Rojas-Bilbao EA, Knott ME, Bal de Kier Joffé ED, Zerga ME, Nuñez M, Puricelli LI and Ranuncolo SM*
Background: Diffuse Large B-Cell Lymphoma (DLBCL) is the most common type of Non-Hodgkin Lymphoma in adults. This germinal center derived B cell lymphoma is a heterogeneous disease with a highly variable clinical course, currently treated with immune-chemotherapy. The International Prognosis Index (IPI) remains the main prognosis indicator. This highlights the absence of biomarkers suitable to provide molecular biology information to more accurately establish prognosis and predict treatment response in DLBCL patients.
Methods: We determined the Oct2, BCL6, IRF8, OCAB and PU.1 transcription factors expression by immunohistochemistry in 73 DLBCL lymph node biopsies to address their potential as prognosis biomarkers in DLBCL patients. These molecules exhibit well-known key roles in the germinal center development.
Results: A large number of cases showed high Oct2 (64/73), BCL6 (40/73) and/or IRF8 (44/73) percentage of positive tumor cell nuclei. In contrast, a significant number of analyzed biopsies, showed a low OCAB and/or PU.1 percentage of positive tumor cells. The expression of each factor was not associated with any of the relevant clinical-pathological features including the DLBCL molecular subtype and the IPI. Oct2, BCL6 and IRF8 high expression (more than 70% of positive tumor cells) correlated with poor prognosis in terms of shorter overall survival. Particularly, high BCL6 and IRF8 expression maintained their prognostic value in a multivariate analysis stratified for the IPI score. Interestingly, IRF8 emerged as a novel prognosis indicator among the free bone marrow disease patients at diagnosis, subjected to a specific multivariate analysis named classification tree. Patients with free-bone marrow disease, which normally have a better outcome, showed a worse prognosis when they expressed high IRF8 at diagnosis.
Conclusions: The assessment of these factors expression would provide novel cellular and molecular insights to more efficiently predict DLBCL patient prognosis.
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