Chapman‐Fredricks, Jennifer R.

Background: Anaplastic large cell lymphomas represent a group of T-cell lymphomas that have long been broadly classified by the presence or absence of ALK fusion proteins (ALK+ or ALK−, respectively). However, recent discovery of extensive additional molecular heterogeneity has both promoted refinement of disease classification and uncovered new opportunities for biomarker-guided targeted therapy. In addition to recognition of a new genetic subtype, ALK− ALCL with DUSP22 rearrangement (R), a new molecular classification has been proposed based on the recent discovery of 2 overarching molecular types of ALCL, defined by the presence (Type I) or absence (Type II) of a gene expression signature highly enriched for JAK-STAT3 activation. BCL2 is a mitochondrial membrane protein that functions to inhibit the actions of pro-apoptotic proteins such as BAX and BAK and can be targeted clinically by BCL2 small molecule inhibitors. BCL2 has been reported to be expressed more frequently in ALK− ALCL than in ALK+ ALCL, but its expression in the context of current molecular findings is unknown. Methods: ALCLs were centrally reviewed and classified by current WHO/ICC criteria. BCL2 was performed using IHC and scored as positive if ≥30% of tumor cells showed staining. DUSP22-R was assessed by fluorescence in situ hybridization (FISH) using a breakapart probe set and a dual-color, dual-fusion (D) probe set for the most common DUSP22 translocation, t(6;7)(p25.3;q32.3). pSTAT3Y705 IHC, which is >90% accurate for Type I/II assignment based on gene expression, was performed and scored based on a previously validated cut-off of ≥30%. Results: We evaluated 217 ALCLs (148M/69F; age: mean, 57 y; range, 5-93 y), including 55 systemic ALK+ ALCLs, 127 systemic ALK− ALCLs, and 35 primary cutaneous (pc) ALCLs. Overall, 86/217 cases were positive for BCL2 (40%). BCL2 was positive in 67/127 ALK− ALCLs (53%) and 15/35 pcALCLs (43%; P=NS), but in only 4/51 ALK+ (7%; P<0.0001). DUSP22-R was present in 90 cases (63 ALK− ALCL and 27 pcALCL). BCL2 was positive in 57/90 cases with DUSP22-R (63%) compared to 29/127 without DUSP22-R (23%; P<0.0001). Among 85 cases with DUSP22-R and informative D-FISH testing, BCL2 was positive in 24/36 cases with t(6;7)(p25.3;q32.3) (67%) and 31/49 cases without t(6;7)(p25.3;q32.3) (63%; P=NS). Among 213 cases with informative pSTAT3Y705 staining, BCL2 was positive in 13/88 pSTAT3+ cases (Type I, 15%) and 70/125 pSTAT3− cases (Type II, 56%; P<0.0001). Conclusions: We identified a complex pattern of BCL2 expression across ALCLs that strongly correlates with a recently introduced molecular classification based on gene expression profiling. While our findings are in keeping with the previously reported low expression in ALK+ ALCL, we found that the higher expression in both systemic ALK− ALCL and pcALCL is particularly associated with DUSP22-R and the absence of pSTAT3Y705 expression (Type II ALCLs). The discovery of 2 overarching types of ALCL associated with the presence or absence JAK-STAT3 pathway activation represents a new conceptual framework for classifying ALCL and understanding its therapeutic vulnerabilities. Of note, previous data demonstrated that Type II ALCLs are enriched for epigenetic alterations and particularly overexpress the histone methyltransferase EZH2. Correlation between BCL2 expression and EZH2 expression also is observed in other lymphomas such as diffuse large B-cell lymphoma, where dual targeting with EZH2 and BCL2 inhibitors has been proposed. Thus, our findings provide further rationale for stratifying Type I and Type II ALCLs and identify BCL2 as a differentially expressed oncoprotein that might represent a target for precision therapy approaches.

