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Review
. 2014 Oct 15;20(20):5182-93.
doi: 10.1158/1078-0432.CCR-14-0497.

Precision treatment of distinct molecular subtypes of diffuse large B-cell lymphoma: ascribing treatment based on the molecular phenotype

Affiliations
Review

Precision treatment of distinct molecular subtypes of diffuse large B-cell lymphoma: ascribing treatment based on the molecular phenotype

Kieron Dunleavy et al. Clin Cancer Res. .

Abstract

Although diffuse large B-cell lymphoma (DLBCL), the most common type of non-Hodgkin lymphoma, was once considered to be a single disease, novel insights into its biology have revealed that it is molecularly heterogeneous. Technologies such as gene expression profiling have revealed that DLBCL consists of at least three distinct molecular diseases that have disparate outcomes following standard therapy. These subtypes arise from different stages of B-cell differentiation and are characterized by distinct oncogenic activation mechanisms. This knowledge has led to the investigation of strategies and novel agents that have selective activity within molecular subtypes and sets the stage for an era of precision medicine in DLBCL therapeutics, where therapy can be ascribed based on molecular phenotype. This work offers the chance of improving the curability of DLBCL, particularly in the activated B-cell subtype, where standard approaches are inadequate for a high proportion of patients. See all articles in this CCR Focus section, "Paradigm Shifts in Lymphoma."

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Conflict of interest statement

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Figures

Figure 1
Figure 1
Patients with DLBCL outcomes following R-CHOP according to COO (in the independent validation cohort). (A) Progression-free survival for COO assignment using the ‘Hans’ algorithm (B) Overall survival for COO assignment using the ‘Hans’ algorithm (C) Progression-free survival in the COO groups as determined by the Lymph2Cx assay. (D) Overall survival in the COO groups as determined by the Lymph2Cx assay. (E) Progression-free survival in the COO groups determined by the gold standard method applying the previously described model6 to gene expression on FT. (F) Overall survival in the COO groups determined by the gold standard method. The P values are from log-rank tests comparing the ABC and GCB groups. The log-rank tests are 1 sided in the direction of greater hazard for ABC. RR, relative risk (with the 95% confidence interval in brackets) associated with the ABC group compared with the GCB group. Reprinted from Scott et al. (19).
Figure 2
Figure 2
Oncogenic Pathways for GCB, ABC and PMBL DLBCL. These sub-types originate from various stages of B-cell differentiation and acquire distinct oncogenic abnormalities as shown. AID denotes activation-induced cytidine deaminase, ITAM immuno-receptor tyrosine-based activation motifs, mTOR mammalian target of rapamycin, and NF-κB nuclear factor-κB. Blue lines indicate activation, and red lines indicate inhibition. Adapted from Lenz and Staudt (103).
Figure 3
Figure 3
Evolution of DLBCL Therapeutics. Schema of progress in DLBCL clinical trials over the past 30 years. This schema shows selected randomized studies in DLBCL from the pre to post rituximab eras and within molecular subtypes of DLBCL. CHOP; cyclophosphamide, doxorubicin, vincristine, prednisone. m-BACOD; methotrexate, bleomycin, doxorubicin, cyclophosphamide, vincristine, dexamethasone. CHOEP; CHOP with etoposide; ACVBP; dose-intensified doxorubicin, cyclophosphamide, vindesine, bleomycin, and prednisone. R-CHOP-I – R-CHOP ibrutinib; R2-CHOP – R-CHOP with lenalidomide (revlimid). RB-CHOP – R-CHOP with bortezomib; R_CHOP-I – R-CHOP with ibrutinib.
Figure 4
Figure 4
Map of B-cell receptor (BCR) and MYD88 signaling pathways and potential targets. Signaling through BCR leads to down stream activation of the NFκB transcription factor, which is a driver pathway in ABC DLBCL. Signaling also activates the AKT/MTOR and MAP kinase pathways. Constitutive MYD88 signaling is an alternative pathway leading to NFκB activation. Adapted from Yang et al. (69).

References

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