Novak, Joseph P.

Abstract Germinal center (GC)-derived lymphomas arise within a specialized immune ecosystem, yet whether malignant cells direct its remodeling remains unclear. Integrating genomic, transcriptomic, spatial, and functional analyses across follicular lymphoma and diffuse large B-cell lymphoma, we define a developmental framework linking malignant B-cell differentiation state to tumor microenvironment (TME) organization. Rather than segregating by histology, lymphomas align along a shared differentiation continuum in which proliferative dark zone (DZ) states associate with immune-depleted TMEs, whereas post-GC/memory B-cell (MBC) states drive inflamed but immunosuppressed TMEs. Spatial profiling reveals collapse of GC architecture and emergence of suppressive myeloid niches along this trajectory. Single-cell lineage reconstruction uncovers a DZ-to-MBC developmental axis underlying lymphoma evolution. Genetic reprogramming in vivo demonstrates that malignant differentiation state is sufficient to instruct TME remodeling. Collectively, these findings establish malignant differentiation state as a causal determinant of immune architecture across GC-derived lymphomas and identify lineage-directed immune reprogramming as a potential therapeutic strategy.

Abstract The purpose of this study was to explore epigenetic dysregulation resulting from deleterious SPEN mutations in diffuse large B cell lymphoma (DLBCL). Truncating (tr) SPEN mutations are among defining variants in LymphGen:BN2 and DLBclass:C1. We previously found SPEN mutations enriched in DLBCL that failed to reach EFS24, and inferior survival was observed in SPEN-tr vs all other BN2 and C1. Differential gene expression (DEG) in these groups identified >1000 DEGs including upregulation of IKZF3 and BCL2 and downregulation of MHC-II, overall suggesting an alternative, aggressive biology for a subset of BN2/C1 cases generally thought to have favorable outcomes. In healthy cells, SPEN is a dynamic epigenetic regulator with roles in chromatin formation and as a NOTCH co-repressor. We hypothesized that loss of SPEN reprograms the epigenetic landscape to drive the aggressive phenotype in affected DLBCL. Methods: OCI-LY3 cell line with CRISPR/Cas9-induced SPEN-tr mutations was analyzed by ATAC and RNA-seq. Diagnostic DLBCL FFPE tumor biopsies from the Molecular Epidemiology Resource (MER) were analyzed by 850k/EPIC methylation array (n=164). SPEN-depleted OCI-LY3 cells displayed significant (|Log2FC|>2) peaks of open (n=3083) and closed (n=1729) chromatin indicative of systemic epigenetic reprogramming, with enriched peaks (FDR<0.01, |Log2FC|>2) converging on pro-survival and immune evasion (ATP11C, BCL11B, RAG1/2 genes) and negatively enriched for cell cycle and apoptotic pathways (CDK6, TP63, CD80 genes). Chromatin accessibility featured enrichment for TCF3/4 and ZEB1 binding motifs and depletion of EBF1, REL, and NFKB1/2 motifs (FDR<0.0001, |Z-score|>5), suggesting a shift to an activated, post-germinal center program (via open TCF3/4 motifs) with reduced reliance on NF-kB signaling. Footprinting analysis further revealed decreased occupancy at NFKB2 and REL/B motifs, and reduced occupancy at HES1 with elevated occupancy at Rbpjl motifs (p<0.05, |Score|>0.2) indicating downregulation of NF-kB is in favor of non-canonical Notch transcription programming. Merging gene expression and accessibility, gene-peak concordance was observed for elevated CXCR4 and IL6 expression and decreased SOCS1, CD274 (PD-L1), and CCND1 expression (FDR<0.01, |Log2FC|>1), suggesting expression programs feature uncontrolled