King, Rebecca L.

Myeloid sarcoma (MS) is a tumor mass involving any extramedullary site composed of myeloid-lineage blasts with myeloid, myelomonocytic, or monocytic differentiation. Distinguishing MS from malignant histiocytic neoplasms (MHNs) is diagnostically challenging due to morphologic and immunophenotypic overlap, particularly for MS with monocytic differentiation, which can mimic MHNs, especially the subtypes of histiocytic sarcoma and interdigitating dendritic cell sarcoma, leading to potential misdiagnosis and inappropriate management. Cyclin D1 overexpression is implicated in MHNs, but its utility in differentiating these entities has not been systematically characterized. We evaluated cyclin D1 immunostaining in 43 MS cases and 30 MHNs. The median age at MS diagnosis was 59 years (range: 0.1 to 90), while the median age at MHN diagnosis was 62 years (range: 9 to 90), with heterogeneous sites of involvement. Cyclin D1 evaluation showed 100% MHNs with strong cyclin D1 positivity in ≥50% tumor cells, compared with 7% MS with weak-to-intermediate positivity in a minor subset of tumor cells. Additional immunohistochemical evaluation showed no difference in PU.1 expression in MHNs (93%) versus MS (84%) but demonstrated a higher proportion of OCT2-positivity in MHNs over MS (52% vs. 23%, P <0.05). Our study demonstrates a high sensitivity (100%) and specificity (93%) in utilizing cyclin D1 to distinguish MHNs (mature phenotype) from MS (immature phenotype) in diagnostic practice. It is particularly valuable in challenging scenarios of MS with the absence of immature/myeloid lineage-defining markers (MPO, CD34, or CD117) and provides a cost-effective tool to resolve this diagnostic pitfall, ensuring an accurate subclassification.

ABSTRACT 162 patients with relapsed secondary central nervous system lymphoma (R‐SCNSL) (median age, 65 years; male, 59.9%) including central nervous system (CNS)‐only ( n = 120) and concomitant CNS/systemic relapse ( n = 42) were retrospectively analyzed. Overall, 21.9% of patients were classified as high risk according to the CNS International Prognostic Index (CNS‐IPI). Several biological and clinical features were significantly associated with leptomeningeal involvement, including double‐ or triple‐hit (DHL/THL) status, MYC rearrangement, negative BCL6 expression by IHC, bone marrow involvement, and concomitant R‐SCNSL. Multivariable analysis showed that leptomeningeal involvement independently predicted inferior OS and was associated with a 98% increase in the hazard of death compared with parenchymal relapse (HR = 1.98, 95% CI: 1.20–3.26, p = 0.008). Based on anatomical localization, R‐SCNSL was classified into four subtypes: parenchymal‐only involvement (parenchymal‐CNS [P‐CNS], 68/42%) and parenchymal involvement plus systemic relapse (parenchymal‐concomitant [P‐concomitant], 17/10.5%); and leptomeningeal with or without parenchymal involvement (leptomeningeal‐CNS [LM‐CNS], 52/32.1%) and leptomeningeal with systemic relapse (leptomeningeal‐concomitant [LM‐concomitant], 25/15.4%). This anatomical classification significantly impacted OS and PFS ( p < 0.001). Two‐year OS and PFS were 58.2% and 29.1% for P‐CNS, 32.4% and 17.7% for P‐concomitant, 22% and 13.9% for LM‐CNS, and 7.1% and 0% for LM‐concomitant, respectively. ASCT showed a trend toward improved survival among patients with a response (CR/PR) in a 4‐month landmark analysis. These findings support the clinical application of the anatomical classification in the management of R‐SCNSL.

