Bernal‐Mizrachi, Leon

Diffuse large B-cell lymphoma (DLBCL), the most common type of lymphoma, arises from various pathogenic mechanisms including gene translocations and fusions. Detection of gene rearrangements using fluorescence in situ hybridization (FISH) is a standard practice for DLBCL diagnosis and guides treatment decisions. High-throughput chromosome conformation capture (Hi-C) DNA sequencing is a next-generation sequencing-based technology to identify genome-wide rearrangements using a single assay. In this study, Hi-C sequencing was performed using FFPE tissues from 159 patients with DLBCL, and identified 746 cancer genes at or proximal to the rearrangement breakpoints with a total of 1903 occurrences. Focusing on clinically important rearrangements, Hi-C detected 102 rearrangements of MYC, BCL2, and/or BCL6 in 92 patients and revealed the fusion partners, including 25 rearrangements missed by FISH. Causes of FISH negative results included FISH-cryptic breakpoints, complex or faint FISH signals, low percentage of FISH positivity, and issues related to tissue fixation. Moreover, in 20 patients (12.6%), Hi-C sequencing detected 22 rearrangements characteristic of other lymphoma types, including CCND1 rearrangements that could lead to reclassification as mantle cell lymphoma. Survival analysis for genome-wide rearrangements using machine learning models identified MYC, PD-L1, CCND1, BCL2, NTRK1/PRCC, RRAS, and FANCE rearrangements with significant prognostic effects in the DLBCL cohort. In conclusion, Hi-C sequencing detects gene rearrangements crucial for diagnosis in an unbiased and molecular manner and showed high sensitivity and specificity in our study. These advantages of Hi-C sequencing offer help to improve the workflow of clinical pathology laboratories, diagnostic precision, and treatment of large B-cell lymphoma.

Abstract Introduction: Diffuse large B-cell lymphoma (DLBCL) is the most common type of malignant lymphoma. Previous studies have shown that DLBCL cells are susceptible to GPX4 (Glutathione peroxidase 4)-regulated ferroptosis, an iron-dependent type of programmed cell death characterized by increased reactive oxygen species and excessive lipid peroxidation. In addition to GPX4, FSP1 (Ferroptosis suppressor protein 1, previously known as AIFM2) is a glutathione-independent repressor of ferroptosis that has shown prognostic significance in solid tumors. In this study, we aimed to reveal the significance of GPX4 and FSP1 in DLBCL. Patients and Methods: We performed immunohistochemistry (IHC) for GPX4 and FSP1 in a large cohorts of patients with de novo DLBCL, and evaluated their cytoplasmic and nuclear expression. Prognostic analysis was performed for FSP1 and GPX4 expression in patients treated with rituximab (R)-CHOP or CHOP chemotherapy, respective of TP53 mutation status, as p53 regulates ferroptosis and TP53 mutation is associated with poorer prognosis in DLBCL. Results: FSP1 expression with a ≥10% cutoff was positive in 42.3% of DLBCL cases. Patients with TP53 mutations had a non-significant trend of higher mean FSP1 expression than those with wild-type (Wt) TP53 (P=0.11). Prognostic analysis revealed that cytoplasmic FSP1+ expression was associated with significantly poorer overall survival and progression-free survival in Wt-TP53 DLBCLs treated with R-CHOP (P=0.016 and P=0.003, respectively), and only showed non-significant unfavorable trends in TP53 mutated DLBCLs and patients treated with CHOP. In contrast, GPX4 expression did not show a significant unfavorable prognostic effect in DLBCL, and in fact, was associated with a non-significant trend of better