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Lue et al. J Cancer Metastasis Treat 2022;8:11 https://dx.doi.org/10.20517/2394-4722.2021.193 Page 5 of 25

DLBCL. With this, a genomic risk model incorporating 150 driver genes, COO designation, and
MYC/BCL2 expression was able to better stratify response to therapy compared to the IPI clinical model, as
well as models relying only on COO, MYC and/or BCL2 expression.

[2]
In another attempt to better understand the genetic landscape of DLBCL, Schmitz et al. characterized 574
DLBCL samples (NCI cohort) utilizing exome and transcriptome sequencing, array-based DNA copy
number analysis and targeted amplicon resequencing. Four genetic subtypes were elucidated: (1) MCD
defined by MYD88 L265P and CD79B mutations, (2) N1 based on NOTCH1 mutations, (3) BN2 based on
BCL6 fusions and NOTCH2 mutations; and (4) EZB characterized by EZH2 mutations and BCL2
translocations. Stratification of outcomes based on this molecular classification revealed that the MCD and
N1 subtypes had inferior OS compared to the BN2 and EZB counterparts after standard of care R-CHOP
therapy. The LymphGen algorithm builds upon the aforementioned 4-class taxonomy, identifying 7
subtypes: MCD, N1, BN2, ST2 (characterized by SGK1 and TET2 mutated), A53 (defined by aneuploidy
with TP53 inactivation), and divides the EZB category into two dichotomous subtypes: EZB MYC-positive
vs. EZB MYC-negative based on the presence or absence of a Double Hit signature (discussed below). This
[4]
genetic algorithm validated the inferior OS observed in the MCD and N1 tumor subtypes. Ultimately, the
LymphGen algorithm was able to successfully classify more patient tumors in the NCI cohort (63.1%)
[2]
compared to the initial 4 class method (Schmitz et al. , 46.6%). Thus, it is clear that not all tumors fall
discretely into these categories, indicating that there is still a need to build upon these current molecular
programs.

In the cluster (C) classification system, five genetically unique subgroups were defined, with a sixth cluster
(C0) consisting of a small number of tumor samples (12 of 304) with no common defining drivers . In this
[3]
system, C3 (defined by BCL2, KTM2D, CREBBP, EZH2, PTEN mutations) and C5 (based on MYDL265P,
CD79B, ETV6, PIM1, GRHPR, TBL1XR1, BTG1 mutations and BCL2 gains) exhibited markedly inferior
progression-free survival (PFS) compared to C1, C2, and C4. Interestingly, C3 and C5 are comprised mostly
of GC-DLBCL and ABC-DLBCL cases, respectively, reinforcing the notion that there is more to classifying
tumors based solely on COO. Together, this data suggests that the heterogeneous landscape of DLBCL is
more complex than the COO classification, and that these new molecular classifications may lend
themselves to precision-based medicine approaches.

Double hit lymphoma signature
High-grade B-cell lymphoma with MYC and BCL2 and/or BCL6 rearrangements, termed Double Hit
(DHL) or Triple Hit lymphomas (THL) have dismal outcomes after standard chemoimmunotherapy [27-29] .
These diagnoses rely on FISH analysis to evaluate and confirm rearrangements of MYC, BCL2 and/or
BCL6. In order to define the genetic landscape of DHL/THL, Ennishi and colleagues analyzed 157 GCB-
DLBCL primary tumor samples, of which 25 were DHL/THL based on FISH, and developed a DHL
signature (DHITsig), comprising of 104 differentially expressed genes . Twenty-seven percent of GCB-
[5]
DLBCLs were characterized as positive for the DHITsig, with only 50% of these tumors harboring MYC and
BCL2 translocations. Traditionally, GCB-DLBCLs are thought to originate from the light zone of the GC
based on GEP; however, tumors that were DHITsig positive displayed more similarities to B-lymphocytes
from the intermediate zone of the GC, suggesting a completely unique COO for DHL/THL. This was
recapitulated by the presence of intermediate zone genes in the DHITsig. The prognostic implication of the
DHITsig was validated in two separate cohorts (BC Cancer Center Cohort, n = 261; and Reddy et al.
[26]
cohort, n = 511), both of which demonstrated clear survival disadvantage for patients with the DHITsig,
which paralleled the outcomes of ABC-DLBCL patients. Interestingly, along with MYC and BCL2
mutations, TP53, EZH2, CREBBP, DDX3X and KMT2D were more frequently mutated in the DHITsig
positive tumors as compared to the DHITsig negative tumors, suggesting possible therapeutic interventions