Background: Anaplastic large cell lymphomas (ALCLs) represent a heterogeneous group of T-cell lymphomas that currently are classified by the presence or absence of ALK tyrosine kinase (TK) fusion genes (ALK+ or ALK−) and clinical presentation (systemic, cutaneous, or breast implant-associated). Two overarching molecular types of ALCL recently were discovered, defined by the presence (Type I) or absence (Type II) of a gene expression signature highly enriched for JAK-STAT3 activation. Fusions involving non-ALK TK genes occur in some ALK− cases, but the fusion landscape of ALCL remains incompletely characterized. Methods: Expert consensus pathology review was conducted in the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). RNAseq was performed and fusions were identified using FusionCatcher. Here, we focused on recurrent in-frame coding fusions. Previously unreported fusions were validated by RT-PCR. Type I/II was assigned using a previously validated gene expression-based model. Genes with adjusted (adj) P<0.05 were considered differentially expressed. Overall survival (OS) was assessed for systemic ALCL, when available. Results: We evaluated 379 ALCLs (229M/150F; mean age, 56 y). Of 199 candidate fusions (excluding reciprocal events), 28 were recurrent and passed quality metrics. At least 1 of these 28 fusions was present in 150 cases (40%). ALK fusions were present in 106 ALK+ ALCLs (all Type I; P<0.0001). Of these, NPM1::ALK was seen in 68/106 (64%). Alternate partners (X::ALK) included ATIC (N=24) and CTLC, COL1A2, MSN, MYH9, RNF213, SATB1, TFH, TPM3, and TRAF1 (1-3 cases each). X::ALK was associated with older age (mean, 52 y) than NPM1::ALK (32 y; P<0.0001) and showed relative overexpression of 49 genes, including multiple activators of small GTPases such as CGNL1 (FC, 5.6; Padj=2.4×10-6), SRGAP1, ALS2, DOCK1, and NCKAP1. ALK expression was similar in cases with NPM1::ALK and X::ALK and there was no significant difference in OS. Non-ALK TK fusions were seen in 17/273 ALK− cases (6%), including TYK2 (N=9); JAK2 (N=6); and ROS1 (N=2). All were Type I ALCLs (P<0.0001). ALK− cases with non-ALK TK fusions overexpressed 38 genes compared to ALK− cases without TK fusions, including cytokines involved in the IL17 signaling pathway such as CXCL6 (FC, 12.5; Padj=4.2×10-3), CXCL1, and CSF3. We then assessed the relationship between ALK− cases with non-ALK TK fusions and ALK+ cases by separately comparing each subset to ALK− cases without TK fusions. FC values for ALK− cases with non-ALK TK fusions were significantly correlated with FC values for ALK+ ALCLs over the set of expressed genes (R=0.54; P<0.0001). At a median follow-up of 32 months, 0/4 systemic ALCL patients with non-ALK TK fusions had died, while 30% of those with ALK− ALCL without TK fusions had died, but this was not statistically significant (P=0.26). The other 13 ALK− cases with non-ALK TK fusions were either localized ALCLs or did not have outcome data available. Of 20 TP63 fusions, 17 (85%) were TBL1XR1::TP63 and 3 were X::TP63. As previously reported, TP63 fusions were associated with poor OS (median OS, 10 months; not reached for other ALK− ALCLs; P=0.007). Four ALCLs had a novel NCL::UBTF fusion involving genes encoding the nucleolar proteins nucleolin and nucleolar (upstream binding) transcription factor-1. Four cases each had PARG::BMS1 and TNK1::GPS2 (the latter seen only in Type I ALCLs). Conclusions: This large consortium-based analysis of coding fusions further elucidates the molecular distinction between Type I and Type II ALCLs. Both ALK and non-ALK TK fusions were seen exclusively in Type I ALCLs, which we have shown previously are enriched for JAK-STAT3 pathway genes and correlate strongly with pSTAT3Y705 positivity by immunohistochemistry. These fusions were not identified in Type II ALCLs, which previous data suggest are associated with epigenetic alterations. ALK+ ALCLs with NPM1::ALK and X::ALK showed differences in gene expression, suggesting biological differences. Furthermore, ALCLs with non-ALK TK fusions shared gene expression features with ALK+ ALCL. Clinical fusion detection could enhance molecular classification of Type I and Type II ALCLs and may guide precision therapy.