survival. Previously we have quantified immune cell abundance and PD-1/PD-L1 expression in the tumor microenvironment of the study cohort using multiplex fluorescent IHC. Correlative analysis found that FSP1+ patients had significantly higher mean and median abundance of CD68+ cells (both M1 and M2 macrophages) and CD11c+ cells than FSP1- patients. Further analysis in Wt-TP53 and mutated TP53 subcohorts found that only in the TP53 mutated DLBCL subcohort, FSP1 expression was associated with significantly higher mean and median CD163-CD68+ (M1) and overall CD68+ macrophages, whereas in the Wt-TP53 DLBCL subcohort, FSP1 expression was associated with significantly higher median (but not mean) CD163+CD68+ (M2) macrophages and CD11c+ cells. Summary: Cytoplasmic FSP1 expression but not GPX4 had significantly adverse prognostic effect in patients with Wt-TP53 DLBCL treated with standard immunochemotherapy. Our results also suggest that in addition to ferroptosis regulation, macrophage abundance was relevant for the prognostic effects of FSP1 expression. Citation Format: Beibei Lyu, Zijun Xu-Monette, Xiaoxian X. Zhao, Eric D. Hsi, Ming Chen, Carlo Visco, Alexandar Tzankov, Karen Dybkaer, Mu-En Wang, Chang Wang, Qingyan Au, Harry Nunns, Zenggang Pan, Benjamin Parsons, Santiago Montes-Moreno, Fenghuang Zhan, Michael B. Møller, Leon Bernal-Mizrachi, Youli Zu, Shanxiang Zhang, Weina Chen, Govind Bhagat, Yong Li, KEN H. YOUNG. Expression of the ferroptosis suppressor FSP1 but not GPX4 shows significant adverse prognostic effect in diffuse large B-cell lymphoma with wild-type TP53 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4661.

Abstract Pyroptosis is a form of programmed cell death characterized by the cleavage of the gasdermin (GSDM) family proteins that form pores in the plasma membrane, cell rupture, and the release of proinflammatory cytokines. In this study, we performed immunohistochemistry for cleaved gasdermin D (GSDMD), gasdermin E (GSDME) N-terminus, and gasdermin C (GSDMC) in 2 different cohorts of diffuse large B-cell lymphoma (DLBCL) and analyzed the impact of GSDM expression on prognosis and immunity. The results showed frequent cleaved GSDMD (N-terminal) expression. Only cytoplasmic GSDMD N-terminal expression correlated with significantly better patient survival in the 2 cohorts. In contrast, GSDME was mainly expressed in the vascular endothelium, and correlated with significantly adverse prognostic effect. Correlating with the multiplex fluorescent immunohistochemistry results, we found that cytoplasmic GSDMD N-terminal expression was associated with increased CD38+ (activated) M1 macrophages in both cohorts, cognate interactions between live DLBCL cells and activated M1 macrophages (and T cells), and lower PD-1/PD-L1 expression in the analyzed cases. In contrast, T-cell pyroptosis, lymphoma cell-resistance to cell death, and phagocytosis by M2 macrophages were observed in tissues with predominantly nuclear GSDMD N-terminal expression. Bulk gene expression profiling and deconvolution analysis revealed associations of cytoplasmic GSDMD N-terminal expression with downregulation of “Don’t eat me”–signaling genes, upregulation of many RNA genes, decreased frequency of “inflammatory” lymphoma microenvironment subtype, increased frequencies of prognostically favorable cell states and ecotypes, and decreased frequency of T-cell exhaustion state. In summary, this study showed distinct cellular and subcellular patterns of 3 GSDM proteins and their associated immune response phenotypes and prognostic effects, with implications for novel therapeutic strategies for B-cell lymphoma.

