Cells currently falling under the ABC classification to tend to express common mutations and translocations, such as PRDM1 truncations or homozygous deletions only seen in the ABC subtype, that have given insight into their behavior patterns (Pasqualucci et al., 2006; Mandelbaum et al., 2010; Schmitz et al., 2018). Identification of these defining pathways and association with a specific disease course, albeit in mice, further backs the strength of disease grouping in prognostics and treatment options (Mandelbaum et al., 2010; Miao et al., 2019). These cells show increased incidence of “chronic active” BCR signaling which is characterized by BCR clustering and autoreactive self-antigens as opposed to tonic signaling which is antigen independent and exhibits a lack of BCR clustering, as seen in GCB. MYD88 mutations conferring extranodal involvement, TNFAIP3 inactivation leading to uncontrollable NF-κB expression, and NOTCH1 mutations are seen almost exclusively in this subtype. These mutations however are not seen in a majority of cells expressing the ABC phenotype so they can hardly be called ABC defining traits, but are far more strongly associated with this subtype than the GCB or Unclassified types.

GCB cells are affected by the master regulator BCL6 similarly to ABC cells, but also are affected by more unique mutations. These possess an association with REL amplifications promoting lymphomagenesis, an almost exclusive presentation of t(14;18)(q32;q21) translocations leading to BCL2 activation and overexpression, and CREBBP mutation affecting the histone acetyltransferase domain leading to epigenetic dysregulation (Iqbal et al., 2004; Kusumoto et al., 2005; Kridel et al., 2012; Visco et al., 2013; Ennishi et al., 2017; Miao et al., 2019). The incidence of these mutations among all patients diagnosed with GCB DLBCL is relatively low and again can hardly be called defining to the disease type. The presence of these mutations in a GCB DLBCL and the association of GCB type with superior response to first line R-CHOP therapy supports the somewhat obvious notion that different (dysregulated) pathways respond differently, or not at all, to a given treatment.

One of the biggest problems with the accepted stratification of DLBCL is the disparity in treatment response even in the presence of seemingly identical focal mutations in both ABC and GCB, such as TP53 deletion or MYC mutations (Jia et al., 2012; Xu-Monette et al., 2012; Cao et al., 2016; Xu-Monette et al., 2016). This observation coupled with the vast number of possible mutations suggests not that we need groups based on individual pathway alterations, but the need for grouping based on sets of mutations that can be found together and that can be targeted therapeutically (Mansouri et al., 2022).

A classification system developed by Schmitz et al. (2018) has sought to link certain groupings of mutations with disease course, severity, and response to traditional R-CHOP therapy as well as suggest other potential therapies. Their view of genetic anomalies was not to view each mutation as an independent and unrelated event, but to try and group mutations that commonly occurred together and characterized a distinct disease course. Independent mutations would be nearly impossible to keep track of and treat individually at this stage in our knowledge and practice of medicine, so groupings like these encompassing multiple class defining mutations could prove to be actionable. The four groups of DLBCL they established through use of their algorithm were “MCD” defined by MYD88 and CD79B mutations, “BN2” defined by BCL6 fusions and NOTCH2 mutations, “N1” defined by NOTCH1 mutations, and “EZB” defined by EZH2 and BCL2 translocations. ABC cells in the MCD category were observed to have a superior response to ibrutinib, which halts B-cell proliferation through action as a Bruton’s tyrosine kinase (BTK) inhibitor, supporting the notion that better characterization of genetic phenomena and heterogeneity can lead to more effective and targeted treatment (Shaffer et al., 2006; Puente et al., 2015; Chapuy et al., 2016). Mutations found more commonly in ABC or GCB subtypes respectively further add defining features and explanation to their course, such as N1 subtype appearing in ABC 95% of the time, or the observed co-occurrence of EZH2 mutations with BCL2 translocations in GCB type lymphomas (Figure 1B) (Miao et al., 2019). The newly defined subtypes also observed significant progression-free survival (PFS) differences, with best outcomes going to BN2 and EZB types (Schmitz et al., 2018). Interestingly these subtypes, BN2 and EZB, were most commonly seen in the current GCB classification which is already accepted as having superior response and survival rate to ABC type malignancies (Cerami et al., 2012; Gao et al., 2013; Valls et al., 2017; Schmitz et al., 2018). The alignment between the potential new classification types and the currently accepted system adds a layer of confidence in exploring the subtypes proposed by Schmitz et al. in terms of prognostic indication, and development of treatments targeted at the pathways identified in their algorithm.

