Zhan, Fenghuang

Despite significant improvements in survival of patients with multiple myeloma (MM), outcomes remain heterogeneous, and a significant proportion of patients experience suboptimal outcomes. Importantly, traditional prognostic factors based on data from patients treated with older therapies no longer capture prognosis accurately in the contemporary era of novel triplet or quadruplet therapies. Therefore, risk stratification requires refinement in the context of available and investigational treatment options in routine practice and clinical trials, respectively. The current identification of high-risk MM (HRMM) in routine practice is based on the Revised International Staging System, which stratifies patients using a combination of widely available serum biomarkers and chromosomal abnormalities assessed via fluorescence in situ hybridization. In recent years, a substantial body of evidence concerning additional clinical, biological, and molecular/genomic prognostic factors has accumulated, along with new MM risk stratification tools and consensus reports. The International Myeloma Society, along with the International Myeloma Working Group, convened an Expert Panel with the primary aim of revisiting the definition of HRMM and formulating a practical and data-driven consensus definition, based on new evidence from molecular/genomic assays, updated clinical data, and contemporary risk stratification concepts. The Panel proposes the following Consensus Genomic Staging (CGS) of HRMM which relies upon the presence of at least one of these abnormalities: (1) del(17p), with a cutoff of >20% clonal fraction, and/or TP53 mutation; (2) an IgH translocation including t(4;14), t(14;16), or t(14;20) along with 1q+ and/or del(1p32); (3) monoallelic del(1p32) along with 1q+ or biallelic del(1p32); or (4) β2 microglobulin ≥5.5 mg/L with normal creatinine (<1.2 mg/dL).

Introduction: Primary diffuse large B-cell lymphoma (DLBCL) of the central nervous system (CNS), traditionally referred to as primary CNS lymphoma (PCNSL), is a rare type of primary large B-cell lymphoma of immune-privileged sites with significantly poorer prognosis than systemic DLBCL. Genetic profiles of PCNSL were widely studied, whereas the tumor microenvironment has not been well characterized. Patients and Methods: A series of molecular analyses were performed using DLBCL FFPE tissues collected by the International Lymphoma Consortium. First, multiplex fluorescent immunohistochemistry (mfIHC) using antibodies for CD20, PAX5, CD3, CD4, CD8, FOXP3, CD45RO, CD68, CD56, PD-1, PD-L1, PD-L2, and CTLA-4 was performed on PCNSL tissues from 121 immunocompetent patients and de novo systemic DLBCL tissues from 405 patients. Digital quantification results for 405 patients with EBV-negative systemic DLBCL or primary testicular (PT) DLBCL have been reported previously. The preliminary mfIHC results of PCNSL will be presented. Second, mfIHC for multiple B cell biomarkers, CD3, CD4, CD8, CD68, CD163, CD11c, and CD31 were performed for 10 PCNSL validation cases, 24 PT-DLBCL and 451 systemic DLBCL tissues (unpublished). Third, RNA samples were extracted and sequenced for the targeted 1408 cancer-associated genes, successfully in 142 PCNSL cases, including 102 cases evaluated by either of these two mfIHC panels and additional 40 PCNSL cases, Results: First, in the first large mfIHC cohort, PCNSLs compared with de novo systemic nodal or extranodal DLBCL had significantly higher mean/median CD56+ cell densities whereas lower T cell densities (consistent with the immune privilege), as well as lower CD45RO+, PD-1+, and FOXP3+ percentages in T cells whereas higher CD4¯CD8¯ double-negative percentages in T cells. Prognostic analysis in the PCNSL cohort showed that high CD56+ cell densities and high CD45RO+CD8+ T cell densities were associated with significantly poorer and better patient survival, respectively, which are opposite to their prognostic effects in systemic DLBCL as previously reported. Twelve patients had very high PD-L1 expression in B cells and significantly poorer survival in the PCNSL cohort. Second, as validation, the 10 PCNSL cases in the second mfIHC study showed significantly less T cells than systemic DLBCL and PT-DLBCL cases, and low CD8 T cell densities and having low percentage of CD8 T cells adjacent to tumor cells were associated with significantly poorer survival. Immunofluorescence landscapeand spatial analysisrevealed significant differences in immune privilege between PCNSL and PT-DLBCL. Third, gene expression profiling analysis by targeted RNA-seq identified 282 significantly differentially expressed genes between PCNSL and systemic DLBCL, referred to as the PCNSL signature. Unsupervised clustering analysis divided the PCNSL cohort into two clusters, which had no significant difference in MYD88 mutation frequencies analyzed at the mRNA level. Importantly, the cluster with higher expression of many neural glial genes in the PCNSL signature had significantly poorer survival, which remained significant in multivariate analysis adjusting for clinical factors and/or treatments, two PCNSL subcohorts (as training and validation cohorts), and methotrexate-treated patients. NCAM1 (Neural Cell Adhesion Molecule 1, encoding CD56) was among the upregulated PCNSL signature genes, explaining the poorer prognosis associated with higher CD56+ cell densities in PCNSL by the mfIHC analysis. Summary: Our studies represent the largest immunophenotypic and gene expression profiling studies currently in PCNSL, a rare type of primary DLBCL of immune-privileged sites. Multiplex immunofluorescence revealed the immune landscape in PCNSL in comparison with systemic and testicular DLBCL, and identified prognostic immune biomarkers. Targeted RNA-seq identified a PCNSL gene signature enriched with neuronal-glial genes and showing significant prognostic effect in PCNSL. These novel findings in the PCNSL microenvironment warrant further studies.