JAK/STAT signaling (via high IL6, low SOCS1) with immune evasion mechanisms independent of PD-L1. By methylation array, strong epigenetic reprogramming was observed in SPEN-tr DLBCL (n=8), where differential methylation analysis vs WT (n=146), vs BN2 (n=4), and vs C1 (n=15) samples revealed hypermethylation signatures (p<0.05, |FC|>1) indicative of reduced cell-cell signaling and antigen presentation pathways (including HLA-A/G/H). In conclusion, SPEN-depletion triggers systemic epigenetic reprogramming to enhance immune evasion and non-canonical Notch target genes. SPEN-tr DLBCL should be considered with heightened risk estimation and as prime candidates for personalized treatments beyond standard therapy. Citation Format: Janek S. Walker, Joseph P. Novak, Abigail R. Dropik, Zilin Xianyu, Michelle K. Manske, Matthew J. Maurer, Eric Mou, Rebecca L. King, Stephen M. Ansell, Thomas M. Habermann, Thomas E. Witzig, James R. Cerhan, Anne J. Novak. Deleterious SPEN mutations induce epigenetic reprogramming to promote survival and enhance immune evasion pathways in an aggressive subset of BN2/C1 DLBCL tumors [abstract]. In: Proceedings of the Fifth AACR International Meeting on Advances in Malignant Lymphoma: From Discovery to Clinical Impact; 2026 Jun 24-27; Philadelphia, PA. Philadelphia (PA): AACR; Blood Cancer Discov 2026;7(3_Suppl):Abstract nr A006.

Abstract Therapeutic options for Waldenström macroglobulinemia (WM) have expanded but improvements in overall-survival (OS) are difficult to interpret due to competing non–WM mortality. We conducted a large single-center retrospective study of 1,020 patients with WM to evaluate survival trends. Patients were stratified by era of active WM diagnosis using a two-era model (1996–2005 and post-2005) and a four-era model (pre-2001, 2001–2007, 2008–2013, and post-2013). OS did not differ significantly across eras in the overall cohort (p = 0.64 and p = 0.86 for the two- and four-era models). However, among patients aged < 65 years at the time of active WM diagnosis in the 2-era model, OS improved in the post-2006 era (median 18.8 vs 14.1 years, p = 0.018). Cause-specific-survival (CSS) improved across all eras, increasing from 15.6 years in 1996–2005 to 18.9 years post-2006 (p < 0.0001), and from 13.7 years pre-2001 to not reached in later periods in the four-era model (p < 0.0001). Competing-risk-analysis (CRA) demonstrated a reduction in WM-related mortality over time (p < 0.001). However, excess mortality persisted, with a standardized mortality ratio (SMR) of 2.79 (p < 0.001) among patients < 65 years compared with a matched U.S. population. Our findings highlight improvements in WM-specific survival, while gains in OS are observed in younger patients.

Abstract Over the past decade, classification systems using high-throughput genetic data have been developed to identify molecular subtypes of DLBCL. Although not a primary goal, these classifiers were also proposed as prognostic factors in their respective publications. To date, however, no study has directly compared these classifiers' ability to predict overall (OS) and event-free survival (EFS) in the same cohort. Herein, we sought to systematically compare predictive performance, benchmarked against the IPI, of several current established molecular classifiers and evaluate if any add significant independent prognostic information beyond the IPI. WES (including paired germline filter) and RNAseq data from newly diagnosed DLBCL patients (N=432; 2018 WHO criteria) in the Mayo Clinic/University of Iowa Lymphoma Molecular Epidemiology Resource (MER) were available for analysis (WES n=112, RNAseq n=40, or both n=280). The number of cases able to be classified (including as unclassified) for each classifier was as follows: IPI (432, 100%), cell-of-origin (COO, by Hans algorithm; 346, 80.1%), refined COO (by gene expression with Dark Zone Signature; 320, 100%), Haematological Malignancy Research Network (HMRN; 349, 89.0%), B-cell state (320, 100%), Lymphoma Ecotype (320, 100%), Lymphoma Microenvironment (LME; 320, 100%), Tumor microenvironment (TME26; 320, 100%), SubLymE (312, 97.5%), LymphGen (358, 91.3%), and DLBclass (223, 58.2%). OS was defined as time from diagnosis to all-cause death while EFS was defined as time from diagnosis to disease progression, initiation of second-line treatment, or all-cause death. We calculated Harrell's c-statistics for each Cox proportional hazards model evaluating the discriminative performance of each classifier in predicting OS/EFS. Using bootstrap validation, we obtained optimism-corrected c-statistics, which we report in the results. We performed likelihood ratio tests (LRT) comparing a univariable Cox model with IPI alone and models including both IPI and a given classifier to assess if a classifier provided independent prognostic information beyond the IPI. All patients were treated with immunochemotherapy (IC) with curative intent, 247 (57%) were male, median age at diagnosis was 65 years (IQR 55-72 years), 390 (96%) were White, 209 (60%) had GCB subtype by Hans, 22 (5.1%) had MYC double-hit by FISH (MYC and BCL2 or BCL6), and 162 (37.9%) had an IPI ≥ 3. The median follow-up was 7.0 years, 167 (39%) experienced an event, and 137 (32%) died. In a univariable Cox model, the c-statistic for IPI predicting OS was 0.66 (95% confidence interval [CI] 0.61-0.70). All other classifiers had c-statistics of ≤0.56. The c-statistic for IPI predicting EFS was 0.64 (95% CI 0.60-0.69), and all other classifiers had c-statistics of ≤0.58. The univariate DLBclass results for OS and EFS were not significantly impacted when restricted to cases with confidence &gt;0.7 (n=136). In Cox models of IPI alone versus IPI plus an individual classifier, the only classifier that provided statistically significant, independent information for OS was TME26 (LRT p=0.02). Adjusting for IPI, patients who were TME26-negative had significantly inferior OS compared to TME26-positive cases (HR 1.63, 95% CI 1.07-2.47; p=0.02). For EFS, DLBclass (restricted to confidence &gt;0.7) added significant prognostic information beyond IPI (LRT p=0.02). This finding was largely driven by C5 subtype; relative to C1 subtype and adjusting for IPI, C5 subtype had significantly inferior EFS (HR 5.53, 95% CI 1.81-17.0; p=0.003). In summary, we compared prognostic performance of multiple DLBCL molecular classifiers with respect to OS and EFS in a single real-world, prospective cohort of newly diagnosed, IC-treated DLBCL. Our data supports two key findings: all classifiers had modest performance for prognosis, and none individually outperformed the IPI in predicting OS nor EFS. Second, only TME26 and DLBclass (confidence &gt;0.7) provided additional prognostic information beyond that captured by the IPI for OS and EFS, respectively. This finding suggests that the tumor immune microenvironment and characteristics of C5 DLBCLs (ABC-subtype, CD79B mutations) can potentially offer significant independent information for predicting survival and response to front-line immunochemotherapy. If replicated, these findings could inform risk-adapted treatment approaches and aid in identifying high-risk patients for enrollment in genomically-informed clinical trials.