Introduction: HIV-associated diffuse large B-cell lymphoma (HIV-DLBCL) is a significant complication in HIV-positive individuals, presenting unique clinical challenges and a poorer prognosis compared to patients with de novo DLBCL. Epstein-Barr Virus (EBV) status is a critical factor influencing the pathogenesis, clinical behavior, and therapeutic responses in these lymphomas. Plasmablastic lymphomas (PBL) have shared some overlapping genomic abnormalities with HIV-DLBCL including MYC rearrangements. This study aims to elucidate the differences in the genetic profiles and pathway activations between EBV(+) and EBV(-) HIV-DLBCL through comprehensive genomic profiling. Methods: Cases of DLBCL were identified in patients living with HIV from a multi-institute cooperative group. Cases of Burkitt lymphoma and PBL were excluded. We performed whole exome sequencing (WES) on 106 tumors of HIV-DLBCL and RNA sequencing on 39 tumors and mapped the reads to hg38 reference genome using BWA and STAR, respectively. EBV status of cases was determined by in situ hybridization and/or reads mapped on EBV genome in sequencing data. Somatic mutations were identified using variant callers (Strelka2, Mutect2) with WES data. For those mutated genes in COSMIC, allele frequency cutoff was set at 0.03. Mutations with an artifact score larger than 0.7 in SOBDetector and those located in segmental duplications were further removed. They were annotated with Ensembl Variant Effect Predictor, manually checked, and plotted with maftools. RNAseq read counts aligned to each gene were obtained by featureCounts and DEseq2 was used for differential expression (DE) analysis between EBV positive and negative groups. Pathway analysis with the DE genes was performed using GSEA. FISH analysis was performed using MYC, BCL2, and BCL6 break-apart probes. Results: There were 41 cases of EBV(+) HIV-DLBCL and 65 cases of EBV(-) HIV-DLBCL. FISH of EBV(+) HIV-DLBCL identified 42% (3/7) with MYC rearrangement (MYCr), none with BCL2 rearrangements (BCL2r) (0/6), and 33% (2/6) positive for BCL6 rearrangement (BCL6r) with 1 tumor having a MYCr/BCL6r. For EBV(-) HIV-DLBCL, there were 35% with a MYCr (6/17), 18% with BCL2r (2/11), and 27% with a BCL6r (3/11) with 2 tumors with MYCr/BCL6r, and 1 tumor with MYCr/BCL2r/BCL6r. The most frequent mutations seen in EBV(+) HIV-DLBCL were STAT3 (32%), DDX3X (22%), and TP53 (15%). For EBV(-) HIV-DLBCL, the most frequent mutations were KMT2D (25%), TP53 (23%), GNA13 (22%), and TET2 (22%). Pathways that were most commonly associated with EBV(+) HIV-DLBCL were JAK/STAT (42%) (STAT3, JAK1) and NF-kB (39%)(DDX3X, TNFAIP3) while EBV(-) HIV-DLBCL was associated with epigenetic modifiers (62%)(KMT2D, TET2, EP300), JAK/STAT (45%)(SOCS1, JAK3) and PI3K/mTOR (40%)(GNA13, MTOR). Significant disparities between EBV(+) and EBV(-) were KMT2D (24% vs 50%, P=0.0025), TET2 (10% vs 26%, P=0.008), SOCS1 (29% vs 39%, P=0.04), DDX3X (15% vs 5%, P=0.03), and GNA13 (5% vs 24%, P=0.001). RAS mutations (KRAS, NRAS) were infrequent in HIV-DLBCL (EBV(+), 12%; EBV(-), 6%), in contrast to prior studies of PBL. Gene expression profiling showed enrichment of MYC targets, oxidative phosphorylation, and the mTORC pathway in EBV(+) as compared to EBV(-) HIV-DLBCL. Conclusion: EBV(+) HIV-DLBCL show a distinct mutational profile compared to EBV(-) HIV-DLBCL, with EBV(+) cases showing frequent mutations with STAT3 and DDX3X in contrast to EBV(-) cases with frequent mutations associated with epigenetic modification pathways (KMT2D, TET2). These genetic profiles underscore the need for tailored therapeutic approaches depending on EBV status. Although the analysis is limited and requires confirmation in a larger cohort, this is the largest study at present evaluating these tumors.