Introduction Despite the remarkable success of combination treatments, multiple myeloma (MM) still poses significant challenges, with a high percentage of patients experiencing relapse over time. Additional metabolic alterations are found in relapsed and refractory MM; however, their impacts have not been fully elucidated. Expression of thyroid hormone receptor interactor 13 (TRIP13) has been identified by Gene Expression Profile (GEP)-70 to correlate with poor prognosis in MM. TRIP13 is an AAA ATPase that regulates the spindle assembly checkpoint in mitosis. Based on GEP data from 34 paired baseline and relapse samples, TRIP13 continuously increased from baseline to first and to second relapse. Overexpression of TRIP13 induces bortezomib resistance. In this study, we aimed to investigate how TRIP13 might regulate MM cell metabolism and to use this information to develop a novel combination strategy to overcome MM resistance. Methods Knockout (KO) of TRIP13 in OPM2 and MM1.S cells was generated by dual gRNAs CRISPR-Cas9 editing deleting a fragment between exon 4 and exon 5. Cell growth curves and response to bortezomib were recorded in the control and TRIP13-KO cells. Metabolomics was performed to reveal cellular metabolic alterations. Seahorse analysis was used to test the mitochondrial stress and glycolysis stress. To investigate whether TRIP13 KO promotes ferroptosis, an intracellular iron-dependent cell death characterized by the accumulation of lipid peroxides, we applied C11-BODIY staining after treatment with Erastin, a ferroptosis-inducer. Expression levels of cyclooxygenase 2 (encoded by PTGS2, a hallmark of ferroptosis), cystine transporter (xCT), and intracellular glutathione peroxidase 4 (GPX4) were analyzed. In addition, the protein levels of iron metabolic molecules, including iron importer transferrin receptor protein 1 (TFRC), iron exporter ferroportin 1 (FPN1), ferritin heavy chain 1 (FTH1), and nuclear receptor coactivator 4 (NCOA4) were assessed. To study whether TRIP13 KO delays MM progression in an immune-competent MM mouse model, Vκ12653 murine MM cells were genetically modified by CRISPR-mediated TRIP13-KO and then injected into C57BL/6 mice. Mouse survival was monitored. Results The cell-doubling rate of TRIP13-KO cells was decreased by 50% compared to control cells. After 24 hours of treatment with 5 nM bortezomib, cell viability of TRIP13-KO cells decreased by 31% compared with control cells. The metabolomic studies revealed that TRIP13-KO OPM2 and MM1.S cells both had significantly decreased intracellular L-serine (FC = 0.57) but increased pyruvate (FC = 1.79), citric acid (FC = 1.76), and isocitric acid (FC = 1.64), indicating TRIP13 may regulate serine metabolism, mitochondrial function, and cellular redox balance. Seahorse analysis indicated that TRIP13-KO MM cells showed decreased glycolysis (decreased by 30%, p &lt; 0.001) and glycolytic capacity (decreased by 33%, p &lt; 0.001) while oxidative phosphorylation showed little change. Moreover, lipid peroxidation and PTGS2 were increased in TRIP13-KO cells after Erastin treatment, indicating that these cells were more vulnerable to ferroptosis. Mechanistically, inhibition of TRIP13 decreased GPX4, FPN1, FTH1, and increased NCOA4, while overexpression of TRIP13 showed the opposite changes, suggesting that targeting TRIP13 sensitizes MM cells to ferroptosis by impairing cellular redox balance and increasing the labile-iron pool. Lastly, TRIP13-KO significantly prolonged mouse survival in the Vκ12653 mouse model (median survival: TRIP13-KO 93 days vs. Control 60.5 days, p &lt; 0.001). Conclusion Our study revealed that TRIP13 plays a critical role in regulating MM cell metabolism. By suppressing TRIP13, we observed increased sensitivity of MM cells to bortezomib, leading to enhanced ferroptosis-mediated cell death and prolonged mouse survival. These findings strongly suggest that targeting TRIP13 could be a promising approach in MM therapy. Moving forward, our future investigations will concentrate on unraveling the precise molecular mechanisms underlying TRIP13-mediated alterations in cell metabolism. Additionally, we plan to explore the potential synergistic effects of TRIP13 inhibition in combination with metabolic targeted treatments, such as venetoclax, to further enhance therapeutic outcomes in MM.