Abstract Background: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma (NHL), accounting for approximately 30% of all NHL cases. DLBCL diagnosis relies on histologic examination, immunophenotyping, molecular and fluorescence in situ hybridization (FISH) analysis to differentiate it from similar NHL subtypes with overlapping morphological features, including more high-grade lymphomas like double-hit lymphoma. Because FISH is performed in a panel of single- or dual-target test format and analyzed through microscopy and manual image analysis, assessment of multiple target biomarkers can be cumbersome and expensive. As additional biomarkers for diagnosis, subtyping, prognosis, and therapeutic decision-making become available, target panels will become larger, posing additional challenges to clinical laboratories. Patients and Methods In this study, Hi-C sequencing of FFPE samples was performed to identify all genomic rearrangements by a single sequencing analysis for an unselected DLBCL case series of 159 patients, and the results were compared to FISH for the detection of clinically important variants. Results Hi-C sequencing showed superior performance compared to FISH: standard FISH for DLBCL includes testing for MYC, BCL2, and BCL6. Between FISH and Hi-C, these biomarkers were detected 105 times, of which, FISH detected 80/105 (76%) and Hi-C detected 102/105 (97%). The cohort included 4 double-hit lymphomas by FISH but Hi-C sequencing detected five. Besides DLBCL diagnostic biomarkers (MYC, BCL2, BCL6), many additional biomarkers were detected by Hi-C sequencing including variants not tested by FISH because the clinical suspicion was ambiguous and the relevant FISH probes were not used, and those not tested because the biomarkers were not thought to be common and, hence, left out of the FISH panel. In total, Hi-C sequencing detected additional biomarkers in 42 (26%) cases, including (1) variants targeted by FISH (i.e. MYC, BCL2, BCL6) but negative, (2) classification biomarkers for other lymphomas (CCND1, MALT, IRF4), and (3) those not tested because the biomarkers are not common and not included in the FISH panel. These additional biomarkers were supportive of suspected diagnosis of DLBCL versus double-hit lymphoma (24 cases), prompted reconsideration of a different diagnosis that may have led to different treatments (6 cases, e.g. mantle cell lymphoma), or biomarkers such as PDL1, ALK, and ATM which have implications for targeted therapies and/or inclusion in clinical trials (5 cases). Conclusion The Hi-C FFPE sequencing technology has the potential to improve the workflow of pathology labs for detection of a wide range of structural variants informing precision diagnosis and treatment for lymphomas.

Abstract Background: Pyroptosis is a form of programmed cell death characterized by cleavage of gasdermin (GSDM) family proteins that form pores in the plasma membrane, cell rupture, and release of pro-inflammatory cytokines. Its pro-inflammatory potential has garnered significant research attention in recent years but has not been studied in lymphoma. Patients and Methods: We performed immunohistochemistry for cleaved GSDMD (n-terminal) in two large cohorts of diffuse large B-cell lymphoma (DLBCL) with multiplex fluorescent IHC (mfIHC) data, and analyzed for prognostic and immune impact. Results: Cleaved GSDMD was frequently expressed in DLBCL, and only the cytoplasmic (versus nuclear) form of expression correlated with significantly better patient survival in two DLBCL cohorts. To understand the expression at the single-cell level, we examined mfIHC results, which revealed that GSDMD+cells were tumor or immune cells, and varied in Ki-67, BCL2, and MYC expression. Cases with cytoplasmic cleaved GSDMD expression had higher mean and median levels of CD38+ (activated) M1 macrophages in two cohorts and lower PD-1/PD-L1 expression, as well as phenotypes of cognate interactions between live activated M1 macrophages, DLBCL cells, and T cells in spatially resolved immune landscape by mfIHC. In contrast, phagocytosis of pyroptotic lymphoma cells by M2 macrophages and cell death of T cells were observed in cases with predominantly nuclear form of cleaved GSDMD expression. Bulk gene expression profiling analysis identified a large proportion of RNA genes upregulated in DLBCLs with cytoplasmic cleaved GSDMD expression, and deconvolution analysis found decreased frequency of the “Inflammatory” lymphoma microenvironment (LME) subtype, increased frequency of cell states and ecotypes with favorable prognostic associations, and decreased frequency of T cell exhaustion states. Summary: Analysis of pyroptosis-inducing cleaved GSDMD (n-terminal) expression in a large number of DLBCL patients revealed dinstinctive cytoplasmic and nuclear expression patterns in live and pyroptotic cells associated with different prognostic and immune effects. Cytoplasmic cleaved GSDMD expression is a marker of cognate interactions between live cells (e.g., activated M1 macrophages) associated with adaptive responses and favorable prognostic effects, whereas nuclear cleaved GSDMD expression is associated with immunosuppressive mechanisms, including T cell death and phagocytosis by M2 macrophages.