Introduction: The use of standardized, evidence-based classification systems is crucial for the accurate diagnosis and treatment of diseases. Moreover, standardized classification facilitates research and epidemiologic studies and promotes consistency in communication among healthcare professionals. Since 2016, the revised 4 th edition of the World Health Organization classification (WHO-HAEM4R) has been the global standard for diagnosis of lymphoid malignancies. With the emergence of new data, 2 new classification systems were developed and published in 2022: the 5 th edition of the WHO Classification (WHO-HAEM5) and the International Consensus Classification (ICC). Both WHO-HAEM5 and ICC maintain a shared fundamental concept of disease classification that integrates clinical, pathologic, and molecular data. However, they differ on nomenclature, establishment of new entities, and/or diagnostic criteria for some disease categories. To evaluate the impact of these differences on real-world diagnosis of non-Hodgkin lymphoma (NHL), we examined the diagnostic classification of NHL in the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study (NCT02736357). Methods: Initiated in 2015, LEO is an ongoing prospective observational study of patients aged ≥18 years with newly diagnosed NHL. Patients are enrolled at 8 major U.S. medical centers. Clinical, epidemiologic, pathologic, and treatment data are abstracted at baseline and active follow-up is conducted for all patients. Lymphoma subtype is coded for each case based on expert hematopathology re-review of the diagnostic pathology slides, the pathology report, biomarker data, and clinical data. Of note, NHL subtype distribution is similar to SEER data. We studied all patients enrolled in LEO between 7/1/2016 (the date LEO pathology review started using WHO-HAEM4R diagnostic codes) and 5/31/2020. WHO-HAEM4R diagnoses and additional clinicopathologic data, when relevant, were used to map cases into the corresponding WHO-HAEM5 and ICC diagnoses. Differences between WHO-HAEM5 and ICC were annotated for each case as: None - same disease entity; Minor - difference in nomenclature with similar diagnostic criteria; Major - difference in disease category and/or diagnostic criteria; or Unevaluable - insufficient data to assign WHO-HAEM5 and/or ICC diagnosis. Results: LEO enrolled 6143 patients during the study period. Of these, comparison between WHO-HAEM5 and ICC was evaluable in 5730 (93.3%). Unevaluable cases included those without a specific WHO-HAEM4R diagnosis at enrollment (N=384; e.g., patients with a low-grade B-cell lymphoma that could not be definitively sub-classified) and those with a specific WHO-HAEM4R diagnosis, but with insufficient clinicopathologic data to assign a specific WHO-HAEM5 and/or ICC diagnosis (N=29). Of the 5730 evaluable cases, 5376 (93.8%) showed no difference between WHO-HAEM5 and/or ICC diagnosis, 311 (5.4%) showed minor differences (nomenclature only), and 43 (0.8%) showed major differences (Table 1). The 43 major differences all involved B-cell NHLs; 20 (46.5%) were attributable to different approaches to classifying double-hit lymphomas, 21 (48.9%) to classification of splenic/leukemic B-cell lymphomas, and 2 (4.6%) to classification of B-cell lymphomas occurring at specific anatomic sites (Table 2). Conclusion: In a large, prospective lymphoma cohort reflecting real-world clinical practice at 8 major U.S. medical centers, major diagnostic differences in the classification of NHL using WHO-HAEM5 or ICC classification criteria were seen in 0.8%, whereas the remaining 99.2% of diagnoses were either the same or showed differences in nomenclature only. The existence of 2 concurrent classification systems presents potential for discrepancies in pathologic diagnosis, clinical practice, clinical trials, and other lymphoma research. Furthermore, some of the differences between WHO-HAEM5 and ICC are clinically and potentially therapeutically significant, and their resolution requires further study. Nevertheless, our findings argue that the proportion of patients affected would be small in real-world practice settings. This appears largely related to incidence rates of specific lymphoma subtypes, with major differences between the 2 classifications predominantly affecting rare entities, while there is general concordance on the most common forms of NHL.

