Kourelis, Taxiarchis

Multiple myeloma (MM) is an incurable plasma cell malignancy. Despite therapeutic advances that have vastly improved survival, all patients are expected to relapse. One mechanism that may contribute to MM relapse is tumor dormancy. Dormant MM cells may persist in the bone marrow, where they exhibit reduced proliferative capacity and resistance to treatment. These cells may then exit dormancy following treatment to drive disease relapse. Dormancy shares many features with cellular senescence, a state of stable growth arrest induced by cell stress. Chemotherapies that produce genotoxic stress have been associated with therapy-induced senescence (TIS). One such genotoxic agent, melphalan (Mel), is routinely administered to MM patients for myeloablation prior to autologous bone marrow transplant. We hypothesized that High Dose Mel (HDM) induces a senescent-like dormant phenotype in surviving MM cells. To test our hypothesis, we developed an in vitro model for HDM. We identified 10µM Mel as a concentration to induce >90% cell toxicity (HDM) in 5TGM1 mouse MM cells over 10 days. 5TGM1-GFP MM cells were cultured with HDM or vehicle (Veh) for 6 hours; cells were then cultured in normal growth medium in the presence of primary mouse (C57BL/6) bone marrow stromal cells (BMSCs). Co-cultures were imaged by fluorescent microscopy every other day to quantify cumulative population doublings (CPD) and cell morphology over the following 10 days. The effect of HDM on CPDs was also evaluated in the human RPMI-8226 MM cell line. 5TGM1-GFP cells were isolated by FACS on day 10 for evaluation of senescence histological characteristics and gene expression. All studies represent n=3 independent experiments unless otherwise indicated. HDM-5TGM1 cells exhibited a significant reduction in mean CPDs over 10 days compared to Veh (HDM 0.32±0.31, Veh 6.72±0.69, p<0.0001), indicating stable growth arrest in HDM treated cells consistent with senescence. HDM-5TGM1 cells were also significantly larger versus Veh (median size in pixels units: HDM 413.2±99.98, Veh 207±8.88, p<0.05), consistent with classical enlarged morphology in senescent cells. Preliminary assessment (n=1) of HDM-RPMI-8226 cells showed similar growth arrest (mean cumulative doublings: HDM 0.058±0.101, Veh 4.185±0.358) and enlargement (mean size in pixel units: HDM 804.1±6.048, Veh 526.9±2.115), suggesting a translatable mechanism in humans. FACS-sorted 5TGM1-GFP cells were stained for telomere associated foci (TAF), a marker of persistent DNA damage characteristic of senescent cells. HDM-5TGM1 cells showed a higher percentage of TAF+ cells (Percent TAF+ cells: HDM 39.7%±9.1%, Veh 10.6%±0.8%, n=2). Sorted HDM-5TGM1 cells also exhibited significant increases over Veh (p<0.001) in senescence markers ( Cdkn1a, Cdkn1c, Glb1), senescence cell anti-apoptosis pathway genes (SCAPs, Bcl2l1), and senescence associated secretory phenotype (SASP) genes ( Ccl5, Icam1, Mmp13). In addition, HDM-5TGM1 cells showed significant increases in myeloid markers that have previously been shown to be increased in dormant 5TGM1 ( Axl, Fcer1g, Mpeg1). Single cell RNA-sequencing was used to further evaluate senescence gene expression changes in growth arrested HDM-5TGM1 cells. Gene set enrichment analysis (GSEA) of genes differentially expressed in HDM-5TGM1 versus Veh cells was performed for custom senescence phenotyping gene sets (Senescence Up, SenUp; Senescence Growth Arrest, SenGA; Inflammatory SASP, iSASP; SCAPs; and Plasma Cell Senescence; PCSen) as well as mouse ortholog versions of a published senescence and biological aging gene set (SenMayo) and KEGG curated gene sets. GSEA of HDM-5TGM1 versus Veh cells confirmed significant (FDR<0.25) upregulation of iSASP, MayoSen, PCSen, SenUp, SCAPs, and SenGA gene sets. Concurrently, GSEA revealed significant downregulation of KEGG DNA replication, cell cycle, and nucleotide excision repair gene sets, supporting our observations of proliferative arrest and persistent DNA damage TAF. Our findings demonstrate that HDM-MM cells exhibit multiple features of senescence, suggesting a potential mechanistic role for TIS in MM dormancy and highlight a novel therapeutic target that may be present in patients post-HDM. Thus, targeting senescence may be a novel approach to eliminate dormant MM cells and prevent relapse.