Abstract Background: Waldenström Macroglobulinemia (WM) is an indolent B-cell lymphoplasmacytic lymphoma characterized by heterogeneous clinical behavior and variable progression patterns. While MYD88L265Pand CXCR4 mutations are frequently encountered, the broader genomic landscape underpinning disease evolution from smoldering WM (SWM) to active treatment naïve WM (TNWM), post-treatment remission WM (PTWM) and relapsed/refractory WM (RRWM) remains incompletely understood. To address this gap, we studied the mutational profile across the WM disease spectrum. Methods We performed whole exome sequencing (WES) on sorted (CD19 and/or CD138) bone marrow aspirates of patients across the spectrum of WM. Paired germline sequencing was performed using peripheral blood mononuclear cells (PBMCs). Unique molecular identifier-tagged reads were deduplicated using fgbio. WES data were processed through the Sarek pipeline. Any valid mutation from either caller, present on the index or in COSMIC was considered. Copy number variations (CNVs) were inferred via CNVkit and summarized at the gene and arm level (≥50% directional change). Mean tumor and germline coverages were 174X and 74X, respectively. Fisher's exact test was used for enrichment and hypergeometric test for overlap analyses. Results A total of 78 high-quality WM samples [15 SWM, 44 TNWM, 13 RRWM, 6 PTWM in remission (all with paired TNWM samples)] were sequenced. The mutational burden varied across disease states (median SWM=1.48 m/Mb, TNWM= 1.12 m/Mb, RRWM = 1.59 m/Mb; p=0.04). Density plots revealed bimodal VAF distributions, consistent with clonal and subclonal architectures in WM. Overall, 77% harbored a MYD88L265P mutation by WES. Among MYD88^WT^ patients, AS-PCR identified MYD88L265P in 4 (25%) not detected by WES, raising the overall mutation rate to 83%, plus one with a non-L265P variant. Low VAF (&lt;10%) MYD88L265P mutations were seen in 6% of matched PBMCs. MYD88 copy number gain was seen in 2 (17%) MYD88WT TNWM patients. CXCR4 mutations were detected in 38% by WES (18% each frameshift and nonsense). Two (4%) CXCR4WT samples were positive by PCR, giving an overall rate of 40%. CXCR4 mutations were more frequent in RRWM (54%) vs TNWM (41%) and SWM (27%), though not statistically significant. Del(6q) and Del(17p) were noted in 16% (n=12) and 7% (n=5) of patient samples. All del(17p) events were noted in TNWM samples and in one paired post-treatment sample. Overall rate of del(17p) and TP53 mutation was 14% (n=11). RRWM was enriched in ARID1A alterations, a gene implicated in chromatin remodeling and plasma cell identity formation [38% (n=5) in RRWM vs. 11% (n=6) in TNWM and SWM], compared to TNWM and SWM p=0.03]. Alterations in NF-kB signaling gene MAP3K14 were more frequent in RRWM (31%, n=4) compared to the SWM/TNWM cohort [(7%), n=4; p=0.036). We noted an enrichment in the TP53 mutation rate in RRMW [n=3, 23%, OR 7.7] compared to TNWM and SWM cohorts [n=2, 4%), p=0.04]. Mutations in FUBP1 (p=0.03), an upstream regulator of MYC, and CARD11 (p=.043), a B-cell signaling scaffold protein were also more frequent in RRWM. Notably, none of the SWM patients harbored an ARID1A alteration (p=0.057), suggesting acquisition during progression. CNV analysis revealed that MAP3K14 amplifications were frequent in RRWM (n=3, 23%) compared to SWM/TNWM [n=2 (4%), p=0.043]. RRWM samples showed increased CD79B mutations (15%) and significant overlap with the C5/ABC diffuse large B-cell lymphoma (DLBCL) genomic cluster (Chapuy et al., Nat. Med. 2018; p=0.007). This overlap remained significant after excluding MYD88L265P (p=0.019), driven by CARD11, CD79B, and IGLL5, suggesting that a subset of RRWM may acquire an ABC DLBCL-like mutational profile. These findings warrant further investigation using transcriptional profiling. Conclusions This study provides a genomic map of WM evolution from precursor to relapse. Increasing somatic mutations and CNVs support stepwise progression. Enrichment of genes involved in chromatin remodeling and plasma cell identity formation (ARID1A), NF-kB or BCR signaling (CARD11, MAP3K14), and DNA damage repair (TP53) were noted at relapse, all of which have been shown to drive aggressive disease biology. Emergence of an ABC-like genotype in a proportion of RRWM indicates convergent evolution with aggressive lymphomas. Transcriptional studies are warranted to explore this further.