Chapuy et al. have developed another classification system through use of whole exome sequencing (WES) that divides DLBCL cells into C1, C2, C3, C4, or C5 depending on pattern of gene expression with defining genetic drivers, or C0 if a genetic driver could not be identified (Chapuy et al., 2018). Cluster 5 exhibited a consistent 18q gain, and is notable because 8 of the 9 patients in the Chapuy sample that had testicular involvement fell into the C5 cluster and 1 of 2 patients in the sample with CNS involvement fell into this cluster (Wright et al., 2003; Monti et al., 2005). This correlation is exciting for two reasons, first it shows a relation between disease course and genetic drivers in DLBCL which has the potential to aid in targeted screening for patients with identified mutations (e.g., 18q deletion) and in selecting more appropriate therapies. Secondarily the C5 group displaying increased extranodal involvement is significant because genes observed in the C5 group (e.g., MYD88) overlap heavily with the genes observed in the Schmitz et al. subgroup MCD, where extranodal involvement was also noted to be significant (Table 1). While the grouping of genes is slightly different between MCD and C5, the overlap and mutually identified association with specific disease course emphasizes the utility of being able to subtype DLBCL beyond what is currently used. Subtype C1 shared alterations in certain pathways (e.g., NOTCH2) with low grade marginal zones lymphomas, and alterations in other NOTCH2 and BCL6 pathways were defining characteristics of this group (Li and Durbin, 2009; Chapuy et al., 2013; Scott et al., 2014; Chapuy et al., 2016; Staiger et al., 2017; Chapuy et al., 2018; Papageorgiou et al., 2021). C3 which was characterized by BCL2 and chromatin modifier mutations, C4 was defined by mutations in four linker and four core histone genes, and these two pathways are mentioned together because they both represent subtypes of GCB type DLBCL (Chapuy et al., 2018). These subtypes are of interventional significance because they both alter the function of common pathways such as PI3K, but do so through different mechanisms (Chapuy et al., 2018). This is yet another example of why therapies must be tailored to the underlying mechanism of disease state, not just the presentation of disease. C2 was defined by markers including TP53 mutation and loss of CDKN2A and RB1 which alter chromosomal stability and cell cycle (Chapuy et al., 2018). Cluster zero (C0) lacked any defining characteristics or identifiable genetic homogeneity and represents a significant lack of understanding in disease pathology (Chapuy et al., 2018).

Research conducted by Lacy et al. (2020) sought to investigate their own set of subgroups using methods “potentially applicable in routine clinical medicine” and came up with 5 distinct groups. Their study aimed not only to establish groups with potentially workable mutations, but also to compare overlap between their groups to subtypes identified in studies Schmitz et al. and Chapuy et al. (2018) (Table 1). The first group, “MYD88” cluster, was defined by MYD88 mutation among others and contained the majority of observed primary CNS lymphomas and primary testicular lymphomas, similarly to MCD and C5 groups (Schmitz et al., 2018; Lacy et al., 2020). The “BCL2” group predominantly had characteristic t(14;18) translocation and other mutations in BCL2 pathways (Lacy et al., 2020). “SOCS1/SGK1” had mutations common to primary mediastinal B-cell lymphoma, and was observed to represent a subdivision of the C4 cluster described by Chapuy et al. (2018) (Lacy et al., 2020). The “TET2/SGK1” was largely GCB in origin and had characteristic mutations including TET2, SGK1, and KRAS, and was postulated to represent another subdivision of the C4 cluster (Chapuy et al., 2018). The final subtype described here which corresponded to the C1 subtype was the “NOTCH2” subtype which included mutations in NOTCH2, BCL10, CD70, and showed a strong correlation between NOTCH2 mutation and BCL6 rearrangement (Chapuy et al., 2018; Schmitz et al., 2018; Lacy et al., 2020). These subtypes seem to provide some prognostic ability with 5-year OS rates for MYD88, SOCS1/SGK1, BCL2, TET2/SGK1, and NOTCH2 groups observed at 42.0%, 64.9%, 62.5%, 60.1%, and 48.1% respectively (Lacy et al., 2020). This study demonstrated significance not only for itself, but helped cement the significance of studies conducted by Schmitz et al. and Chapuy et al. stemming from the overlap of their respective subtypes in terms of genetic anomaly identified and observed disease course, especially in the context of different algorithms and research parameters utilized between the studies.