AbstractTo address the current and long‐term unmet health needs of the growing population of non‐Hodgkin lymphoma (NHL) patients, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/). A total of 7735 newly diagnosed patients aged 18 years and older with NHL were prospectively enrolled from 7/1/2015 to 5/31/2020 at 8 academic centers in the United States. The median age at diagnosis was 62 years (range, 18–99). Participants came from 49 US states and included 538 Black/African‐Americans (AA), 822 Hispanics (regardless of race), 3386 women, 716 age <40 years, and 1513 rural residents. At study baseline, we abstracted clinical, pathology, and treatment data; banked serum/plasma (N = 5883, 76.0%) and germline DNA (N = 5465, 70.7%); constructed tissue microarrays for four major NHL subtypes (N = 1189); and collected quality of life (N = 5281, 68.3%) and epidemiologic risk factor (N = 4489, 58.0%) data. Through August 2022, there were 1492 deaths. Compared to population‐based SEER data (2015–2019), LEO participants had a similar distribution of gender, AA race, Hispanic ethnicity, and NHL subtype, while LEO was underrepresented for patients who were Asian and aged 80 years and above. Observed overall survival rates for LEO at 1 and 2 years were similar to population‐based SEER rates for indolent B‐cell (follicular and marginal zone) and T‐cell lymphomas, but were 10%–15% higher than SEER rates for aggressive B‐cell subtypes (diffuse large B‐cell and mantle cell). The LEO cohort is a robust and comprehensive national resource to address the role of clinical, tumor, host genetic, epidemiologic, and other biologic factors in NHL prognosis and survivorship.

Abstract Background: Persons of African ancestry (AA) experience a 1.5-2-fold risk of multiple myeloma (MM) compared to persons of European ancestry (EA). We assembled a set of MM patients with self-reported AA in order to evaluate the contribution of genetics to etiology in this high-risk group. Methods: Here we present the results of a meta-analysis of two GWAS in 1,813 cases and 8,871 controls of AA. We also conducted an admixture mapping scan to identify risk alleles associated with local ancestry, fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA, and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. Finally, we conducted an eQTL analysis measuring gene expression in those genes harboring a risk variant in malignant plasma cells from 292 of the patients from a single site. Results: In GWAS analysis, we identified two suggestive novel loci located at 9p24.3 and 9p13.1 at P&lt;1 × 10-6, but no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. 20 of the 23 known EA risk variants showed directional consistency and 9 replicated at P&lt;0.05 in AA individuals. In eight regions, we identified markers that better capture MM risk in persons of AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95%CI: 1.56, 2.11) increased MM risk compared to those with average risk (25-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P= 5.1 × 10–12). Conclusion: Our study shows that common genetic variation contributes to MM risk individuals of AA. This abstract is also being presented as Poster C040. Citation Format: Zhaohui Du, Niels Weinhold, Gregory Chi Song, Kristen A. Rand, David J. Van Den Berg, Amie E. Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William J. Blot, Graham Casey, Victoria L. Stevens, Rick Kittles, Phyllis J. Goodman, W. Ryan Diver, Anselm Hennis, Barbara Nemesure, Eric A. Klein, Benjamin A. Rybicki, Janet L. Stanford, John S. Witte, Lisa Signorello, Esther M. John, Leslie Bernstein, Antoinette Stroup, Owen W. Stephens, Maurizio Zangari, Frits Van Rhee, Andrew Olshan, Wei Zheng, Jennifer J. Hu, Regina Ziegler, Sarah J. Nyante, Sue Ann Ingles, Michael Press, John David Carpten, Stephen Chanock, Jayesh Mehta, Graham A Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Kenneth C. Anderson, Loic Le Marchand, Daniel Auclair, Brian C.-H. Chiu, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, Wendy Cozen. A meta-analysis of genome-wide association study and eQTL analysis of multiple myeloma among African Americans [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr PR05.