Abstract Background: Follicular lymphoma (FL) is a germinal center–derived B cell malignancy characterized by the clonal expansion of a dominant malignant B cell population. While prior studies have identified transcriptional subtypes across patients, most analyses have treated B cells within individual tumors as a transcriptionally uniform population. However, this assumption has not been systematically tested using high-resolution, clonotype-resolved transcriptomic data. The broader landscape of intratumoral B cells—including those not belonging to the dominant clone—remains poorly defined, and their roles in disease biology are not well understood. These unexpanded, intratumoral B (ITB) cells may include residual non-malignant populations, early-stage malignant cells, or immune-modulating cells with distinct roles in the tumor microenvironment. It is also unknown whether their presence varies across patients or correlates with clinical features or immune microenvironmental interactions. Methods: We performed integrated single-cell 5′ RNA sequencing and B cell receptor (BCR) repertoire sequencing on 7 newly diagnosed FL 1-3A fresh-frozen lymph node biopsies (Dasari et al., Blood Cancer Discov 2025). Using a high-confidence approach that incorporates heavy and light chain pairing, V and J gene usage, and CDR3 nucleotide junction identity, we classified B cells into two groups: (1) cells belonging to the dominant expanded clone (FL B cells) and (2) all other B cells with detectable and non-expanded BCRs (ITB). These clonal identities were then integrated with single-cell transcriptomic profiles using Seurat and Immcantation pipelines. Differential expression analysis was conducted using edgeR to compare FL B cells to ITB cells across all FL biopsies. Results: After quality filtering, a total of 44,637 single cells were retained across all 7 samples (minimum per sample: 3,847 cells), including malignant and non-malignant B cells as well as diverse tumor microenvironment populations. The proportion of B cells assigned to the dominant FL clone varied substantially across tumors, ranging from 22% to 89%, indicating that some tumors contain a substantial population of ITB cells. In one tumor, we identified two expanded malignant B cell clones comprising 40.6% and 34.4% of all cells. These clones exhibited non-overlapping V and J gene usage (IGHV3-11/IGHJ5 vs. IGHV3-72/IGHJ3), distinct CDR3 junctions, and different immunoglobulin isotypes (IGHG1 vs. IGM). BCL2 was expressed in most cells within both clones (Clone 1: 87.8%, Clone 2: 67.0%), with mean log-normalized expression levels of 1.79 and 0.95, respectively. Both clones formed distinct UMAP clusters and showed transcriptional divergence from ITBs, with 453 differentially expressed genes (DEGs) identified for Clone 1 and 98 for Clone 2 (adjusted p&lt;0.01, |log₂FC|&gt;1, min.pct≥0.25). Additionally, 748 DEGs were identified between the two clones. This evidence of clonal divergence within a single FL tumor reinforces the need to reconsider intratumoral homogeneity in FL and suggests that multiple malignant clones may sometimes coexist. When comparing FL clones to ITB cells across tumors we found that FL clones exhibited a transcriptional program enriched for proliferation and cell cycle regulators, including MKI67 (p&lt;0.005), E2F1 (p&lt;0.0001), CDKN2A (p&lt;0.0001), and CDKN2B (p&lt;0.01), as well as elevated expression of AICDA (p&lt;0.01), EZH2 (p&lt;0.0001), and PD-L1 (p&lt;0.05). As expected, the malignant cells also had higher expression of BCL2 (p&lt;0.01) and CD10/MME (p&lt;0.0001). In contrast, ITB cells demonstrated relatively higher expression of SELL (p&lt;0.0001) and TNFRSF14 (p&lt;0.05), which were significantly downregulated in the FL clone. Conclusions: Together, these findings challenge the prevailing notion that FL tumors are defined by a single homogeneous malignant B cell population. Instead, our data support a model in which multiple transcriptionally and functionally distinct B cell populations coexist within tumors, including dominant clones and a diverse population of ITB cells. This is, to our knowledge, the first study to comprehensively characterize these populations using integrated, lineage-aware single-cell multiomic profiling across FL patients. These insights may ultimately inform new strategies for understanding tumor evolution, immune evasion, and therapeutic targeting in follicular lymphoma.