Another key classification system using an algorithm referred to as “LymphGen” developed by Wright et al. (2020) intended on developing a more clinically useful stratification system based partially on work done by Schmitz et al. and Chapuy et al. This algorithm again recognizes genetic “constellations” rather than individual abnormalities and divides patients into 7 groups based on the prevalence of defined features. These groups are “MCD” characterized by BCR-dependent NF-κB immune evasion, “N1” characterized by NOTCH1 signaling and altered B cell differentiation, “A53” characterized by TP53 inactivation and aneuploidy, “BN2” characterized by NOTCH2 signaling with BCR dependent NF-κB immune evasion and a loss of CD70, “ST2” characterized by JAK/STAT3 signaling with NF-κB activation, and EZB which was further subdivided as being MYC+/− (“EZB-MYC+” and “EZB-MYC–“) and had chromatin modification conferring anti-apoptosis as well as PI3 kinase signaling and S1PR2-GNA13 inactivation (Wright et al., 2020). The LymphGen algorithm, using these criteria among other genetic markers, used genetic information gathered from malignant cells to then score the cells on the presence of these various mutations and assign them to the appropriate group based on assigned confidence intervals (Wright et al., 2020). The benefit to this algorithm was the ability to not only define subtype based on presence of these traits, but also to identify cells that had a probability of being part of a core, extended or genetically composite group where probability of belonging to a subtype was >90%, 50%–90%, or if the cell was a core member of more than one subtype, respectively (Wright et al., 2020). Using the algorithm, 63.1% of the cohort was able to be classified, greater than the 46.6% classified by Schmitz et al. (Wright et al., 2020). This is an especially high number when considering that to fall into one of the 7 subtypes with acceptable confidence for the algorithm, cells must acquire multiple mutations that seem as though they statistically should not occur together as often as they do if they were independent of each other. The ability to group these cells together may stem from a founder effect where a cell acquires an initial genetic mutation that may be relatively more common, and only certain secondary mutations confer continued survival for the cell. MYC overexpression would normally lead to cell death if not also paired with a BCL2 translocation that prevents cell death (Evan et al., 1992). A sort of natural selection such as this confers the ability of these algorithms to become of clinical use in the near future since these mutations likely do not occur in isolation (e.g., BCL2 and MYC mutations codependency), but are dependent on each other for the survival of the cell inextricably linking the altered pathways.

BCR signaling is involved in regulation of B cell survival, development, and differentiation, and can be chronic active or tonic in DLBCL, and both overexpression and overactivation are implicated in lymphomagenesis (Rawlings et al., 2017). Chronic signaling resembles antigen-dependent (autoreactive self-antigens) active BCR signaling in non-malignant B cells and is characterized by BCR clustering (Davis et al., 2010; Young and Staudt, 2013; Young et al., 2015; Havranek et al., 2017). Tonic BCR signaling is antigen-independent and clustering is not observed (Davis et al., 2010). ABC cells are characterized by chronic active BCR signaling, GCB DLBCL display tonic signaling (Davis et al., 2010; Havranek et al., 2017). During normal signaling after the BCR is bound by an appropriate ligand, CD79A and CD79B form a heterodimer and following dual phosphorylation of the intracellular immunotyrosine-based action motifs (ITAMs) of CD79A/CD79B, SYK kinase is recruited and activated which then activates BTK (Bruton’s tyrosine kinase) which leads to downstream activation of BCR signaling, notably mTOR and NF-κB (Miao et al., 2019). Mutations in any part of this pathway can potentially be problematic and lead to overactivation, such as loss of negative feedback ITAM mutation of CD79B which is detected in near 20% of ABC DLBCL cases (Davis et al., 2010). B cell receptors can be positively regulated by mutation or amplification of CD79B and CD79A, and negatively regulated by inhibitors including LAPTM5, LYN, PTPN6, GRB2, PRKCD, DGKZ, SLA, and MAP4K1 (Lenz et al., 2008a; Lam et al., 2008; Affymetrix® White Paper, 2009; Dobin et al., 2013; Anders et al., 2015; Seshan, 2017; NCI Genomic Data Commons, 2016). Loss of function of negative regulators of BCR signaling leads to unchecked activation, or a loss of negative feedback, of the BCR and was present in 38.5% of cases of DLBCL (Schmitz et al., 2018). Loss of function of negative regulators was more prevalent in MYD88 with CD79A/CD79B activating mutations, than in MYD88 lacking CD79A/CD79B alterations (56% vs 36.4%) which is of potential clinical utility because aggressive lymphomas with MYD88 ^L265P and CD79B mutations have a response to ibrutinib (Bruton’s tyrosine kinase is downstream of BCR) and presumably have chronic active BCR signaling (Shaffer et al., 2006; Puente et al., 2015; Chapuy et al., 2016; Schmitz et al., 2018). The most common mutation affecting BCR and TLR signaling is MYD88, 18%–27% of cases, which directly affects TLR signaling and indirectly influences BCR signaling because MYD88, TLR9, and BCR form a multiprotein supercomplex which leads to promotion of downstream NF-κB and mTOR activation (Phelan et al., 2018).