Purpose: Multiple myeloma (MM) treatment has changed tremendously, with significant improvement in patient out-comes. One group with a suboptimal benefit is patients with high-risk cytogenetics, as tested by conventional karyotyping or fluorescence in situ hybridization (FISH). Methodology for these tests has been published, but not necessarily standardized. Methods: We address variability in the testing and reporting methodology for MM cytogenetics in the United States using the ongoing African American Multiple Myeloma Study (AAMMS). We evaluated clinical and cytogenetic data from 1,221 patients (1,161 with conventional karyotyping and 976 with FISH) tested between 1998 and 2016 across 58 laboratories nationwide. Results: Interlab and intralab variability was noted for the number of cells analyzed for karyotyping, with a significantly higher number of cells analyzed in patients in whom cytogenetics were normal (P 5.0025). For FISH testing, CD138-positive cell enrichment was used in 29.7% of patients and no enrichment in 50% of patients, whereas the remainder had unknown status. A significantly smaller number of cells was analyzed for patients in which CD138 cell enrichment was used compared with those without such enrichment (median, 50 v 200; P, .0001). A median of 7 loci probes (range, 1-16) were used for FISH testing across all laboratories, with variability in the loci probed even within a given laboratory. Chromosome 13–related abnormalities were the most frequently tested abnormality (n5956; 97.9%), and t(14;16) was the least frequently tested abnormality (n 5 119; 12.2%). Conclusions: We report significant variability in cytogenetic testing across the United States for MM, potentially leading to variability in risk stratification, with possible clinical implications and personalized treatment approaches.

Abstract Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P &lt; 1 × 10−6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P &lt; .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10−12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.

Multiple myeloma (MM) is a neoplasm thought to arise from a damaged germinal center B-cell that progresses to a plasma cell clone arising in bone marrow. MM comprises 20% of all hematologic cancer deaths. Persons of African ancestry (AA) have a 1.5 to 2-fold higher risk compared to individuals of European ancestry (EA). Genetically driven differences in hematopoiesis may lead to variation in the levels white blood cell (WBC) subsets which could, in turn, be associated with MM etiology. There are differences in genetic determinants of WBC traits between EA and AA populations, with possible implications for the racial disparity in risk. We tested the above hypothesis using Mendelian randomization (MR), an approach that leverages genetic determinants of specific traits (i.e. WBC counts) to estimate their effects on the risk of an outcome; and a transcriptome-wide association study (TWAS), which utilizes genetic predictors of gene expression to identify susceptibility genes. These analytic approaches were applied to data from the African American Multiple Myeloma Study (AAMMS) consisting of 1813 cases and 8871 AA cancer-free controls to examine how differences in heritable WBC gene expression profiles influence MM risk. Genetic determinants of variation in WBC subsets in AA were obtained from the literature and supplemented with new genome-wide association findings in AA subjects from the UK Biobank cohort (n=6108). Odds ratios (OR) for MM per 1 standard deviation (SD) increase in each WBC phenotype were estimated using independent (linkage disequilibrium (LD) r2<0.10) variants with P<10-6 as genetic instruments. Analyses based on variants associated with WBC traits in AA populations did not identify any statistically-significant associations between MM risk and WBC overall (p=0.81, using 15 SNPs) or subsets (lymphocytes, monocytes, eosinophils, neutrophils and basophils, p>0.05 for each). However, when we applied genetic determinants of WBC identified in 330,000 cancer-free EA UK Biobank participants (P<10-8, replication P<0.05, LD r2<0.05), a statistically significant inverse relationship emerged between increasing lymphocyte counts and MM risk (OR=0.80, 95% CI: 0.66-0.97, p=0.02, using 385 SNPs), as well as increasing basophil counts (OR=0.63, 95% CI: 0.41-0.96, p=0.03, using 140 SNPs). Next, we examined the association between WBC gene expression profiles and MM risk in AAMMS data. We applied published and validated ancestry-specific models developed using the PrediXcan approach, which leverage germline genetic and transcriptomic data from the Multi-Ethnic Study of Atherosclerosis (MESA) (Mogil