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Page 2 of 25 Lue et al. J Cancer Metastasis Treat 2022;8:11 https://dx.doi.org/10.20517/2394-4722.2021.193

main DLBCL subtypes: germinal center B-cell-like (GCB) and activated B-cell (ABC), with a third group
[1]
dubbed ‘unclassifiable’ for tumors that are unable to fit discretely into the two former groups . These
subtypes have differing oncogenic drivers that impact the clinical outcome, with GCB-DLBCLs having a
[1]
superior overall survival (OS) compared to ABC-DLBCLs . More recent genetic classification systems have
divided DLBCL into even smaller subgroups , which also have prognostic implications after standard of
[2-6]
care rituximab cyclophosphamide, doxorubicin, vincristine, prednisone (R-CHOP). In this review, we detail
the history of DLBCL classifications, the implications of these new molecular systems, and review recent
therapeutic agents for the treatment of DLBCL.

CLASSIFICATION SYSTEMS: IMMUNOHISTOCHEMISTRY TO GENE EXPRESSION
PROFILING
Over the past several years, our understanding regarding the immense heterogeneity that lies within DLBCL
has led to new molecular classifications based on diverse genetic profiles . Understanding the complex
[1]
molecular background of DLBCL may lead to improved therapeutic approaches in the future. Herein, we
describe the evolution of DLBCL taxonomy, starting with cell of origin (COO) designation to more recent
systems that further sub-classify DLBCL into smaller hierarchical groups [Table 1].

The concept of cell of origin: activated B-cell vs. germinal center Diffuse Large B-cell Lymphoma
The premise of classifying DLBCL into subtypes can date back to studies suggesting that CD10, the
common acute lymphoblastic leukemia antigen, could differentiate two classes of DLBCLs [7-10] , translating
into potential clinical implications based on an expression. Subsequently, using GEP, Alizadeh and
[11]
colleagues identified two distinct DLBCL subtypes, termed GCB and ABC, both of which are defined by
expression patterns that align with different stages of B-cell maturation. The authors concluded that after
standard of care treatment, GCB and ABC-DLBCLs are characterized by drastically different OS, with the 5-
year OS of GCB-DLBCLs being 76% vs. 16% for ABC-DLBCLs. The enhanced understanding of the
heterogeneity of DLBCL led to the identification of a third subtype termed “type 3”, or what we have
commonly come to know as DLBCL-unclassifiable, which represents a group of tumors that do not
discretely fit into ABC or GCB subgroups . Similarly to what was described by Alizadeh et al. , and limited
[11]
1
by retrospective analysis, this study confirmed that after anthracycline-based chemotherapy, GCB-DLBCL
patients demonstrated a superior OS compared to their ABC and unclassifiable counterparts (5-year OS:
60% vs. 35% vs. 39%, respectively).

[12]
Another study evaluated 58 DLBCL biopsies using oligonucleotide microarrays (Affymetrix) and
identified a 13-gene model that was able to predict dichotomous outcomes: cured vs. fatal/refractory. Using
[12]
the Affymetrix platform, Shipp et al. and colleagues attempted to validate COO genes identified by
Alizadeh et al. as a surrogate for prognosis after R-CHOP, while acknowledging the limitations that come
[11]
with this attempt which include: differential technology used by both groups (cDNA arrays/Lymphochip by
Alizadehet al. vs. oligionucleotide arrays/Affymetrix by Shippet al. ); differing panel of genes probed;
[12]
[11]
varying computational approaches; and lastly, different tumor samples studied. Notably, the two GEP arrays
developed by the separate groups shared 90 overlapping COO signature genes. As such, this 90 gene panel
was used to cluster DLBCL samples into ABC vs. GCB-DLBCL and was able to confirm the inferior
[11]
outcome of ABC-DLBCL tumors in the Alizadeh et al. samples (Lymphochip). However, no relationship
between COO and clinical outcome was observed in the 58 DLBCL samples used in Shipp et al. ’s
[12]
(Affymetrix) developmental analysis. In an attempt to reconcile these discrepancies, another classification
method was developed not only to distinguish COO, but also to estimate the likelihood that a tumor falls
[1]
within a particular subgroup . Applying this classification system to both the Lymphochip and
[13]
Affymetrix datasets, tumor samples identified as GCB had a clear survival advantage compared to those
[12]