2.6.5. Diffuse large B cell lymphoma, leg type

It manifests as red or bluish (violaceous) nodules or tumors on one or both legs, usually below the knee; 10–15% develop outside of the lower extremities. Contrary to other cutaneous B cell lymphomas, these tumors frequently disseminate to extracutaneous sites and pursue an aggressive course. MYD88 L265P mutations are seen in ~50% of cases.

#### 2.6.6. Diffuse large B cell lymphoma associated with chronic inflammation

Also known as pyothorax-associated DLBCL, it usually develops in patients with a long standing history of pyothorax; however it may also arise at other sites with chronic inflammation [14]. It is seen worldwide but is more common in Japan and China. Clinically, it is an aggressive tumor. These tumors are almost always EBV-positive and are believed to arise from EBV-infected post germinal center B cells. The pattern of EBV gene expression present in this type of lymphoma (LMPI and EBNA2 positivity) suggests the role of local immunosuppression within the sites of chronic inflammation.

#### 2.6.7. Lymphomatoid granulomatosis

This is also an EBV-positive large B cell lymphoma with a T cell-rich background which is clinically and pathologically distinct from DLBCL [15]. The usual manifestations are cough and fever (60%), rash/nodules (40%), malaise and weight loss (35%), neurological abnormalities and dyspnea (30%), or chest pain (15%) [16]. Extranodal involvement is common. The lungs are commonly affected. Other commonly involved sites include kidney, liver, brain, and skin. Lymph nodes and splenic involvement is rare. Histologically, the infiltrates are either angiocentric or angioinvasive. Often extensive necrosis is present with only a few atypical large B cells in a pleomorphic background of lymphocytes, plasma cells, and histiocytes. The large atypical B cells represent the neoplastic component and show evidence of EBV infection with in situ hybridization. Pulmonary nodules exhibit central necrosis and cavitation.

#### 2.6.8. EBV-positive DLBCL, NOS

EBV-positive DLBCL, NOS is a variant of DLBCL that replaced the entity, EBV-positive DLBCL of the elderly and was added in the 2016 WHO classification. It may affect persons of all ages [17–21]. This is seen in patients without known immunodeficiency or prior lymphoma. It is seen most commonly in Asian countries where it accounts for 8–10% of DLBCL among patients without a known immunodeficiency. The majority of patients present with extranodal disease, with or without nodal involvement. While the initial reports were in adults >50 years old, this entity has been increasingly recognized in younger patients [17, 22].

However, it was not superior in predicting the outcome. In a study on 108 patients, it was shown that Hans and Choi algorithms predicted OS and PFS significantly better than the Tally method [33]. Other algorithms use combinations of other markers (Muris et al.: BCL2, CD10, MUM1 [34]), (Natkunam et al.: LMO2 [35]), (Nyman et al. 50: MUM1, CD10, GCET1, MUM1, FOXP1,

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However, the utility of IHC methodology is also limited by its poor concordance to GEP, inferior accuracy and reproducibility and a lack of prognostic utility. IHC algorithms do not recognize the 10–15% of tumors and are not always reproducible [37]. Lymph2Cx is a 20-gene version of a Nanostring code set for a COO typing assay of DLBCL. This represents GEP like

Figure 4. Immunohistochemistry algorithms for the characterization of diffuse large B-cell lymphoma on the basis of cell of origin. (a) Hans algorithm; (b) Choi algorithm; (c) Nyman algorithm; (d) Visco-young algorithm; (e) Muris algorithm;

and (f) Tally algorithm.

LMO2 [36]) and have been described in detail in Figure 4.

#### 2.6.9. EBV-positive mucocutaneous ulcer

It is considered a provisional entity in the 2016 revision of the WHO classification. This is characterized by the presence of isolated circumscribed ulcerative lesions, typically affecting elderly individuals [23, 24]. Its association with immunosuppression is not clear. Usually, the oropharynx is affected but lesions may also occur in the skin or in the gastrointestinal tract. Histologically, a polymorphous inflammatory infiltrate mixed with scattered EBV-infected B cells is seen in the lesions, which frequently include cells resembling Hodgkin/Reed-Sternberg cells both morphologically and immunophenotypically. This entity is distinguished from Hodgkin lymphoma by its extranodal presentation and has a benign disease course which is characterized by frequent spontaneous regressions and its excellent response to conservative treatment.