et al. PMID: 30096133). The primary TWAS used gene expression models trained in AA subjects (n=233), with sensitivity analyses using models developed in AA and Hispanic subjects (n=585). The TWAS significance threshold was based on the number of genes with significant germline prediction models (p<0.05 and R2 ≥0.05) in AA, corresponding to P < 0.05/2700 = 1.85×10-5. The expression of two genes was significantly associated with MM risk: KANK1at 9p24.3 (P = 1.01×10-5) and DNAJC27at 2p23.3 (P = 1.56×10-5). KANK1is a candidate tumor suppressor gene for renal cell carcinoma and has recently been associated with MM risk in AA [Du, Blood 2017 130:3058]. Here we provide additional evidence for its role in MM etiology via gene expression-mediated mechanisms. DNAJC27 (previously known as RBJ) is a novel MM risk gene linked to constitutive activation of ERK in solid tumors. We also identified two suggestively associated genes: PRR14 (P = 1.34×10-4; combined AA-Hispanic sample: P = 1.56×10-6), which has been linked to MM risk in EA populations, and PARP16 (P = 9.46×10-5). To our knowledge this is the first study to comprehensively examine variation in WBC traits and gene expression profiles with respect to MM risk in AA. Our TWAS analysis leveraged data from the largest collection of genetic and gene expression data in AA, enabling ancestry-matched inference and identification of two novel risk genes. Although the limited availability of genetic instruments for WBC limited the power of MR analysis, findings using variants identified in European populations may offer some insight into trans-ethnic etiologic pathways and contribute to risk stratification strategies using genetic and blood cell count biomarkers. Future studies, particularly with MGUS-free controls, are needed to validate these results. Disclosures Song: Millennium Pharmaceuticals Inc: Employment. Rand:Ancestry.com: Employment. Ailawadhi:Cellectar: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy; Pharmacyclics: Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy. Nooka:Takeda: Honoraria, Other: advisory board participation; Janssen: Honoraria, Other: advisory board participation; GSK: Honoraria, Other: advisory board participation; Spectrum pharmaceuticals: Honoraria, Other: advisory board participation; Adaptive technologies: Honoraria, Other: advisory board participation; Amgen: Honoraria, Other: advisory board participation; Celgene: Honoraria, Other: advisory board participation; BMS: Honoraria, Other: advisory board participation. Singhal:Bureau of Millennium/Takeda, Celgene, Janssen, Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. van Rhee:Takeda: Consultancy; Sanofi Genzyme: Consultancy; Castleman Disease Collaborative Network: Consultancy; EUSA: Consultancy; Adicet Bio: Consultancy; Kite Pharma: Consultancy; Karyopharm Therapeutics: Consultancy. Mehta:Millennium/Takeda, Celgene; stock in Celgene, Bristol-Myers Squibb and Bluebird: Speakers Bureau. Wolf:Takeda: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Janssen: Consultancy; Amgen: Consultancy. Martin:Roche and Juno: Consultancy; Amgen, Sanofi, Seattle Genetics: Research Funding. Fiala:Incyte: Research Funding. Terebelo:Jannsen: Speakers Bureau; Celgene: Honoraria; Newland Medical Asociates: Employment. Anderson:Bristol-Myers Squibb: Other: Scientific Founder; Oncopep: Other: Scientific Founder; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Sanofi-Aventis: Other: Advisory Board. Vij:Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Genentech: Honoraria; Janssen: Honoraria; Karyopharm: Honoraria; Sanofi: Honoraria; Takeda: Honoraria, Research Funding. Bernal-Mizrachi:TAKEDA: Research Funding; Kodikas Therapeutic Solutions, Inc: Equity Ownership; Winship Cancer Institute: Employment, Patents & Royalties. Morgan:Amgen, Roche, Abbvie, Takeda, Celgene, Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Other: research grant, Research Funding. Zonder:Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Intellia: Consultancy, Membership on an entity's Board of Directors or advisory committees; Caelum: Consultancy, Membership on an entity's Board of Directors or advisory committees; Alnylam: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees. Huff:Member of Safety Monitoring Board for Johnson and Johnson: Membership on an entity's Board of Directors or advisory committees; Karyopharm, Sanofi, MiDiagnostics: Consultancy. Lonial:Karyopharm: Consultancy; Takeda: Consultancy, Research Funding; Amgen: Consultancy; BMS: Consultancy; Janssen: Consultancy, Research Funding; GSK: Consultancy; Celgene Corporation: Consultancy, Research Funding; Genentech: Consultancy. Orlowski:Poseida Therapeutics, Inc.: Research Funding.