Cell-of-origin determined by both gene expression profiling and immunohistochemistry is the strongest predictor of survival in patients with diffuse large B-cell lymphoma.
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Abdulla M, Hollander P, Pandzic T, Mansouri L, Ednersson SB, Andersson PO, Hultdin M, Fors M, Erlanson M, Degerman S, Petersen HM, Asmar F, Grønbaek K, Enblad G, Cavelier L, Rosenquist R, Amini RM
Am. J. Hematol. 95 (1) 57-67 [2020-01-00; online 2019-11-07]
The tumor cells in diffuse large B-cell lymphomas (DLBCL) are considered to originate from germinal center derived B-cells (GCB) or activated B-cells (ABC). Gene expression profiling (GEP) is preferably used to determine the cell of origin (COO). However, GEP is not widely applied in clinical practice and consequently, several algorithms based on immunohistochemistry (IHC) have been developed. Our aim was to evaluate the concordance of COO assignment between the Lymph2Cx GEP assay and the IHC-based Hans algorithm, to decide which model is the best survival predictor. Both GEP and IHC were performed in 359 homogenously treated Swedish and Danish DLBCL patients, in a retrospective multicenter cohort. The overall concordance between GEP and IHC algorithm was 72%; GEP classified 85% of cases assigned as GCB by IHC, as GCB, while 58% classified as non-GCB by IHC, were categorized as ABC by GEP. There were significant survival differences (overall survival and progression-free survival) if cases were classified by GEP, whereas if cases were categorized by IHC only progression-free survival differed significantly. Importantly, patients assigned as non-GCB/ABC both by IHC and GEP had the worst prognosis, which was also significant in multivariate analyses. Double expression of MYC and BCL2 was more common in ABC cases and was associated with a dismal outcome. In conclusion, to determine COO both by IHC and GEP is the strongest outcome predictor to identify DLBCL patients with the worst outcome.
Bioinformatics Support for Computational Resources [Service]
Clinical Genomics Uppsala [Collaborative]
PubMed 31659781
DOI 10.1002/ajh.25666
Crossref 10.1002/ajh.25666