- op a new molecular outcome predictor for advanced cHL.
AB - Purpose: Despite major advances in the treatment of classic Hodgkin's lymphoma (cHL), ∼ 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 bio- markers 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) orthe reactive cell microenvironment (mainly represented by specificT-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 todevel- op a new molecular outcome predictor for advanced cHL.
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U2 - 10.1158/1078-0432.CCR-08-1119
DO - 10.1158/1078-0432.CCR-08-1119
M3 - Article
C2 - 19228737
AN - SCOPUS:63149134916
SN - 1078-0432
VL - 15
SP - 1367
EP - 1375
JO - Clinical Cancer Research
JF - Clinical Cancer Research
IS - 4
ER -