PI3K can indirectly activate NF-κB pathway and was genetically altered in 34.3% of cases of DLBCL, and is also able to directly activate mTOR mechanisms (Kent, 2002). Activation of mTOR inappropriately promotes cell proliferation and metabolism that contributes to tumor initiation and progression (Tian et al., 2019). Normally, activation through the BCR or CD19 leads to activation of the PIK3CD/PIK3CA heterodimer (BCR does this indirectly through intermediate activation of PIK3AP1), which goes on to activate PIP3 leading to activation of PDPK1, then activation of an AKT1/AKT2 heterodimer, and final activation of mTOR (Schmitz et al., 2018; Miao et al., 2019). Activating events involving PI3K signaling subunits (PIK3CA, PIK3CD, PIK3AP1, PDK1, AKT1/2) can lead to downstream AKT activation (Miao et al., 2019). Activation of MIR17HG which functions to inhibit PTEN, a negative regulator of PIP3, also leads to overactivation of this pathway and overexpression of mTOR (Miao et al., 2019). Inactivating mutations of negative PIP3 regulators PTEN and INPP5D are also seen in up to 15% and 10% of cases respectively and lead to unchecked mTOR expression (Schmitz et al., 2018). BCR co-receptor CD19 and the BCR itself (through SYK kinase) are able to activate PI3K signaling, which leads to activation of AKT which activates downstream mTOR promoting cell survival, again showing the large role BCR signaling plays in promotion of DLBCL (Uddin et al., 2006; Young and Staudt, 2013). Activating mutations of PI3K subunits (PIK3CA amplification/activating mutation) are identified in 6% of ABC DLBCL but not GCB, others (PTEN deletion) are present in both ABC and GCB (9%–11%) (Lenz et al., 2008a; Pfeifer et al., 2013; Chapuy et al., 2018; Schmitz et al., 2018; Wang et al., 2018).