Introduction Newly-diagnosed multiple myeloma (MM) patients often share tumor genetic abnormalities associated with a high risk of progression and poor survival. We hypothesized that single-cell transcriptomic characterization of the tumor immune microenvironment (TIME) may be combined with tumor-based risk stratification to uncover novel disease biology mechanisms associated with clinical outcomes and improve risk stratification. Methods We performed single-cell RNA sequencing of 361 CD138 negative sorted bone marrow mononuclear cells (BMMCs) samples from 263 MM patients enrolled at time of diagnosis in the Multiple Myeloma Research Foundation CoMMpass study (NCT01454297). Specimens were analyzed at baseline (n=263) across a network of five collaborating academic research centers following assay harmonization. Genetic factors that determine risk were defined as one or more of the following gain- or loss-of-function events derived from baseline genomic sequencing data: del17p14, translocations of the Ig locus with the MAF/A/B or WHSC1/MMSET/NSD2 loci, and gain of chromosome 1q21. Statistical modeling strategies were used to assess single-cell populations or RNA signatures associations with known risk factors or disease progression (FDR<0.05). Results The study generated high-quality single-cell profiles of 731,643 cells from 123 high-risk and 107 standard-risk MM patients based on genetics. Based on distinct transcriptome profiles, BMMCs formed 106 clusters corresponding to 5 major compartments: NK and T cells, B cells, erythrocytes, myeloid cells, and plasma cells. Our preliminary differential abundance analysis comparing high- vs standard-risk patients at baseline uncovered significant differences in the TIME associated with genetic risk. The high-risk group was identified as enriched in effector CD8+, and CD4+ T cells. In contrast, the high-risk group exhibited depletion of naive CD8+ and interferon-associated CD4+ and CD8+ T as compared to the standard-risk group. Within subclusters in the T and NK cells compartment, a higher cytotoxicity signature was observed in high-risk patients, characterized by the expression of granzymes and perforin. Finally, our preliminary survival and progression analysis associated a higher frequency of IDO1-expressing macrophages in worst progression patients, while better outcomes were associated with CD8+ T and B cells expressing androgen response and IL6/STAT3/EMT programs, respectively. Conclusions Current approaches for risk stratification are based on bulk measurements of tumor's genetic or epigenetics features, which do not capture the diversity and dynamics of the TIME. Through single-cell transcriptomics, we were able to capture, in high granularity, the TIME and correlate specific immune cell populations and phenotypes with relapse risk and poor prognostic outcomes. These results suggest that immune subpopulations may be an essential novel aspect for improving current risk stratification models.

Introduction While chimeric antigen receptor (CAR)-T cell therapy has transformed the management of hematologic malignancies, it requires frequent monitoring for acute toxicities, almost universally achieved through mandatory hospitalizations, therefore utilizing a significant amount of healthcare resources. At Mayo Clinic in Rochester, MN, our standard practice is administering CAR-T cell therapy in the outpatient setting through a multi-disciplinary hospital-based outpatient (HBO) unit and remote patient monitoring (RPM) program. Our CAR-T RPM program consists of in-home, electronic health record-integrated technology to monitor vital signs and neurologic symptoms for 30 days post CAR-T infusion. Here we report the healthcare utilization outcomes of CAR-T patients managed in the outpatient setting enrolled in the RPM program. Methods Patients undergoing FDA-approved CAR-T cell treatment in the outpatient setting and participating in the CAR-T RPM program at Mayo Clinic Rochester were included in this IRB-approved study. Patient characteristics, healthcare utilization metrics, inpatient interventions, and patient satisfaction data regarding the RPM program were reviewed. Length of stay (LOS) includes any hospitalizations for which the admission date falls within the RPM monitoring period (CAR-T cell infusion to day +30), even if the hospitalization continued past day +30. Results A total of 123 patients participated in the CAR-T RPM program and underwent treatment in the outpatient setting. Median age at CAR-T infusion was 63 years (range 22 - 83), and most patients were male (n=78, 63%). Non-Hodgkin lymphoma was the most common diagnosis (n=74, 60%), followed by multiple myeloma (n=47, 38%), ALL (n=1, 1%) and other (n=1, 1%). During the PRM monitoring period, 19 (16%) patients were managed entirely in the outpatient setting. The remaining 104 (84%) patients required at least one hospitalization, with most patients (n=70, 57%) hospitalized only once [26 (21%) patients were hospitalized twice, and 7 (6%) patients were hospitalized 3 times, and 1 (1%) patient hospitalized 4 times during the monitoring period]. When considering the first hospitalization post CAR-T infusion, the median LOS was 6 days (range 2 - 47). When considering all hospitalizations post CAR-T, the median LOS was 8 days (range 2 - 47). Only 7 (6%) patients required an ICU stay, with a mean ICU stay of 0.2 days (standard deviation 0.9). Cytokine release syndrome (CRS) was noted in 92 (75%) of patients at a median of 3 days (range 0 - 18) post CAR-T infusion. All patients with CRS received tocilizumab, at a median of 4 days post CAR-T infusion. Steroids for CRS were administered in 63 (68%) of these