Introduction: Outcomes from multidisciplinary lymphoma tumor boards in the molecular era are limited, and the effects of transitioning to virtual formats during the COVID-19 pandemic are not well-documented. This study evaluates how the transition of the Mayo Clinic Lymphoma Tumor Board to a virtual format has impacted its effectiveness and operations. The board, part of the International Mayo Clinic Care Network (MCCN), involves case presentations, subspecialist reviews, and collaborative recommendations. Methods: The Mayo Clinic Lymphoma Tumor Board, an integral part of the Mayo Clinic Care Network (MCCN), conducted a comprehensive review of lymphoma cases from 2014 to 2024. The board's review process involves a structured approach including the presentation of clinical case details, radiology and hematopathology findings, proposed treatment options, relevant literature review, and discussions. From 2014 to 2024, the Mayo Clinic Lymphoma Tumor Board reviewed a total of 722 patients. The review process involves a multidisciplinary team, including physicians, pharmacists, clinical research associates, and trainees. Recommendations and changes related to radiology interpretation, pathologic diagnosis, and treatment approaches were documented and tracked prospectively. In March 2020, the board transitioned to a virtual format due to the COVID-19 pandemic. This shift allowed for remote participation and continued collaborative review while maintaining the board's structured approach and documentation practices. Results: In a total of 722 patients, changes in care were identified in 423 patients, including 287 with newly diagnosed lymphoma and 136 with relapse or refractory disease. Among those who experienced changes, 94 had diffuse large B-cell lymphoma, 49 had follicular lymphoma, 39 had marginal zone lymphoma, 36 had classical Hodgkin lymphoma, and 29 had mantle cell lymphoma. Prior to the COVID-19 pandemic, 431 patients were analyzed, with 217 (50.3%) experiencing changes. A total of 268 changes were documented among these patients. Changes in radiologic interpretation occurred in 9 patients (2.1% of 431 total patients). Pathologic diagnosis changes were noted in 42 patients (9.7%). Additional testing was recommended for 73 patients (16.9%), and clinical management was altered for 144 patients (33.4%). After transitioning to a virtual format, 291 patients were reviewed post-COVID, with 206 (70.8%) having recommended changes. The total number of change recommendations was 322, reflecting increases across all components compared to previous data, with adjustments for varying numbers of patients reviewed. Specifically, radiologic interpretation changes occurred in 21 patients (7.2%), pathologic diagnosis changes in 57 patients (19.6%), additional testing recommendations for 85 patients (29.2%), and clinical management alterations in 159 patients (54.7%). Conclusion: Transitioning to a virtual format in the Mayo Clinic Lymphoma Tumor Board's continued to demonstrate the effectiveness, with increased changes in diagnostic interpretations and clinical management. These results illustrate the potential of virtual tumor boards to improve collaborative decision-making and adapt to evolving clinical needs.

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.

ABSTRACTDiffuse large B‐cell lymphoma (DLBCL) patients that fail to achieve a complete metabolic response with frontline immunochemotherapy have a poor prognosis. Genomic profiling has led to a broader understanding of the molecular drivers in DLBCL, but it is unknown how well current classifiers identify patients that will experience primary treatment resistance (PTR). Using whole exome and RNA sequencing data from newly diagnosed DLBCL patients, we evaluated the genomic landscape of PTR and compared it to that of non‐PTR DLBCL. We found a significant increase in the frequency of TP53 (34% vs. 15%, p = 0.005) and ARID1A mutations (21% vs. 7%, p = 0.007) in PTR cases, with pathway analysis further demonstrating a downregulation of TP53 and an increase in chromatin modifying pathways. These results suggest that TP53 and ARID1A may be key mediators of PTR and important pathways contributing to the poor outcomes. We found that the current molecular classifiers were unable to identify PTR cases at diagnosis. However, our newly identified high‐risk signature identified 46% of PTR cases at diagnosis. Overall, these results contribute to our understanding of the genomic landscape of patients with primary treatment resistance.

Abstract Since the publication of the Revised European-American Classification of Lymphoid Neoplasms in 1994, subsequent updates of the classification of lymphoid neoplasms have been generated through iterative international efforts to achieve broad consensus among hematopathologists, geneticists, molecular scientists, and clinicians. Significant progress has recently been made in the characterization of malignancies of the immune system, with many new insights provided by genomic studies. They have led to this proposal. We have followed the same process that was successfully used for the third and fourth editions of the World Health Organization Classification of Hematologic Neoplasms. The definition, recommended studies, and criteria for the diagnosis of many entities have been extensively refined. Some categories considered provisional have now been upgraded to definite entities. Terminology for some diseases has been revised to adapt nomenclature to the current knowledge of their biology, but these modifications have been restricted to well-justified situations. Major findings from recent genomic studies have impacted the conceptual framework and diagnostic criteria for many disease entities. These changes will have an impact on optimal clinical management. The conclusions of this work are summarized in this report as the proposed International Consensus Classification of mature lymphoid, histiocytic, and dendritic cell tumors.