8521 Background: Several clinical and molecular prognostic factors (e.g, International Staging System [ISS] stage, plasma cell labeling index, genomic models) exist for multiple myeloma (MM). We hypothesized that exploiting gene signatures representative of oncogenic pathway deregulation (i.e., Ras, Myc, etc.), would improve MM prognostication and also aid with the identification of novel therapeutic targets. Methods: Using a discovery cohort (n=47) of patients with MM and corresponding gene expression data, we built upon current molecular risk-stratification and devised a Bayesian genomic (“metagene”) model for prognosis. We validated that model in an independent patient cohort (n=207). Finally, we incorporated ISS staging and clinical variables to construct a combined Clinico-Genomic Risk Stratification System. We further validated the combined model in a separate cohort (n=72), in a blinded manner. Results: Using gene signatures predictive of oncogenic pathway activation in the discovery cohort, we identified specific patterns (metagenes) of signaling pathway activation with prognostic relevance. In an independent validation cohort, this metagene-based model accurately predicted event free survival (EFS) independently of ISS (multivariate hazard ratio [HR] 3.4 for ISS stage, and 5.4 for the metagene model, p=0.002). Using multivariate risk modeling, we incorporated ISS staging and the metagene model into a Clinico-Genomic System and successfully stratified the validation cohort into three groups (low, intermediate, and high risk) with markedly different EFS (HR 4.2 for intermediate risk and 14.0 for high risk vs. the low risk cohort, p<0.0001). In an additional blinded validation, the Clinico-Genomic System again accurately predicted median overall survival (68.7 [low risk] vs 24.7 [intermediate risk] vs 18.7 months [high risk], p<0.0001); more accurately than either ISS or other reported genomic models. Conclusions: A combined Clinico-Genomic Risk Stratification System, building on patterns of oncogenic pathway activation and ISS staging system, improves upon current prognostic models in MM and identifies novel pathway targets for future therapeutic consideration. No significant financial relationships to disclose.

Abstract Glucocorticoid (GC) is an effective anti-myeloma agent by directly inducing apoptosis and growth inhibition in myeloma cells. The anti-myeloma action of GC is mediated by its intracellular receptor, the glucocorticoid receptor (GR). The response to GC is variable among myeloma patients and resistance to glucocorticoid treatment develops almost invariably. The mechanism regulating glucocorticoid-sensitivity in not well understood, although it has been hypothesized that the regulation might occur at both the receptor (GR) and post-receptor level. In MM.1 myeloma cell lines, we observed significant down-regulation of GR expression as the cells develop GC-resistance, suggesting that GR expression level is an important determinant of GC-response. Here we present evidence that GR expression level directly correlates with the clinical outcome in myeloma patients who were treated with GC-containing regimens. First, using a quantitative real-time PCR analysis, we performed a retrospective analysis of GR gene expression on bone marrow plasma cell samples from 35 patients with newly diagnosed myeloma who were then treated on the ECOG study E1A00. This is a phase 3 trial which randomized patients to dexamethasone (dex) alone vs. dex in combination with thalidomide. Pre-treatment expression levels of GR-alpha, GR-beta and GR-P splicing isoforms were measured for 35 patients, of whom, 10 had post-treatment samples available. Interestingly, a large variation of the GR expression levels was observed across the patient samples, with the GR-alpha being the predominant isoform. However, a clear correlation between GR expression and treatment response was not seen, likely due to the small sample size. To access a larger patient pool, we retrospectively analyzed the GR expression levels using the cDNA microarray data from the Arkansas group on 351 newly diagnosed myeloma patients treated with Total Therapy 2, of which dexamethasone was an essential component throughout the treatment course. Of the 351 patients, both event-free (EFS) and overall survivals (OS) were compared between 49 patients (14%) with low levels of GR expression and the rest (86%) with high levels of GR expression. Strikingly, the cases with low levels of GR expression were associated with statistically significantly worse EFS and OS compared to those with high levels of GR expression, with the 5-year EFS of 20% vs. 52% and OS of 34% vs. 68%, P &lt; 0.01. In summary, we have shown for the first time that the baseline level of glucocorticoid receptor expression in newly diagnosed myeloma patients predicts their clinical response to GC-containing regimen and the overall clinical outcome.