#### 2.7. Molecular subtypes

As noted above, the classification of DLBCL NOS, into GCB vs. ABC subtypes is important for the prognostication. The prognosis of GCB-type DLBCL is considered to be better than ABC-type DLBCL. In the rituximab era the 5-year survival of GC type DLBCL is 87–92% as compared to 44% in the ABC-type DLBCL [7, 25]. Moreover, response to novel therapies may be different for the two subtypes. The classification into GCB- vs. ABC-type is best conducted by genomic expression profiling [26]. The DNA microarray is an effective tool to characterize the molecular features of DLBCL and specific genes associated with response to therapy. Though microarray GEP are gold standard for profiling of DLBCL to determine COO, they are expensive and not readily available. Moreover, they have poor flexibility and reproducibility in evaluating low quality RNA samples from formalin-fixed paraffin-embedded (FFPE) tissues and for high quality data, they require RNA extraction from the frozen tissues [27]. Thus their implementation in the routine clinical practice is limited [28]. IHC-based methods are rapid, cost effective and thus are widely used in the clinical practices. Different algorithms have been developed to improve the accuracy. These algorithms use different combinations of antibodies to identify germinal center or activated B cell-related proteins [4, 7, 29]. The relatively simple and most well-known is the Hans algorithm which is based upon the application of 3 antibodies, CD10, BCL6, IRF4/ MUM1 and has a reasonable correlation with the GEP [30]. Cases are considered positive if 30% or more of the tumor cells are stained with an antibody (CD10, BCL6, and MUM1). The overall concordance with gene expression array is 80%. The Choi algorithm added FOXP1 and GCET 1 to Hans algorithm and showed 93% concordance with GEP [25, 31]. A Tally classifier substituted BCL6 for the LMO2 antibody which predicted COO better than rest of the IHC algorithms [32]. However, it was not superior in predicting the outcome. In a study on 108 patients, it was shown that Hans and Choi algorithms predicted OS and PFS significantly better than the Tally method [33]. Other algorithms use combinations of other markers (Muris et al.: BCL2, CD10, MUM1 [34]), (Natkunam et al.: LMO2 [35]), (Nyman et al. 50: MUM1, CD10, GCET1, MUM1, FOXP1, LMO2 [36]) and have been described in detail in Figure 4.

2.6.8. EBV-positive DLBCL, NOS

46 Hematology - Latest Research and Clinical Advances

2.6.9. EBV-positive mucocutaneous ulcer

2.7. Molecular subtypes

EBV-positive DLBCL, NOS is a variant of DLBCL that replaced the entity, EBV-positive DLBCL of the elderly and was added in the 2016 WHO classification. It may affect persons of all ages [17–21]. This is seen in patients without known immunodeficiency or prior lymphoma. It is seen most commonly in Asian countries where it accounts for 8–10% of DLBCL among patients without a known immunodeficiency. The majority of patients present with extranodal disease, with or without nodal involvement. While the initial reports were in adults >50 years

It is considered a provisional entity in the 2016 revision of the WHO classification. This is characterized by the presence of isolated circumscribed ulcerative lesions, typically affecting elderly individuals [23, 24]. Its association with immunosuppression is not clear. Usually, the oropharynx is affected but lesions may also occur in the skin or in the gastrointestinal tract. Histologically, a polymorphous inflammatory infiltrate mixed with scattered EBV-infected B cells is seen in the lesions, which frequently include cells resembling Hodgkin/Reed-Sternberg cells both morphologically and immunophenotypically. This entity is distinguished from Hodgkin lymphoma by its extranodal presentation and has a benign disease course which is characterized by frequent spontaneous regressions and its excellent response to conservative treatment.

As noted above, the classification of DLBCL NOS, into GCB vs. ABC subtypes is important for the prognostication. The prognosis of GCB-type DLBCL is considered to be better than ABC-type DLBCL. In the rituximab era the 5-year survival of GC type DLBCL is 87–92% as compared to 44% in the ABC-type DLBCL [7, 25]. Moreover, response to novel therapies may be different for the two subtypes. The classification into GCB- vs. ABC-type is best conducted by genomic expression profiling [26]. The DNA microarray is an effective tool to characterize the molecular features of DLBCL and specific genes associated with response to therapy. Though microarray GEP are gold standard for profiling of DLBCL to determine COO, they are expensive and not readily available. Moreover, they have poor flexibility and reproducibility in evaluating low quality RNA samples from formalin-fixed paraffin-embedded (FFPE) tissues and for high quality data, they require RNA extraction from the frozen tissues [27]. Thus their implementation in the routine clinical practice is limited [28]. IHC-based methods are rapid, cost effective and thus are widely used in the clinical practices. Different algorithms have been developed to improve the accuracy. These algorithms use different combinations of antibodies to identify germinal center or activated B cell-related proteins [4, 7, 29]. The relatively simple and most well-known is the Hans algorithm which is based upon the application of 3 antibodies, CD10, BCL6, IRF4/ MUM1 and has a reasonable correlation with the GEP [30]. Cases are considered positive if 30% or more of the tumor cells are stained with an antibody (CD10, BCL6, and MUM1). The overall concordance with gene expression array is 80%. The Choi algorithm added FOXP1 and GCET 1 to Hans algorithm and showed 93% concordance with GEP [25, 31]. A Tally classifier substituted BCL6 for the LMO2 antibody which predicted COO better than rest of the IHC algorithms [32].

old, this entity has been increasingly recognized in younger patients [17, 22].