Normally, BCR stimulation caused by antigen binding activates BTK signaling through SYK activation, which activates PLCλ2 and PKCβ, PKCβ then phosphorylates CARD11 which recruits BCL10 and MALT1 to form a complex (CBM complex) that inactivates negative regulator CYLD/SPATA2 complex and inactivates RELB (Schmitz et al., 2018). ZC3H12A is a more independent regulator of NF-κB pathway-dependent transcripts and enhances mRNA decay of anti-apoptotic gene transcripts including BCL2L1, BCL2A1, RELB, BIRC3, and BCL3 (Skalniak et al., 2009; Lu et al., 2016). Inactivating mutations of ZC3H12A are seen in up to 10% of cases, the consequence of which is anti-apoptotic and pro-lymphomagenesis (Skalniak et al., 2009; Lu et al., 2016; Schmitz et al., 2018). Failure of the NF-κB pathway to produce adequate IL-1β, which ZC3H12A is dependent on for activation, may also lead to inadequate mRNA degradation and anti-apoptotic characteristics (Skalniak et al., 2009). Mutations that cause overactivation of BCR signaling such as activating mutations of CD79A/CD79B or SYK which overstimulate BTK/PLCG2 causing activation of PRKCB and the CBM complex lead to an overactive NF-κB pathway (Schmitz et al., 2018). CARD11 mutations, which occur in both ABC and GCB type, impair auto-inhibition seen in wild type proteins which lead to continued activation of NF-κB (Lenz et al., 2008b; Lamason et al., 2010; Wilson et al., 2012; Bohers et al., 2014; Schmitz et al., 2018). Inactivating mutations are also seen in the negative regulators of the CBM complex themselves, including inactivation of CYLD/SPATA2 complex which functions as the inhibitor of the CBM complex in a negative feedback loop (Schmitz et al., 2018). Inactivation of negative regulators of RELB is also seen in up to 15% of cases, specifically inactivation of the TRAF2/3 complex, and overactivation of RELB is thought to indicate dismal outcome after immunochemotherapy because RELB confers DLBCL cell resistance to DNA damage induced apoptosis, preventing genotoxic agent doxorubicin from having the desired effect (Schmitz et al., 2018; Eluard et al., 2022). Negative regulators of inactivation signaling enzymes and adaptors that promote BCR-dependent NF-kB activation are aberrant in 44.9% of cases (Schmitz et al., 2018). 66.2% of cases also had mutations in other regulators of NF-κB such as TLR2 and ZC3H12A which negatively regulate the stability of NF-κB messenger RNA (mRNA) (Nicorici et al., 2014). In the BN2 subtype 2 components of BCR-dependent NF-κB pathway were altered in 47% of cases, protein kinase C beta (PKCB) and BCL10 (Schmitz et al., 2018). Signatures of BCR-dependent NF-κB activation were highest in MCD and BN2 (Schmitz et al., 2018).

NF-κB signaling may also be stimulated through activation of the IKBKG/IKBKB complex, which is only partially dependent on the BCR pathway and may be activated through various means (Schmitz et al., 2018). Activating mutations of positive regulators, TLR2 and MYD88, or inactivation of negative regulators TNIP1/TNFAIP3, result in the ability of IκB kinase (IKBKG/IKBKB) to inhibit the NFKBIA/NFKBIE complex (Schmitz et al., 2018; Miao et al., 2019; Ma and Malynn, 202012). Inhibition of this complex causes release of p65/p50 and REL pathways, which may also adopt activating mutations themselves, and final overexpression of NF-κB expression (Schmitz et al., 2018; Miao et al., 2019). Genetic alterations of NF-κB negative regulators were a prominent feature of subtype BN2, those affecting negative regulators TNFAIP3 or TNIP1 were found in 55% (Schmitz et al., 2018). Mutations in positive regulator MYD88 are also a defining trait of the MCD subtype and are a prominent source of gene overexpression (Schmitz et al., 2018).

Toll-like receptor 2 (TLR2) signaling in its standard state is mediated by MYD88, an adapter protein which assists in signaling, in complex with IRAK1/4 (Ngo et al., 2011). Mutation of MYD88 promotes assembly of a complex composed of IRAK1 and IRAK4 which enhances IRAK4 kinase activity and IRAK1 phosphorylation. Hyperphosphorylated IRAK1 causes activation of TRAF6, which activates TAK1, which can then accomplish downstream NF-κB and JAK/STAT signaling through the IκB kinase pathway (Ngo et al., 2011; Schmitz et al., 2018; Miao et al., 2019). Activating mutations of TLR2, MYD88, and TRAF6 are observed and can stimulate this pathway in absence of a proper TLR ligand (Schmitz et al., 2018). Activating mutations of MYD88 increase activity of both NF-κB and JAK/STAT pathways (Rosenquist et al., 2017). Inactivating mutations of negative regulators UBE2O and TNFAIP3, which normally inhibit TRAF6, are also observed to cause overstimulation of downstream NF-κB pathway (Miao et al., 2019).