Introduction: PET/CT is the standard-of-care for staging and therapy response assessment in lymphoma. Fluorodeoxyglucose (FDG)-avidity in extranodal marginal zone lymphoma (EMZL) remains controversial with some variability by extranodal location. The current Lugano classification recommends the use of CT scans only in staging and follow-up for EMZL. However, emerging data from small studies have challenged this suggestion. In this study we aimed to determine the ability of PET/CT to detect FDG-avid EMZL during staging work-up. Methods: First, we retrospectively analyzed the University of Miami (UM) MZL database (period 2/2016-1/2023) searching for patients who underwent staging PET/CT. Images were reviewed by expert radiologists to ascertain avidity of tumor and not surrounding tissue, with specific attention to ocular and GI locations; if scans were not available (n=15), we retrieved data from reports (results presented in part at ICML2023). Next, we aimed to validate the initial UM results additionally analyzing data from imaging reports for patients prospectively enrolled in the Lymphoma Epidemiology of Outcomes (LEO) MZL cohort (period 7/2015-5/2020), excluding LEO patients from Miami to avoid overlap. Patients with high-grade transformation at diagnosis were excluded. For patients with >1 extranodal site, each location was counted independently. We considered FDG-avid disease if SUVmax was ≥2 as this value is commonly observed between mediastinal blood pool (BP) and liver background. To normalize data, we calculated ratios of lymphoma SUVmax versus both BP and liver background, as available. Patients without measurable disease were excluded from analysis. Results: Among 210 patients with EMZL in the UM cohort, 152 had staging PET/CT and were analyzed. Twenty-two patients demonstrated >1 extranodal site providing a total of 187 locations. The LEO cohort included 411 patients from 7 centers, with 235 having available imaging reports. Fifty-two patients in this cohort demonstrated >1 extranodal site providing a total of 306 locations. Disease distribution is depicted in Table 1. Among 187 EMZL locations in the UM cohort, the most common were gastric (n=33, 17.6%), ocular (n=31, 16.6%), lung (n=30, 16%), skin and soft tissue (n=16, 8.6%, each). Similarly, lung (n=63; 20.6%), soft tissue (n=46; 15%), gastric and ocular (n=34 each; 11%) were common locations in the LEO cohort. EMZL demonstrated FDG-avidity (SUVmax ≥2) across all locations with identical values in both cohorts (UM= 78.1% & LEO= 76.5%). FDG-avidity by location is shown in Table 1A & B with salivary gland (100% & 100%), lung (93.3% & 95.2%), soft tissue (93.8% & 100%), and airways (90.9% & 100%) demonstrating high avidity in both cohorts. Contrarily, skin was commonly non-FDG avid (93.8% & 81%). The median size of FDG-avid lesions was 2.4cm (range, 0.7-17.4) in UM and 2.9cm (range, 0.1-12) in LEO cohorts. In patients with >1 extranodal site FDG-avidity was nearly universal across sites (UM=93% & LEO=100%). We observed a significant correlation between lymphoma size and FDG-avidity for UM (r=0.33; P=0.001), and for LEO (r=0.55; P<0.0001). In patients with background FDG-avidity data in the UM cohort (n=150), a BP index and liver index ≥1 detected lymphoma in 79.3% & 71.5% cases, respectively. We were unable to calculate indexes in LEO cohort since only limited data on BP (n=26) and liver (n=19) background was available in imaging reports. Conclusions: This study represents the largest analysis evaluating accuracy of PET/CT to determine initial tumor burden in 387 patients with EMZL. We demonstrate that EMZL is largely an FDG-avid disease across two cohorts, and PET/CT should be included in the staging of these patients while acknowledging possible limited sensitivity in GI locations due to physiologic uptake. Furthermore, we observed that patients with multiple extranodal locations demonstrate uniform FDG-avidity across all sites except for skin involvement. Based on our results we recommend the incorporation of PET/CT into standard staging of EMZL in planned revised Lugano classification guidelines. In those demonstrating initial FDG-avidity, a lower SUVmax threshold of SUVmax ≥2, comparison to mediastinal BP rather than to liver background activity and evaluating for resolution of focal FDG-avidity should be considered to assess treatment response in routine care and clinical trials.