Abstract Description Signal regulatory protein-α (SIRPα) is a key member of the “do-not-eat-me” signaling pathway and is expressed on intratumoral monocytes/macrophages in lymphoma. In this study, we found that SIRPα is also expressed by a subset of malignant B cells in lymphoma. SIRPα+ B cells have a memory phenotype with germinal center (GC) dark-zone features, and RNA velocity analysis showed that SIRPα+ B cells exhibit higher spliced transcripts confirming a more mature phenotype. SIRPα expression is substantially upregulated by treating lymphoma B cells with LPS or CpG and SIRPα+ B cells showed increased proliferation when compared to SIRPα- B cells, which was associated with reduced cellular autophagy. SIRPα+ B cells exhibited increased expression of BAFF signaling pathway molecules as the likely mechanism of increased proliferation and survival. Furthermore, in co-culture, SIRPα+ lymphoma B cells suppressed T-cell function and blocking SIRPa/CD47 signaling reversed T cell inhibition. Clinically, we found that a greater number of SIRPα+ B cells present in the diagnostic tumor biopsies of FL patients was associated with a significantly poorer overall survival. We conclude that SIRPα+ lymphoma B cells are a proliferative component of indolent lymphomas, are associated with T-cell suppression, and increased prevalence of these cells is associated with a poor prognosis. Targeting SIRPα+ B cells in lymphoma may therefore be a promising therapeutic strategy. Topic Categories Tumor Immunology: Cellular Responses and Tumor Microevironment (TIME)

Abstract Extramedullary disease (EMD) is associated with an inferior prognosis and lower response rates to conventional multiple myeloma (MM)–directed therapies compared to MM without EMD. A deeper understanding of the molecular landscape and underlying drivers of EMD is essential to identify potential targets for novel therapeutic strategies. To address this, we performed whole-exome sequencing on EMD tumor tissue from 18 unique patients and bone marrow aspirates (BMAs) from 20 patients at the time of EMD development. Notably, paired EMD and BMA samples were collected from 6 patients at the point of EMD diagnosis, allowing for direct comparison of molecular profiles. Our analysis revealed a near-universal presence of mutations within the MAPK pathway in EMD samples (94%), compared to BMAs (60%; odds ratio, 10.7; P = .02; q &lt; 0.1). Additionally, mutations in established driver genes (NRAS, KRAS, and BRAF) were common and frequently clonal, suggesting their central role in EMD pathogenesis. We also identified alterations in genes associated with cell adhesion and migration (ROBO1, ROBO2, and FAT1) and the SWI/SNF complex and epigenetic regulators (ARID1A, KMT2C, KMT2D, and EP300), although these were predominantly subclonal. Furthermore, we frequently detected biallelic alterations in the tumor suppressor genes MAX (22%), a binding partner for MYC, and CDKN2C (17%). Genomic complexity was significantly higher in EMD samples than BMAs, as evidenced by increased tumor mutational burden and the enrichment of 1q gain/amplifications. These findings underscore the distinct molecular profile of EMD compared to BMA and highlight the genomically complex and heterogeneous nature of extramedullary disease in MM.