In healthy B cells, apoptosis is induced through a lack of affinity of BCL2 for a specific antigen, so constitutive BCL2 activation through mutation would result in B cells that can avoid apoptotic programs in the absence of proper antigen recognition (Miao et al., 2019). Various BCL2 mutations occur and are noted in various DLBCL subtypes, such as the t(14;18)(q32;q21) translocation seen in 34%–44% of GCB DLBCL (Iqbal et al., 2004; Visco et al., 2013; Ennishi et al., 2017). Translocations such as this move BCL2 near genes that cause overactivation, or constitutive activation of BCL2 and promote survival (Kridel et al., 2012). Somatic hypermutation involving promoter and coding regions of BCL2 is seen in about 35% of DLBCL cases, with the majority being in the GCB subtype (Schuetz et al., 2012). These two examples indicate that while activation/mutation of BCL2 is common across many DLBCL’s, the root cause is not the same and may drive the need for multiple approaches to treating the same faulty pathway. Different mutations also result in differential response to BCL2 inhibitors, which is a consideration in measuring response to BCL2 inhibitors (Schmitz et al., 2018). Overactivation of other BCL2 family members such as BCL2L1 and MCL1 can also impair intrinsic apoptotic pathways and lead to continued cell survival and proliferation (Schmitz et al., 2018; Miao et al., 2019).

EZH2 is an important mediator of negative transcriptional activity, achieved through trimethylation of Lys27 of histone H3 subunit, referred to as H3K27 (Velichutina et al., 2010; Beguelin et al., 2013; Caganova et al., 2013). Overactivation of EZH2 leads to excessive activation of cell cycle regulators and promoters of plasma cell differentiation, such as CDKN1A, CDKN1B, CDKN2A, PRDM1, IRF4, or XBP1 (Miao et al., 2019). These problems culminate in defective germinal center formation in GCB cells, cells that can proliferate unchecked by the cell cycle regulators, protection from AID-dependent genotoxic damage-induced apoptosis, and restricted differentiation (Velichutina et al., 2010; Beguelin et al., 2013; Caganova et al., 2013). EZH2 mutation alone is not enough to create an environment conducive to the development of DLBCL, however in mice it has been shown that EZH2 mutation coupled with overexpression of BCL2 may be able to propagate the development of DLBCL (Cattoretti et al., 2005; Miao et al., 2019).

KMT2D is a histone monomethyltransferase responsible for regulation of transcription of tumor suppressor genes such as TNFAIP3, SOCS3, or TNFRSF14, so inactivation of this gene will lead to decreased tumor suppressor activity (Ortega-Molina et al., 2015; Miao et al., 2019). Nearly 30% of DLBCLs show mutation in this gene, commonly a non-sense or frameshift, but some cases of DLBCL show decreased KMT2D activity in the absence of mutation indicating other epigenetic regulation may be relevant (Morin et al., 2011; Ortega-Molina et al., 2015; Schmitz et al., 2018). KMT2D inactivation is also implicated in disruption of cell cycle regulators CDK6 and BCL2, which promote malignant cell survival (Zhang et al., 2015).

Among multiple histone lysine acetylation sites, H3K27 acetylation is related to active transcription while deacetylation represses transcription. EP300 and CREBBP are involved in H3K27 acetylation to promote transcription of tumor suppressor genes such as PRDM1, IRF4, CIITA, CD74, or HLADR, as well as acetylation of BCL6 and p53 which results in inhibition and activation of transcription respectively (Miao et al., 2019). CREBBP mutation reduces expression of these genes essential to plasma cell differentiation and immune responses against lymphomagenesis, which can be found in about 20% of patients with DLBCL and more commonly in the GCB than ABC subtype (Pasqualucci et al., 2011a; Lohr et al., 2012). CREBBP mutations have been observed in mice to promote substantial increases in the number of germinal center B cells which promotes development of MYC-driven lymphoma (Hashwah et al., 2017). Deficiencies in CREBBP also reduce expression of genes responsible for germinal center exit, antigen presentation and immune response, promoting lymphomagenesis (Jiang et al., 2017). EP300 is mutated in roughly 10% of DLBCLs of both ABC and GCB types, and effects are similar phenotypically to CREBBP mutations (Pasqualucci et al., 2011b).