patients. Neurotoxicity was reported in 45 (37%) patients at a median of 7 days (range 1 - 19) post CAR-T infusion. During the RPM monitoring period, patients were seen in our HBO unit with a median of 18 outpatient visits (range 4 - 30). Patient survey data, obtained at the end of the RPM monitoring period, were available from 37 patients. The majority of patients felt that the RPM program helped them feel comfortable managing their health at home, were able to reach a team member, and receive an appropriate response promptly. The majority of patients felt comfortable using the RPM equipment and interacting with providers virtually. Overall, 83% of patients were satisfied with the RPM program and 6% were neither satisfied nor dissatisfied. When asked about the reason for disappointment, technical difficulties/issues with the devices were the themes mentioned by the few patients (11%) who were unsatisfied with the RPM program. Conclusion: Despite the complexities and frequent monitoring associated with CAR-T cell therapy, outpatient CAR-T cell treatment is a feasible model of care. As the standard practice at our institution, the CAR-T RPM program was part of the management of nearly all patients undergoing an FDA-approved CAR-T product in the outpatient setting. RPM in the acute setting post CAR-T infusion is a well-received practice initiative by the majority of patients, including a high level of comfort utilizing the RPM equipment and virtual interaction with the RPM providers.

Background: Patients (pts) receiving FDA-approved chimeric antigen receptor T-cell (CAR-T) therapy or Bispecific antibody Teclistamab (Tec) are commonly managed in the inpatient setting given the common adverse events such as cytokine release syndrome (CRS) and immune cell-associated neurotoxicity syndrome ICANS. We have previously reported that hospital-based outpatient (HBO) management of pts receiving CAR-T is feasible and safe (Bansal et al, ASH2022). In 2023, HBO management at our institution began incorporating home health visits and management of grade 1 CRS in outpatient setting for select pts receiving standard of care (SOC) CAR-T. Here, we report outcomes of our updated practice. Methods: We retrospectively analyzed medical records and remote monitoring data of adult pts who received SOC CAR-T or Tec between 10/2020 and 7/2023 at Mayo Clinic, Rochester under an IRB approved protocol. Results: In 3/2023, pts deemed to be low risk for severe CRS (fever onset >= 3 days from infusion, CRP<100) received HBO management for grade 1 CRS, including outpatient administration of tocilizumab. If CRS improved or resolved, outpatient monitoring was continued. If CRS persisted within the observation period on HBO, pts were admitted. Recurrent CRS after the first episode were all managed inpatient. Nine pts met these criteria for HBO CRS management and their outcomes were compared to those who received initial inpatient (INPT) CRS management (INPT, n=17) during the same timeframe, as well as the outcome of 164 pts who had CRS management INPT prior to our practice change (Table 1). Two-third of the pts with initial management of CRS outpatient did not require hospitalization. Median time to hospitalization trended later than those managed inpatient at the onset of CRS. The duration of hospitalization was comparable for all pts admitted between initial HBO and INPT CRS management. However with fewer admissions in the initial CRS HBO group, the average hospitalization days (LOS) per patient treated for that group was lower compared to initial INPT CRS management. Data on additional pts will be presented at ASH. In 1/2023, pts on RPM with no ongoing CRS symptoms, no language barriers, and no compliance concerns received home health visits during weeks 3 and 4 post CAR-T infusion in place of clinic visits on HBO. Home health visit team communicated with HBO staff to review assessment and plan. Changes in HBO utilization will be presented. Finally, 24 pts received 223 Tec infusions on HBO. Median age was 66 years, 15 (61%) were males, 9 (38%) had high risk cytogenetics. The median prior lines of therapy was 5. Among these pts, 220/223 (99%) doses were performed on HBO and 204/220 (93%) infusions never required admission for management. Twenty pts enrolled in RPM (Figure 1). An average of 2 alerts were generated per patient during the 2 week period and median time from infusion to alert was 1.5 days. Majority of alerts were resolved over a phone call and only 13/114 (11%) alerts required a physician visit/hospital admission. Of the 16 Tec infusions resulting in admission, 4/16 (25%) required re-admission resulting in a total of 20 hospitalizations. Admissions mostly occurred during step-up dosing (18/20; 90%). Most common reason for first admission was fever (13/16, 85%) and median time to admission was 1 day from infusion. Median LOS was 1.5 days (range, 0-12). In terms of CRS, majority were Grade 1 (12/13, 93%) which were managed with steroids (dexamethasone/ prednisone) alone. One patient had CRS grade 4 event, in the setting of concurrent decompensation during dialysis, and was treated with steroids, tocilizumab, vasopressor, CRRT, thoracentesis, intubation and mechanical ventilation. The rate of second CRS event after management of first CRS with steroid (dexamethasone/ prednisone) was 15% (2/13). These second CRS episodes also resolved with steroid alone. Data on additional pts receiving Tec will be presented at ASH. Conclusion: Our data showed that additional advances in outpatient practice, including initial outpatient management of CRS and outpatient administration of Tec step up dosing are feasible, safe and reduce hospital resource utilization.

