A molecular risk score based on 4 functional pathways for advanced classical Hodgkin lymphoma.
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%).
Sánchez-Espiridión
Beatriz
B
Molecular Pathology Programme, Genetic and Molecular Epidemiology Group, Tumour Bank, Centro Nacional de Investigaciones Oncológicas, Madrid, Spain.
Montalbán
Carlos
C
López
Angel
A
Menárguez
Javier
J
Sabín
Pilar
P
Ruiz-Marcellán
Carmen
C
Lopez
Andrés
A
Ramos
Rafael
R
Rodríguez
Jose
J
Cánovas
Araceli
A
Camarero
Carmen
C
Canales
Miguel
M
Alves
Javier
J
Arranz
Reyes
R
Acevedo
Agustín
A
Salar
Antonio
A
Serrano
Sergio
S
Bas
Agueda
A
Moraleda
Jose M
JM
Sánchez-Godoy
Pedro
P
Burgos
Fernando
F
Rayón
Concepción
C
Fresno
Manuel F
MF
Laraña
José García
JG
García-Cosío
Mónica
M
Santonja
Carlos
C
López
Jose L
JL
Llanos
Marta
M
Mollejo
Manuela
M
González-Carrero
Joaquín
J
Marín
Ana
A
Forteza
Jerónimo
J
García-Sanz
Ramón
R
Tomás
Jose F
JF
Morente
Manuel M
MM
Piris
Miguel A
MA
García
Juan F
JF
D000465:Algorithms; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D005260:Female; D020869:Gene Expression Profiling; D006689:Hodgkin Disease / Q000175:diagnosis* / Q000188:drug therapy / Q000235:genetics*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009364:Neoplasm Recurrence, Local / Q000175:diagnosis* / Q000188:drug therapy / Q000235:genetics*; D018365:Neoplasm, Residual / Q000175:diagnosis / Q000188:drug therapy / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis; D016612:Paraffin Embedding; D012333:RNA, Messenger / Q000235:genetics; D012074:Remission Induction; D020133:Reverse Transcriptase Polymerase Chain Reaction; D018570:Risk Assessment; D015398:Signal Transduction / Q000187:drug effects*; D015996:Survival Rate; D016896:Treatment Outcome
D014408:Biomarkers, Tumor; D012333:RNA, Messenger