However, the utility of IHC methodology is also limited by its poor concordance to GEP, inferior accuracy and reproducibility and a lack of prognostic utility. IHC algorithms do not recognize the 10–15% of tumors and are not always reproducible [37]. Lymph2Cx is a 20-gene version of a Nanostring code set for a COO typing assay of DLBCL. This represents GEP like

Figure 4. Immunohistochemistry algorithms for the characterization of diffuse large B-cell lymphoma on the basis of cell of origin. (a) Hans algorithm; (b) Choi algorithm; (c) Nyman algorithm; (d) Visco-young algorithm; (e) Muris algorithm; and (f) Tally algorithm.

platform that can run on FFPE tissue. Twenty genes have been selected out of 93 candidate genes [38, 39] to identify COO using this platform. In NanoString technology, digitally colored code sets are attached to the sequence-specific probes to directly measure mRNA [28, 40]. This technique offers highly sensitive, quantitative and reproducible results on FFPE and frozen tissue samples. This requires a very small amount of RNA and covers a large number of genes enabling complex genetic analysis. Studies have demonstrated strong concordance between patient-matched frozen and FFPE materials. It showed 98% concordance for ABC/GCB and 95% in the unclassifiable cases when compared with GEP [38]. In a study on 82 patients, who were treated with R-CHOP the concordance rate between Lymph2Cx assay and Hans algorithm was 73.6%. The outcome of Lymph2Cx-defined ABC (77.1%) was significantly poor as compared to the GCB type (96.6%). On contrary, there was no difference in the outcome of two groups classified by the Hans algorithm [41].

3.3. Immunophenotype

and 6.2.

3.4. Workup

It is essential for the differentiation of various subtypes of DLBCL. This is established either by flow cytometry or IHC. Flow cytometry can be employed in determining bone marrow involvement [45] when PET/CT is not readily available for staging and in determining CNS involvement by CSF flow cytometry [46]. Immunophenotype findings are usually combined with morphologic findings to arrive at a diagnosis. Tumor cells in DLBCL generally express pan B cell antigens (CD19, CD20, CD22, and CD79a) as well as CD45. The typical immunophenotype is CD20+, CD45+, and CD3. The panel should include CD20, CD3, CD5, CD10, CD45, BCL2, BCL6, Ki-67, IRF4/MUM1, and MYC. 50–75% of tumors express surface and cytoplasmic monoclonal immunoglobulin (Ig). The proliferative fraction of cells is usually higher than 40% and may occasionally be >90%. CD5 positive tumors are associated with a more aggressive disease and a higher incidence of CNS involvement and a worse prognosis. CD10+ and BCL6+ indicates GCB lymphoma while MUM1+ indicates ABC lymphoma. The three most common translocations noted in DLBCL include MYC, BCL2 and BCL6. MYC is an oncogene involved in pathogenesis of aggressive lymphomas based on partner gene translocation. MYC protein is a transcription regulator for cellular proliferation acting on metabolic and angiogenic mechanism. Genetic translocation involving MYC are considered primary events in 5–15% of DLBCL [47] and in around 20% on first relapse [48]. In DLBCL frequently the partner gene is BCL-2 or to a lesser extent BCL-6 or both, in the so-called double-hit or triple-hit lymphomas. Overexpression of MYC protein can be tested with IHC which can occur independent of translocation in 30% of cases; however for confirmation of specific translocation FISH studies are required [49]. Both, overexpression and translocation confer adverse outcome as documented in different studies [50]. More information on this translocation and their effect on outcome is detailed in Sections 2.3

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Initial work up includes thorough physical examination with special attention to node bearing areas and evaluation of performance status (PS) and constitutional symptoms. Appropriate site for excisional/incisional biopsy should be earmarked as stated above. Laboratory assessments include complete blood count (CBC) with differential, complete metabolic profile (CMP), lactate dehydrogenase (LDH) and Beta-2 microglobulin. Additional tests including uric acid and phosphorus, in patients with high tumor burden. Hepatitis B virus (HBV) testing is also warranted as there is an increased risk of HBV reactivation in patients who may require Rituximab. Positron emission tomography (PET)/computed tomography (CT) scan is recommended for initial staging as upstaging can result in altered therapy. Also baseline PET/ CT is necessary to confirm the response on the post treatment PET scans. A systematic review and meta-analysis by Adams et al. showed that sensitivity and specificity of PET/CT for detection of bone marrow involvement ranged from 70.8 to 95.8% and from 99.0 to 100%, respectively [51]. There were 3.1% patients who were PET negative but had bone marrow involvement on bone marrow biopsy. On contrary 12.5% patients with negative bone marrow biopsies had marrow involvement on PET scan and PET/CT [51]. Bone marrow biopsy is not needed if the PET/CT is negative unless finding another concomitant lymphoma is important