Conventional therapies to multiple myeloma (MM) are not aimed at specific molecular targets leading ultimately to treatment resistance. Recent reports have shown that iron is instrumental in cancer development and progression and that high intracellular iron levels are associated with poor prognosis. We have demonstrated that MM cells exhibit dysregulated iron homeostasis and that limitation of cytosolic iron inhibits MM cell growth both in vitro and in vivo. The potential therapeutic role of iron should be further investigated to better understand how targeting high-iron MM cells could prevent or delay MM development and recurrence. Our study will provide crucial insights into the iron biology of MM pathogenesis and may lead to novel MM therapy. In this study, two mouse models, young Vk*MYC and old KaLwRij mice, were injected with iron dextran (1.25 mg/kg, IP, once a week). Tumor burden was monitored by serial Serum Protein Electrophoresis (SPEP) tests, flow cytometry, and immunohistochemistry. In vitro co-culturing of ARP1 MM cells with macrophages was employed to determine iron transfer. To determine iron's roles in MM evolution, we injected iron dextran into Vk*MYC mice at 8-week age. Vk*MYC mice develop MGUS around 40-50 weeks with plasma cell (PC) bone marrow infiltration and kidney damage etc. Iron-dextran was used because it is primarily taken up by macrophages. After 14-16 weeks of iron injection, M spike was detected in the injected Vk*MYC mice. The percentage of bone marrow plasma cells (CD138+) were significantly increased to 9% in the Vk*MYC mice injected with iron compared to control mice injected with vehicle by flow cytometry and immunohistochemistry. The acceleration of disease progression via iron injection was also tested in KaLwRij mice, which also spontaneously develops MGUS in old age. M protein was detected in 12 of 15 mice (80%) injected with iron dextran for 10 weeks and 1 of 5 KaLwRij (20%) control mice at 18-months of age. CD138+ B220- plasma cells were determined by flow cytometry. A significant increase of CD138+B220- plasma cells in iron treated mice (4% versus 2%) was observed compared to vehicle control mice. Deparaffined sections of bone marrow from the above mice were stained with Prussian blue and confirmed positive staining of macrophages from iron administrated mice. These results indicate that iron accelerates MGUS development in vivo. We next evaluated whether MM cells accumulate iron from the microenvironment. ARP1 MM cells were co-cultured with primary macrophages derived from mouse bone marrow to mimic disease environment in vitro. Under these conditions, MM cells induced macrophage polarization from M0 to M1 and M2. Furthermore, increased macrophage polarization was confirmed in vivo from the KaLwRij mice injected with 5TGM1 MM cells. To confirm that MM cells uptake iron from macrophages, increased intracellular ferritin levels were observed by western blot in ARP1 MM cells following co-culture with iron-loaded macrophages. We observed that this increase in intracellular ferritin was mediated via the transferrin receptor. This iron mobilization was prevented by iron chelation. Additionally, we confirmed that ferritin levels were higher in CD138+ primary human MM cells compared to CD138- non-MM cells by western blot. Our data indicate that MM cells promote macrophage polarization resulting in the transferring of iron into MM cells. The blockade of iron trafficking between MM cells and macrophages might hold a promise for the prevention and therapy in MM. Disclosures Bergsagel: Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy. Zhan:BIPHARM LLC: Consultancy, Other: % Allocation of Profit.