Background: Anaplastic large cell lymphomas (ALCLs) are CD30-positive T-cell lymphomas that share pathologic features but differ in clinical presentation, outcome, and molecular features. The World Health Organization (WHO) and International Consensus Classification (ICC) classify ALCLs by presence or absence of ALK rearrangements (R) and clinical presentation (systemic, cutaneous [c], or breast implant-associated [BIA]). ICC, but not WHO, recognizes DUSP22-R as defining a new genetic subtype of ALK- ALCL. The classifications otherwise do not reflect additional molecular heterogeneity in genetics (e.g., TP63-R) or therapeutic vulnerabilities (e.g., JAK-STAT3 pathway activation). Methods: ALCLs (N=689) underwent expert consensus review (WHO/ICC) through the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). All cases also underwent genetic subtyping (ALK, DUSP22, TP63, and triple-negative [TN]) using fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC), as well as IHC for phospho-STAT3 Tyr705 (pSTAT3). RNAseq was performed and evaluable in 393 cases; the remaining cases had insufficient tissue, tumor content, RNA yield or quality, and/or sequencing data quality. Sequenced and non-sequenced sub-cohorts had similar demographics and subtype distribution. Results: Unsupervised gene expression profiling (GEP) identified 2 main molecular types of ALCL. Type I ALCLs predominantly included ALK+ ALCLs, BIA-ALCLs, and a subset of TN ALCLs (designated TN-I), whereas Type II ALCLs predominantly included ALCLs with DUSP22-R, TP63-R, or both (double-hit; DH), and the remaining TN ALCLs (TN-II). Type I ALCLs were strongly associated with pSTAT3 expression (74.2±26.4% positive malignant cells vs 9.9±22.7% for Type II; P<0.0001). An independently derived pSTAT3 staining threshold of 30% assigned Type I vs II with 91% accuracy. A third cluster of ALCLs, mostly cALCL, showed an epithelial GEP signature rather than a lymphoma signature; these cases were assigned to Types I or II based on pSTAT3 IHC. Distinct sub-signatures were identified for ALK+, DUSP22-R, TP63-R, and BIA ALCL (Fig. 1), but not ALK- ALCL or cALCL. Gene set enrichment analysis showed Type I ALCLs to be enriched for JAK-STAT3 signaling genes (normalized enrichment score [NES], 2.22; FDR<0.0001) and related pathways, such as TNFα-NFκB signaling (NES, 2.21; FDR<0.0001). In contrast, Type II ALCLs were enriched for cell cycle, DNA repair, epigenetic, and metabolic pathway genes, but not for major tyrosine kinase-mediated signaling pathway genes. Enriched epigenetic pathways included chromatin modifying enzymes (NES, -1.86; FDR=0.002) and histone methylation (NES, -1.71; FDR=0.002). EZH2 was the most overexpressed gene in Type II ALCLs (fold-change, 7.74; FDR=8.84×10 -306). At the protein level, EZH2 IHC H-scores were 275±45 in Type II and 168±70 in Type I ALCLs (P<0.0001); H3K27me3 H-scores were 170±81 and 76±63, respectively (P<0.001). The top metabolic gene set involved cholesterol biosynthesis (NES, -1.88; FDR=0.002). Overall survival (OS) data were available in 257 systemic ALCL patients (145 sequenced and 112 non-sequenced; cALCL and BIA-ALCL were excluded). Non-sequenced TN ALCLs were assigned to TN-I or TN-II using pSTAT3 IHC. The results supported earlier data indicating favorable prognosis of DUSP22-R ALCL (5 y OS, 95%) and ALK+ ALCL (87%), intermediate prognosis of TN ALCL (TN-I, 52% and TN-II, 38%; P=NS), and poor prognosis of TP63-R/DH ALCL (0%)(P<0.0001; Fig. 2). Conclusions: Two overarching molecular types of ALCL exist, predominantly associated with the presence (Type I) or absence (Type II) of the JAK-STAT3 signaling program. Distinct GEP signatures exist for ALK+ ALCL and BIA-ALCL (predominantly Type I), and DUSP22-R ALCL and TP63-R ALCL (predominantly Type II). TN ALCLs lacking ALK-R, DUSP22-R, and TP63-R can be stratified into TN-I and TN-II subtypes. pSTAT3 IHC has >90% accuracy as a surrogate for GEP-based subtyping. ALK- ALCL and cALCL cluster by molecular subtype rather than by defining GEP signatures. Type II ALCLs are enriched for targetable epigenetic and metabolic pathways, including EZH2/histone methylation and cholesterol biosynthesis. This molecular classification is diagnostically, prognostically, and potentially therapeutically relevant, and can be applied using FISH and IHC in routine practice and in the clinical trial setting.