Background: Upfront autologous stem cell transplant (ASCT) is the standard-of-care for newly diagnosed multiple myeloma (MM) patients. However, relapse and the development of therapy-related myeloid neoplasms (t-MN) post ASCT results in considerable morbidity and mortality. We hypothesized that enrichment of abnormal myeloid progenitors and immune effector cells (IEC) in peripheral blood stem cells (PBSCs) of patients with MM is associated with a higher risk of relapse and development of t-MN. Methods: After institutional review board approval, we screened patients with active MM that were evaluated at Mayo Clinic, Rochester, MN between 01/01/2003 and 12/31/2020. Patients that underwent an ASCT and had cryopreserved PBSC product available for research were included. Using mass cytometry, we performed a comprehensive immunophenotyping of mobilized cryopreserved PBSCs from 54 MM patients undergoing 1 st ASCT, using validated antibody panel of 37 lymphoid- and myeloid-based markers each. Flow cytometry standard files were normalized and concatenated using the Fluidigm acquisition software. Flow cytometry standard files were uploaded to the OMIQ software from Dotmatics (www.omiq.ai, www.dotmatics.com), where transformation and cleaning (doublets, debris) were performed. To correct for between-sample technical variations (“batch effects”), we used fdaNorm within the omiq.ai platform. Clustering and visualization of normalized and concatenaded flowcytometry files were performed within the omiq.ai platform using PhenoGraph and UMAP, respectively. We performed principal component analysis (PCA) to identify major immunomic drivers of variability across patients. We explored the associations between immune subsets and the dichotomized clinical outcomes of interest: progression-free (PFS), myeloid neoplasm-free (MNFS) and overall survival (OS) from ASCT. A 2-sided false discovery rate adjusted P-value of <0.05 was considered significant when multiple comparisons were performed; otherwise, a P-value of <0.05 was considered significant. Results: The most abundant cell populations were T-cells (49% of the CD45 +) and myeloid cells (43% of the CD45 + cells). Clustering on the CD45 + cells revealed 30 unique lymphoid clusters and 27 unique myeloid clusters. Subclustering on NK-cells identified an additional 16 NK-cell clusters. On PCA, principal components-1 (PC-1) and 2 (PC-2) explained 15.2% and 12.5% of the variability in the data, respectively. A high PC-2 score was associated with inferior median PFS (20 vs. 52 months; P=0.005, Figure 1A), MNFS (52 vs. 85 months, P=0.03, Figure 1B) and OS (64 vs. 106 months, P=0.01) from ASCT. Immune subsets enriched in the high PC-2 cohort included the ‘NKT-like’ (CD56 +) T-cell subset which expressed the inhibitory CD159a receptor and TIGIT; a terminally differentiated (CD27/CD28 -, CD57/KLRG1 +) and exhausted (TIGIT/PD-1 +) T cell subset, 2 exhausted (TIGIT/PD-1 +) T cell subsets; an immunosenescent (CD27/CD28 -, CD57/KLRG1 +) T cell subset as well as a terminally exhausted (C27/C28 -, KLRG1/PD-1/TIGIT +) TCRgamma-delta subset. Immune subsets with high loadings within PC-1 (associated with improved clinical outcomes) consisted exclusively of CD4 + cells with early memory phenotypes (CD27/CD28/CD127 +). Abnormal expression of CD7 and HLA-DR expression on myeloid progenitor cell subsets was associated with an inferior PFS, MNFS, and OS. A NK-cell subcluster, characterized by an immature (CD56 high), inhibitory (CD159a +, NKG2A) phenotype, was enriched in patients developing t-MN (0.33% vs. 0.17%, P=0.006). Conclusion: We identify abnormal myeloid and immune effector cells in the PBSCs of patients with MM, even prior to ASCT. Patients with a PBSC product that is enriched in immunosuppressive T and myeloid cell subsets, and with a lower proportion of antigen presenting cells, progenitor populations, and anti-tumor macrophages have a shorter PFS and MNFS. This suggests that the predisposition to t-MN and inferior outcomes for MM are possibly determined early in the disease course. These findings need external validation and have the potential to guide sequencing of future treatment modalities.

