Purpose: Despite major advances in the treatment of classic Hodgkin's lymphoma (cHL), f30% of patientsinadvancedstagesmayeventuallydie as resultof the disease,andcurrentmethods topredict prognosis are ratherunreliable.Thus, the applicationof robust techniques for theidentificationofbiomarkers associated with treatment response is essentialif 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 functionalpathways associated withunfavorable outcome that were significantly enrichedin either the Hodgkin's and Reed-Sternberg cells (regulation of the G 2 -M checkpoint, chaperones, histone modification, and signalingpathways) or the reactive cellmicroenvironment (mainly representedby 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 biologicalpathways associated with treatment response and eventually usedina larger series to develop a new molecular outcome predictor for advanced cHL.