NOTCH genes (NOTCH1 and NOTCH2) code for a series of receptors involved in specialization of cells, cell growth, differentiation, and apoptosis (Notch1 Gene MedlinePlus, 2015). Mutations in NOTCH1 are a defining characteristic of the N1 subtype, and NOTCH2 mutations in combination with BCL6 fusions are defining of the BN2 subtype (Schmitz et al., 2018). Mutations in NOTCH1/2 signaling can be activating type in the NOTCH receptor itself or activating mutations of downstream intracellular messengers such as PEST, which can activate nuclear gene transcription (Lee et al., 2009; Arcaini et al., 2015). Inactivating mutations of SPEN and DTX1, negative regulators of NOTCH signaled transcription, could also lead to overexpression of genes (Schmitz et al., 2018; Miao et al., 2019).

GCB cells under normal conditions should exist only within appropriate germinal centers but are found in circulation and extranodal sites in DLBCL (Montesinos-Rongen et al., 2011; Pham-Ledard et al., 2012; Pham-Ledard et al., 2014a; Pham-Ledard et al., 2014b; Kraan et al., 2014; Oishi et al., 2015; Chapuy et al., 2016; Fukumura et al., 2016; Taniguchi et al., 2016; Cao et al., 2017; Franco et al., 2017; Zheng et al., 2017; Zhou et al., 2018; Miao et al., 2019). Migration of these cells can likely be traced back to inactivation or under-activation of the sphingosine 1-phosphate receptor-2 (S1PR2) (Green et al., 2011; Muppidi et al., 2014; Miao et al., 2019). Under malignant conditions, S1PR2 is inactivated, resulting in a failure of activation of downstream GNA13, which then is unable to activate ARGHEF1, which then cannot activate RHOA, causing a lack of inhibition of cell migration (Muppidi et al., 2014; Rosenquist et al., 2017; Miao et al., 2019). GNA13 and ARHGEF1 normally encode for mediators that control the growth of GCB cells and confine them to germinal centers, so a lack of these mediator’s results in their systemic distribution and uncontrolled migration (Morin et al., 2011; Muppidi et al., 2014). The homing pathway encoded by GNA13 and ARHGEF1 is disrupted in 38% of EZB subtype cases, showing the importance of this specific pathway (Schmitz et al., 2018).

BCL6 fusions are commonly associated with NOTCH2 mutations, which make up the defining characteristics of the BN2 subtype (Schmitz et al., 2018). BCL6 in its normal functional capacity is responsible for recruiting histone deacetylase 3 (HDAC3) which deacetylates BCL6-bound transcriptional enhancers, rendering them inaccessible for transcription (Hatzi et al., 2013; Miao et al., 2019). Alterations in the first-noncoding exon of BCL6 also interfere with negative autoregulation, further increasing activity of the gene (Miao et al., 2019). BCL6 regulates plasma cell differentiation (IRF4, PRDM1), cell migration (S1PR1), DNA damage response (ATR, CHEK1), the cell cycle (CDKN1A, CDKN1B), and cell death (TP53) (Miao et al., 2019). Activating mutations of BCL6 (or activators such as MEF2B) or inactivating mutations of BCL6 inhibitors (EP300, CREBBP, FBXO11) lead to suppression of these processes previously mentioned, and promotion of germinal center formation and disruption of plasma cell formation (Cattoretti et al., 2005; Pasqualucci et al., 2011b; Miao et al., 2019).

p53, encoded for by TP53, plays a critical role in activation of genes involved in regulation of cell death and cell cycle progression, including BAX and CDKN1A (Miao et al., 2019). Inactivation of p53 through deletion of TP53 is seen in 8%–24% of DLCBL (Jardin et al., 2010) but inactivation can occur through numerous other mechanisms. p14^ARF (CDKN2A) normally inhibits MDM2, preventing inactivation of p53 by MDM2, but p14^ARF can develop an inactivating mutation leading to constitutive inhibition of p53 by MDM2 (Schmitz et al., 2018; Miao et al., 2019; Lenz et al., 2008a; Ma and Malynn, 202012). Activating mutations of MDM2 or MDM4 (another inhibitor of p53) can also lead to continued inactivation of p53, and failure of CDKN1A/BAX mRNA transcription (Miao et al., 2019). Inactivation of p53 also causes failure of proper cell cycle progression (limited BTG1, BTG2, CDKN1A expression), failure of apoptotic pathways (limited FAS, BCL2 expression), and failure of adequate DNA repair mechanisms (limited BRCA2, ATM, PRKDC expression) (Rosenquist et al., 2017).