Multiple Myeloma (MM) progresses from monoclonal gammopathy of undetermined significance (MGUS) and/or smoldering MM (SMM). Despite similar primary genetic events as MM, MGUS and SMM PCs are non- or low-proliferative. Since oncogene activation and DNA damage drive senescence growth arrest to promote immune clearance of potentially malignant cells, we hypothesized that MGUS and SMM pre-malignant PCs exhibit senescence features. To test this, we performed gene set enrichment analysis (GSEA) of a published human PC gene array dataset (GSE5900) comparing normal, MGUS, and SMM PCs for custom senescence phenotyping gene sets (Senescence Up, SenUp; Senescent Cell Anti-Apoptosis Pathways, SCAPs; Senescence Growth Arrest, SenGA; Inflammatory Senescence Associated Secretory Phenotype, iSASP; Interferon SASP, IFN-SASP) versus biological aging gene sets (SenMayo; CellAge). MGUS and SMM PCs exhibited significant enrichment (NES>1.5, q<0.05) for senescence gene sets SenUp, SenGA, and SCAPs compared to normal PCs, with no enrichment for aging gene sets. MGUS PCs were also enriched for iSASP (NES=1.4, q=0.11), whereas SMM PCs were enriched for IFN-SASP (NES=2.3, q<0.05), characteristic of late-senescence. Thus, both MGUS and SMM PCs show enrichment of senescence gene sets compared to normal PCs with differential SASP profiles. Next, we evaluated MGUS, SMM, and MM patient PCs isolated by magnetic sorting for histological senescence features. PCs were immunostained for LMNB1 and HMGB1, and fluorescent in situ hybridized for α-satellite. Cellular senescence was defined as loss of ≥50% nuclear membrane LMNB1, loss of HMGB1, and ≥2 senescence-associated distensions of satellite (SADS) per nuclei. PCs from MGUS patients (N=12) exhibited increased percentage of senescent PCs (26.9±4.1%, Mean±SEM, p<0.0001) compared to SMM (11.0±1.9%, N=19, p<0.0001) and MM (11.6±1.5%, N=11, p<0.001). A subset analysis of SMM patients for which disease stability was known (≥2 years, N=6-8) showed no differences. These results demonstrate that the percentage of senescent PCs is increased in MGUS but not SMM PCs compared to proliferative disease. To assess PC senescence in the native bone marrow microenvironment (BMME), we evaluated trephine bone biopsies from MGUS and SMM patients that progressed or not to MM ≤10 years, as well as newly diagnosed MM. Biopsies were immunostained for CD138, LMNB1, and HMGB1. Whole biopsy images were analyzed using the artificial intelligence-based software HALO. Cells were classified as senescent if they were double negative and non-senescent if they were double positive for LMNB1 and HMGB1. The percentage of non-senescent PCs increased with progression to MM and positively correlated with total PC burden (R=0.52, p<0.0001), reflective of proliferative disease. Senescent PCs correlated with total senescent BMME (R=0.87, p<0.0001), consistent with a role for senescent cells to drive paracrine senescence. We performed proximity analysis to evaluate the cellular composition within 25um of senescent and non-senescent PCs. As expected, non-senescent PCs exhibited a significantly greater percentage of proximate non-senescent BMME in all groups (p<0.0001). In contrast, senescent PCs in stable MGUS (N=16) and SMM (N=14) were equally surrounded by senescent and non-senescent BMME. In progressing MGUS (N=21) and SMM (N=20), as well as MM (N=18), senescent PCs exhibited significantly reduced senescent BMME in their proximate environment (p<0.05). This suggests that senescent PCs in progressive disease, in contrast to stable disease, fail to drive local paracrine senescence responses. These data demonstrate that PCs from stable MGUS and SMM patients exhibit senescence features, with isolated PCs from stable MGUS showing increased senescence gene expression and histologic features. While stable SMM also exhibits senescence gene expression, they lose morphological features of senescence and show a preferential IFN SASP. Within the bone compartment, senescent PCs in stable MGUS and SMM exhibit the expected proximity to senescent BMME. In contrast, progressing MGUS and SMM, as well as NDMM, show a loss of proximate senescent BMME. Given the role of senescence to drive inflammation to clear potentially tumorigenic cells, these data support that failure to drive paracrine senescence may be key to the immune escape of pre-malignant cells in MGUS and SMM.