Introduction: Previously we demonstrated that HIV associated diffuse large B-cell lymphomas (DLBCL) of Germinal Center B-cell subtype (GCB) are more proliferative, with enhanced genomic stability and increased expression of DNA repair genes, particularly Fanconi anemia (FA) and homologous recombination (HR) genes compared to their HIV negative counterparts (Maguire et al, 2019). It is unknown if this signature is unique to the GCB subtype or if it is also observed in Activated B-cell (ABC) and Unclassified (UNC) DLBCL. Herein we validate our HIV associated GCB DLBCL findings in a larger independent cohort and report for the first time the aberrational profile of molecularly profiled HIV associated ABC DLBCL compared to their HIV negative counterparts respectively. Methods: An independent cohort of 353 DLBCL FFPE cases was assembled, including 125 HIV-DLBCL samples. All samples underwent hematopathological review to confirm diagnosis and determine tumor content. Samples with <60% tumor content were macro-dissected before they were RNA/DNA extracted. Cell of origin (COO) profiles were assessed using the Lymph3Cx molecular assay which can distinguish primary mediastinal B-cell lymphoma (PMBL) like from GCB, ABC and UNC DLBCL (Mottok et al 2018). Copy number (CN) analyses were performed on samples with sufficient DNA (41 HIV neg, 32 HIV pos) using the OncoScan FFPE assay kit and the resulting data analyzed using Chromosome Analysis Suite (ChAS) v4.1 and the multisample viewer module of Reproductive Health Research Analysis Software (RHAS) v1.1. Additional digital gene expression profiling was performed using the Pan-Cancer panel (NanoString, Seattle, WA) customized to include 9 BCL2 family genes for a total of 739 genes and analyzed using the NanoString nSolver Advanced Analysis module. Results: GCB, ABC, UNC and PMBL-like proportions were 50%, 30%, 14% and 6% in HIV unassociated (HIV neg) and 50%, 23%, 25% and 2% in HIV pos tumors respectively, confirming both cohorts were GCB-enriched by molecular profiling. PMBL-like cases were excluded from further analyses. OncoScan CN analyses showed that HIV pos DLBCL were significantly less aberrant than HIV neg DLBCL (median CN per sample 0.56 vs 1.01, p<0.001). HIV pos GCB tumors were significantly less aberrant than both HIV neg GCB tumors (median CN per sample 0.50 vs 1.11, p<0.001), and HIV pos ABC tumors (median CN per sample 0.50 vs 0.81, p=0.009). HIV pos ABC tumors were also less aberrant than HIV neg ABC tumors, however, the difference was not significant overall (median CN per sample 0.81 vs 1.03, p=0.162) or for gain/amplifications (median CN per sample 0.38 vs 0.42, p=0.814), but was borderline significant for loss/deletions (median CN per sample 0.31 vs 0.47, p=0.06). GEP analyses identified Cell Cycle and DNA repair as the top two upregulated pathways in HIV pos GCB tumors compared to HIV neg GCB tumors. In contrast, Cell Cycle and DNA repair were downregulated in HIV pos ABC tumors compared to HIV neg ABC tumors. However, one gene ( RBX1) was identified as significantly upregulated in both pathways in HIV pos GCB (adjusted p-value 0.0215) and HIV pos ABC (adjusted p-value 0.0046) tumors compared to their HIV neg counterparts. A second gene ( SKP1) was also significantly upregulated in HIV pos GCB (adjusted p-value 3.94E-5) and HIV pos ABC (adjusted p-value 0.0031) tumors. Together RBX1 and SKP1 encode the two principal functional subunits of the SKP1, CUL1, F-box protein (SCF) complex which is part of the ubiquitin proteasome system (UPS) and has been reported as essential for maintaining genome and chromosome stability (Thompson et al 2021). Conclusions: These results demonstrate that HIV pos DLBCL tumors are less aberrant than their HIV neg counterparts irrespective of COO subtype. However, the degree of genomic stability differs by COO, with HIV pos GCB tumors being more genomically stable than HIV pos ABC tumors. Although both have enhanced expression of UPS related SCF genes ( RBX1, SKP1), only HIV pos GCB tumors have enhanced expression of key DNA repair genes as well including Fanconi Anemia ( BRCA2/FANCD1, FANCL) and mismatch repair ( MSH2, MSH6) genes (adjusted p-values of ≤ 0.0263). Given the reported role of SCF in genomic stability maintenance, the HIV pos COO CN differences could be due to the contributions of both DNA repair and SCF mechanisms in HIV pos GCB and mainly SCF mechanisms in HIV pos ABC tumors.