Introduction: Diffuse large B cell lymphoma (DLBCL) patients experience favorable outcomes following frontline immunochemotherapy, however, 30-40% of patients will exhibit primary refractory disease or relapse (rrDLBCL). Recent studies have expanded upon well-defined characteristics of newly diagnosed DLBCL (ndDLBCL) to elucidate genomic landscapes underlying rrDLBCL; yet, high-throughput examination of resistance and relapse mechanisms within rrDLBCL subtypes, including the newly defined dark zone signature (DZsig) addition to cell of origin (COO), have yet to be described. To expand upon the current tumor etiology and define subtype-specific driving mechanisms, we describe a multi-omic analysis leveraging clinical and biologic variables in rrDLBCL. Methods: Tumor biopsies (N=228) collected at the time of relapse were obtained from n=85 participants in the Mayo Clinic/University of Iowa Lymphoma Molecular Epidemiology Resource (MER), n=73 in the Mayo Clinic Biobank, and n=38 from CC-122-DLBCL-001 or n=32 CC-122-ST-001 trials. Tumor samples were analyzed by WES (n=158) or WGS (n=70) and by RNAseq (n=145). Comparative analysis against ndDLBCL MER samples (N=444) utilized WES (n=404) and RNAseq (n=321). Chi Square or Fisher's exact test was used for enrichment analysis of categorical variables, while Wilcoxon or Kruskal-Wallis test was used for continuous variables. Results: rrDLBCL samples were enriched for ABC (46% vs 33% in ndDLBCL, p=0.01), and fewer GCB (27% vs 40%, p=0.006). Amongst rrDLBCL patients, variance in overall survival (from time of original diagnosis; log-rank p=0.001) was observed between COO subtypes, with poor outcomes in patients with DZsig (median 15.0 mo) and GCB (36.5 mo) compared to ABC tumors (74.4 mo). Patients with progression or relapse within 6 months featured a more even COO distribution (ABC - 22%, GCB - 34%, DZsig - 28%) than patients with early (6-24 mo; 51%, 22%, 22%) or late relapses (&gt;24 mo; 62%, 19%, 4%), which were predominantly ABC. Comparing mutation frequency within subtypes, rrDLBCL GCB tumors were enriched for B2M (41% vs 15% in ndDLBCL, p=0.002), EP300 (19% vs 7%, p=0.059), CIITA (19% vs 5%, p=0.02), PRKCB (11% vs 2%, p=0.035), CD79B (11% vs 0%, p=0.004), and CD83 (8% vs 1%, p=0.049) mutations, and CNV events including gains at 8q24.21 (MYC locus; 48% vs 14%, p&lt;0.001) and 18q21.33 (BCL2, TCF4 locus; 36% vs 15%, p=0.021), and losses at 17p13.1 (TP53 locus; 40% vs 19%, p=0.035). rrDLBCL DZsig tumors featured enrichment for BCL6 (22% vs 3%, p=0.025), and SPEN (17% vs 3%, p=0.062) mutations and 2q22.2 losses (LRP1B locus; 20% vs 0%, p=0.019). Despite differential mutation and CNV profiles, gene expression analysis revealed minimal variance within COO subtypes in rrDLBCL and ndDLBCL, however upregulation of lymphoma driving genes including MYBPC2 (LogFC=1.68, FDR&lt;0.001), MYOM2 (LogFC=1.33, FDR=0.007), MYC (LogFC=0.61, FDR=0.04), and CELSR2 (LogFC=0.53, FDR=0.02) were observed in ABC rrDLBCL. Increased frequency of LymphGen classifier A53 was observed in ABC (43% vs 17%, p=0.005) and GCB (40% vs 14%, p=0.009) rrDLBCL. Using CIBERSORTx to infer lymphoma microenvironment (LME) cell type abundance, an LME-depleted class was evident in rrDLBCL tumors, including reduction of CD8+ T cells (effect size (r)=-0.78, p&lt;0.001) and T follicular helper cells (r=-0.48, p=0.012) in GCB rrDLBCL and reduction of T follicular helper cells (r=-0.43, p=0.023) and Tregs (r=-0.32, p=0.065) in DZsig rrDLBCL. Significance: We present an update to the genomic landscape of rrDLBCL, highlighting GCB and DZsig tumors with differential biology and advanced clinical course. Our data supports increased implementation of sequencing efforts in rrDLBCL to more broadly evaluate relapse mechanisms, with optimism that a more detailed understanding of r/r disease may guide trials for targeted treatment strategies. For example, rrDLBCL patients may be strong candidates for MYC pathway targeting agents (BETi), or a Lenalidomide-based regimen (R2 or Tafa-Len), as Lenalidomide has been shown to reprogram the LME via PD-L1 expression in addition to downregulation of MYC and MYC target genes. Or, due to enrichment of variants affecting anti-apoptotic proteins including BCL6 or BCL2 in DZsig and GCB rrDLBCL, a venetoclax-based therapeutic may be considered. Further targeted strategies should be considered as development of a more personalized approach remains an unmet need.