MYC is a proto-oncogene at the center of multiple second messenger pathways and regulates transcription of genes involved in cell growth and proliferation, apoptosis, metabolism, DNA replication, and protein biosynthesis (Dang, 2012; Karube and Campo, 2015). Cells with gene expression characteristic of MYC, and characteristic of proliferation, are highly associated with the MCD and BN2 subtypes (Schmitz et al., 2018). DLBCL with rearrangements involving MYC and BCL2/BCL6, which upregulate MYC gene expression, are referred to as double hit or triple hit lymphomas, and are associated with inferior progression free survival and overall survival in patients receiving traditional R-CHOP therapy (Hummel et al., 2006; Savage et al., 2009; Valera et al., 2013; Rosenquist et al., 2017). Interestingly however, MYC rearrangements are not predictive of poorer prognosis in patients who receive the DA-EPOCH-R regimen (etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin, rituximab) suggesting the possible targetability of this pathway (Lai et al., 2018). Another study found MYC partner to be prognostically significant, with IGH-MYC translocations having the worst prognosis of all MYC translocations, likely because IGH-MYC translocations place MYC adjacent to immunoglobulin enhancers which leads to constitutive MYC expression (Copie-Bergman et al., 2015; Karube and Campo, 2015). One of the causes of MYC translocations with IGH or BCL6 is thought to be mediated by activation-induced cytidine deaminase (AID), which normally is responsible for somatic hypermutation and class switch recombination, but can also target and create breaks in BCL6 and MYC (Shen et al., 1998; Miao et al., 2019). Mutations resulting from incorrect AID-related hypermutation, especially in regions not coding for immunoglobulin genes, has been reported in more than half of DLBCL patients (Gordon et al., 2003; Deutsch et al., 2007; Miao et al., 2019). In addition to activating MYC translocations leading to downstream gene upregulation, inactivating mutations of the negative regulator MAX-gene associated protein (MGA) are also implicated in improper MYC expression (Miao et al., 2019). Not only are the MYC aberrations themselves relevant clinically as indicated by trials with DA-EPOCH-R protocol, but being able to further subtype these based on MYC partner or mutation location may provide further prognostic significance (Copie-Bergman et al., 2015; Karube and Campo, 2015; Xu-Monette et al., 2016).

Immune editing and evasion of immune surveillance is a hallmark of the DLBCL, especially the MCD subtype and therefore the ABC type, with 76% of MCD acquiring mutation or deletion of HLA-A, HLA-B, or HLA-C (Chang et al., 2016). Inactivating alterations to MHC class I molecules, through augmentation or deletion of components HLA-A/B/C or β2 microglobulin (B2M) is common among DLBCL in both GCB and ABC types, and results in failed expression of surface MHC class I and subsequent failure to activate cytotoxic CD8⁺ T cells (Challa-Malladi et al., 2011). GCB types occasionally (10% of cases) also display disruptions in the MHC class II molecules, and thus failure to activate CD4⁺ T cells, through mutations in HLA-DMA/HLA-DMB or inactivating mutations in the MHC class II transactivator CIITA (Steimle et al., 1994; Schmitz et al., 2018). Natural killer (NK) cells display the CD2 receptor and are activated by the CD58 ligand, so mutations or deletions in CD58 (21% of all DLBCL and in ABC 68% of the time) cause loss of this extracellular ligand and subsequent failure of NK-mediated cytolysis (Miao et al., 2019). CD4⁺ and CD8⁺ T cells also display the CD2 receptor, and activation would also be affected by loss of the CD58 ligand on the tumor cell (Miao et al., 2019). CD274/PDCD1LG2 (PD-L1/PD-L2) gains, amplifications, and translocations are another mechanism by which DLBCL evades destruction by T cells, because binding of this ligand to PD-1 receptors on CD8⁺/CD4⁺ T cells prevents activation (Georgiou et al., 2016). Another deleterious mutation of DLBCL cells that can cause failure to activate immune cells is a loss of CD70, which would normally bind to CD27 on the CD4⁺ and/or CD8⁺ T cells to cause activation.