Background: High Grade B cell Lymphoma (HGBL) with MYC and BCL2 and/or BCL6 rearrangements(R) was introduced as an entity in 2016 by the WHO revised 4 th edition. In 2022, both the WHO 5 th edition (beta version) and the International Consensus Classification (ICC) separated DHL- BCL2 (+/- BCL6-R)from DHL- BCL6 given differences in biology . However, while the ICC has maintainedDHL- BCL6 as a provisional entity, the WHO has removed the category, thus removing the requirement to FISH for BCL6-R in this setting. Clinical data on DHL- BCL6 is much more limited, as these cases represent only 10-20% of DHL and have been combined with BCL2-R cases in prior studies. Outcomes are variable in retrospective studies with no consistent data on prognosis or optimal therapeutic strategies. By retaining the category of DHL-BCL6 as a provisional entity, the ICC emphasized the need for further, multicenter, prospective studies evaluating the clinical and biological features of this disease. We herein report a comprehensive comparison of clinical characteristics and outcomes in patients with DHL- BCL6 compared to diffuse large B-cell lymphoma (DLBCL), not otherwise specified (NOS); DLBCL with MYC rearrangement only; DHL- BCL2; and HGBL, NOS in a large, multicenter, prospective cohort of patients from Lymphoma Epidemiology of Outcomes (LEO). Methods: Adult patients with newly diagnosed large B-cell or HGBL were enrolled within 6 months of diagnosis at one the 8 LEO cohort academic medical centers in the US between 2015 and 2020. Baseline characteristics were abstracted at the time of diagnosis per protocol. Based on FISH data patients were further sub mgrouped into DLBCL, NOS (without MYC rearrangement); MYC-R DLBCL, NOS; HGBL, NOS; DHL- BCL2 and DHL- BCL6. Event-free survival (EFS) was defined as the time from diagnosis until progression/relapse, retreatment, or death. Overall survival (OS) was defined as the time from diagnosis until death due to any cause. Results: A total of 1526 eligible patients were identified during this time period. All FISH data was available at the time of diagnosis and the choice of treatment was based on physician discretion. Median age at diagnosis was 63 years (IQR 53-72), with 148 (10%) patients in the AYA category, and 128 (8%) patients > 80 years. 58% (891) were male, 11% self identified as Hispanic or Latino, and 7% as Black/African American. The median diagnosis to treatment interval (DTI) was 20 days (IQR 12-32), and 33% had DTI < 14 days. The FISH-based subgroups were MYC-negative DLBCL, NOS (N=1146, 75%), MYC-R DLBCL,NOS 227 (N = 96, 6%), DHL- BCL2 (N=154, 10%), DHL- BCL6 (N=38, 3%), and HGBL, NOS (N=92, 6%). When available, COO by Hans algorithm was 92% GCB in DHL- BCL2 and 50% GCB in DHL- BCL6. Clinical characteristics can be found in the table. At a median follow-up of 49 months (IQR 36-67), 490 patients (32%) had an event and 356 patients (23%) died. EFS at 24 months (EFS24) was 75% (95% CI: 73-77). Patients with DHL- BCL6 were younger at diagnosis (median 60 years), had more extranodal site involvement (40%), more often stage III/IV disease (70%), and more often treated with a higher intensity regimen than R-CHOP (69%) compared to DLBCL,NOS and MYC-R DLBCL. DHL- BCL6 also had fewer patients that were males (47%), with DTI <=14 days (33%), NCCN IPI ≥ 4 (45%), elevated LDH (53%) than HGBL, NOS and DHL- BCL2. The 2-year EFS and OS rates were noted to be significantly better in the DHL- BCL6 (EFS 79%, 95% CI: 67-93; OS 92%, 95% CI: 84-100) as compared to DHL- BCL2 (EFS 58%, 95% CI: 50-66; OS 70%, 95% CI 63 - 78) and HGBL, NOS (EFS 74%, 95% CI: 65-84; OS 74%, 95% CI: 65-84 ), (Figure 1) but were comparable to that of DLBCL, NOS (EFS 78%, 95% CI: 76-81; OS 87%, 95% CI: 86-89). Conclusions: Our data support separating DHL- BCL6 from DHL -BCL2 as these patients form a unique subgroup with some clinical characteristics comparable to both DLBCL, NOS as well as HGBL, NOS and DHL- BCL2 subtypes. In this cohort, clinical outcomes are more comparable to DLBCL, NOS than DHL- BCL2 or HGBCL, NOS. More frequent use of intensive chemotherapy in DHL- BCL6 compared with DLBCL may account for this finding, although larger multicenter studies are needed. Our results support continued identification of DHL- BCL6 in the clinical setting to better understand optimal therapy and biology of this cohort.