Immunohistochemical profiling based on Bcl-2, CD10 and MUM1 expression improves risk stratification in patients with primary nodal diffuse large B cell lymphoma.
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SourceJournal of Pathology, 208, 5, (2006), pp. 714-723
Article / Letter to editor
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Journal of Pathology
SubjectNCMLS 3: Growth and differentiation; NCMLS 6: Genetics and epigenetic pathways of disease; ONCOL 1: Hereditary cancer and cancer-related syndromes; ONCOL 2: Age-related aspects of cancer; ONCOL 3: Translational research; UMCN 1.2: Molecular diagnosis, prognosis and monitoring; NCMLS 3: Growth and differentiation
Clinical outcome in patients with diffuse large B cell lymphomas (DLBCL) is poorly predictable. Expression of proteins related to germinal centre B (GCB) cell or activated B cells (ABC) and expression of apoptosis-regulating proteins Bcl-2 and XIAP have been found previously to be strongly associated with clinical outcome. In this study we aimed to develop an algorithm based on expression of GCB/ABC-related proteins CD10, Bcl-6 and MUM1 and apoptosis-inhibiting proteins Bcl-2, XIAP and cFLIP for optimal stratification of DLBCL patients into prognostically favourable and unfavourable groups. Expression of CD10 and cFLIP was associated with better overall survival (both p = 0.03), whereas expression of MUM1, Bcl-2 and XIAP was associated with poor clinical outcome (p = 0.01, p = 0.0007 and p = 0.03, respectively). Multivariate analysis revealed that Bcl-2 was the strongest prognostic marker followed by CD10 and MUM1. Stratification of patients according to a new algorithm based on expression of these three markers improved patient risk stratification into low and particularly high clinical risk groups (p = 0.04 and p < 0.0001, respectively). We conclude that, in our group of primary nodal DLBCLs, a new algorithm, based on expression of the apoptosis-inhibiting protein Bcl-2 and the GCB/ABC-related proteins CD10 and MUM1, strongly predicts outcome in International Prognostic Index (IPI)-low and -high patients. Its predictive power is stronger than previously published algorithms based on only GCB/ABC- or apoptosis-regulating proteins.
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