Diagnosis of Burkitt lymphoma using an algorithmic approach - applicable in both resource-poor and resource-rich countries

Autor: Shahin Sayed, Kikkeri N. Naresh, Amos R. Mwakigonja, Lorenzo Leoncini, Chryste`le Bilhou-Nabera, Ian Magrath, Bessie Byakika, Martine Raphael, Patricia Rince, Monica Onorati, Alistair Reid, Michael Mawanda, Hazem A. H. Ibrahim, Stefano Lazzi, Furrat Amen, Emma Moshi, Martin D. Ogwang, Maria Raffaella Ambrosio, Emily A Rogena, Valeria Calbi
Rok vydání: 2011
Předmět:
Zdroj: British Journal of Haematology. 154:770-776
ISSN: 0007-1048
DOI: 10.1111/j.1365-2141.2011.08771.x
Popis: Distinguishing Burkitt lymphoma (BL) from B cell lymphoma, unclassifiable with features intermediate between diffuse large B-cell lymphoma (DLBCL) and BL (DLBCL/BL), and DLBCL is challenging. We propose an immunohistochemistry and fluorescent in situ hybridization (FISH) based scoring system that is employed in three phases - Phase 1 (morphology with CD10 and BCL2 immunostains), Phase 2 (CD38, CD44 and Ki-67 immunostains) and Phase 3 (FISH on paraffin sections for MYC, BCL2, BCL6 and immunoglobulin family genes). The system was evaluated on 252 aggressive B-cell lymphomas from Europe and from sub-Saharan Africa. Using the algorithm, we determined a specific diagnosis of BL or not-BL in 82%, 92% and 95% cases at Phases 1, 2 and 3, respectively. In 3·4% cases, the algorithm was not completely applicable due to technical reasons. Overall, this approach led to a specific diagnosis of BL in 122 cases and to a specific diagnosis of either DLBCL or DLBCL/BL in 94% of cases that were not diagnosed as BL. We also evaluated the scoring system on 27 cases of BL confirmed on gene expression/microRNA expression profiling. Phase 1 of our scoring system led to a diagnosis of BL in 100% of these cases.
Databáze: OpenAIRE