Abstract Abstract 2865 Poster Board II-841 BACKGROUND: The ubiquitin-proteasome pathway, which has been shown to be an essential cellular degradative system in myeloma cells, can also regulate bone formation through its effects on osteoblast differentiation. Retrospective analysis of variation of ALP during treatment with bortezomib indicates a close correlation between myeloma response and serum ALP levels which multiple studies have shown to be of bone origin. To determine if this effect is a class effect of proteasome inhibitors (PIs), this retrospective study analyzed variation of ALP in relationship to myeloma response during treatment with carfilzomib, the first in a new class of selective epoxyketone PIs that has demonstrated encouraging safety and efficacy in two phase 2 studies of relapsed or refractory myeloma patients. METHODS: Retrospective analysis of serum ALP was performed on relapsed or refractory myeloma patients enrolled on two phase 2 studies (PX-171-003 and PX- 171-004) evaluating the safety and efficacy of single agent carfilzomib. We analyzed data from 38 patients in the first cohort of the PX-171-003 study, a relapsed and refractory myeloma trial for patients who have received ≥ 3 prior therapies including bortezomib and an IMiD and 29 patients in PX-171-004, a relapsed or refractory myeloma trial that included bortezomib naïve patients. All patients received 20 mg/m2 of carfilzomib on Days 1, 2, 8, 9, 15, and 16 of a 28-day cycle. RESULTS: Seventy-seven patients were enrolled. The median age was 63 years with a median time since diagnosis of 4.6 years, 52% were male, 84.% had relapsed after autologous transplants, 82.% were previously exposed to bortezomib, and 92% were previously exposed to an IMiD. Sixty seven patients with ALP data were evaluable for response. In PX-171-003 the ORR (≥PR) was 18% and the clinical benefit response (CBR; ≥MR) was 26%, while in PX-171-004 the ORR was 35.5% overall and 57% in bortezomib naive patients. ALP increment from baseline, which was most evident during the second cycle of treatment, was statistically different in patients who achieved ≥VGPR compared to all others on Days 1 (P=0.0049) and 8 (P=0.006) of Cycle 2. In all patients achieving a VGPR or better, ALP increased more than 15 units per liter at Cycle 2 Day 1 over baseline An ALP increase over the same period of time was seen in 26 %, 13%, and 11% of patients achieving PR, MR, and SD, respectively. None of the patients with progressive disease exhibited a similar increase. Our study indicates that response first assessed on Day 15 of Cycle 1 parallels the ALP elevation which returned to baseline levels at the end of Cycle 3. CONCLUSIONS: This retrospective analysis on a subset of patients in these ongoing phase 2 studies of single agent carfilzomib in relapsed or refractory multiple myeloma suggests that elevation in ALP may be associated with best response. Taken with previous publications describing bortezomib treatment, these results suggest that this specific anabolic bone phenomenon could be a class effect of proteasome inhibitors. These phase 2 studies are ongoing with a higher dose of carfilzomib (27 mg/m2) being evaluated. The data from this small subset analysis suggests that further exploration of this relationship is warranted. Disclosures: Zangari: Milllennium: Honoraria, Research Funding; Novartis: Research Funding; Celgene: Honoraria; OrthoBiotech: Honoraria; Optum Health: Honoraria; Educational Concepts Group, LLC: Membership on an entity's Board of Directors or advisory committees. Vij:Proteolix: Consultancy, Research Funding. Jagannath:Millennium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria; Merck: Honoraria. Siegel:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Millennium: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Stewart:Millennium: Consultancy, Research Funding; Proteolix: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Celgene: Honoraria. Wang:Proteolix: Honoraria, Research Funding. Belch:Ortho Biotech: Honoraria, Research Funding. Jakubowiak:Millennium Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Centocor Ortho Biotech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Exelixis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol-Myers-Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Trudel:Celgene: Honoraria, Speakers Bureau; Ortho Biotech: Honoraria. Bahlis:Celgene: Honoraria, Speakers Bureau; Ortho Biotech: Honoraria, Speakers Bureau. Lonial:Celgene: Consultancy; Millennium: Consultancy, Research Funding; BMS: Consultancy; Novartis: Consultancy; Gloucester: Research Funding. Singhal:Celgene: Speakers Bureau; Millennium: Speakers Bureau.

Abstract The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents.

Two oncogenic pathways have been hypothesized for multiple myeloma (MM) and premalignant monoclonal gammopathy of undetermined significance (MGUS) tumors: a nonhyperdiploid pathway associated with a high prevalence of IgH translocations and a hyperdiploid pathway associated with multiple trisomies of 8 chromosomes. Cyclin D1, D2, or D3 expression appears to be increased and/or dysregulated in virtually all MM tumors despite their low proliferative capacity. Translocations can directly dysregulate CCND1 (11q13) or CCND3 (6p21), or MAF (16q23) or MAFB (20q11) transcription factors that target CCND2. Biallelic dysregulation of CCND1 occurs in nearly 40% of tumors, most of which are hyperdiploid. Other tumors express increased CCND2, either with or without a t(4;14) translocation. Using gene expression profiling to identify 5 recurrent translocations, specific trisomies, and expression of cyclin D genes, MM tumors can be divided into 8 TC (translocation/cyclin D) groups (11q13, 6p21, 4p16, maf, D1, D1+D2, D2, and none) that appear to be defined by early, and perhaps initiating, oncogenic events. However, despite subsequent progression events, these groups have differing gene expression profiles and also significant differences in the prevalence of bone disease, frequency at relapse, and progression to extramedullary tumor.