Background: Cytopenias are a common complication of and prolonged (beyond month 3 post CAR-T infusion), severe (grade 3 or higher) cytopenias can be difficult to manage. Stem cell boosts have been reported to restore hematopoiesis; however, stem cells would need to be available prior to CAR-T therapy for potential use post CAR-T. Most lymphoma patients and limited number of myeloma patients may have pre-collected stem cells in storage. Identifying patients at high risk for prolonged and severe cytopenia post CAR-T at the time of CAR-T evaluation (baseline), before leukapheresis, can help identify the patients for coordination of stem cell collection during CAR-T manufacturing and increase the likelihood that the collected stem cells would be used. In this study, we aim to identify clinical variables at the time of CAR-T evaluation, prior to leukapheresis, that are associated with severe cytopenias at month 3 post CAR-T infusion and identify patients who could be considered for pre-emptive stem cell collection prior to CAR-T therapy. Methods: We conducted a retrospective analysis of patients with multiple myeloma (MM) and non-Hodgkin lymphoma (NHL) who received CAR-T products at Mayo Clinic from 01/2016 to 06/2022. Patients with progressive disease in the first year post CAR-T were excluded from the analysis. Baseline (at CAR-T evaluation, prior to leukapheresis) variables were compared between those with and without severe cytopenia at month 3 post CAR-T. Severe cytopenias were defined as hemoglobin (Hg) < 8 g/dL, absolute neutrophil count (ANC) < 0.5 x 10 9/L, and/or platelet count (PLT) < 50 x 10 9/L. Statistically significant variables (p<0.05) by analysis were examined for statistical significance in multivariate analysis (MVA). Results: Among the 166 patients who received CAR-T (88 NHL, 78 MM) during the study period, 31 (18.67%) had a severe cytopenia at month . Twenty baseline variables were examined; HGB, PLT, ANC, and c-reactive protein (CRP) We devised a cytopenia risk score using 1 point each for Hg<10 or PLT<100k at baseline, with a range of 0 to 2. Demographics and clinical outcome by cytopenia risk score is shown in Table 1B. A higher percentage of patients with a score of 1 or 2 had a severe cytopenia at month 3 (Figure 1). In particular, there was a . In addition Conclusion: Baseline cytopenias before leukapheresis may identify patients with increased risk for severe cytopenias at month 3 post CAR-T. These patients can have continued slow hematopoietic recovery in the first year. Stem cell collection, if feasible, could be considered before CAR-T to alleviate post-CAR-T severe prolonged cytopenias.

Abstract The approach to patients with high-risk smoldering multiple myeloma (SMM) varies among clinicians; while some advocate early intervention, others reserve treatment at progression to multiple myeloma (MM). We aimed to describe the myeloma-defining events (MDEs) and clinical presentations leading to MM diagnosis among SMM patients seen at our institution. We included 406 patients diagnosed with SMM between 2013-2022, seen at Mayo Clinic, Rochester, MN. The 2018 Mayo 20/2/20 criteria were used for risk stratification. Median follow-up was 3.9 years. Among high-risk patients who did not receive treatment in the SMM phase (n=71), 51 progressed by last follow-up; the MDEs included: bone lesions(37%), anemia(35%), hypercalcemia(8%), and renal failure(6%); 24% met MM criteria based on marrow plasmacytosis (≥60%) and/or free light chain ratio (>100); 45% had clinically significant MDEs (hypercalcemia, renal insufficiency, and/or bone lesions). MM diagnosis was made based on surveillance labs/imaging(45%), testing obtained due to provider suspicion for progression(14%), bone pain(20%), and hospitalization/ED presentations due to MM complications/symptoms(4%). The presentation was undocumented in 14%. A high proportion (45%) of patients with high-risk SMM on active surveillance develop end-organ damage at progression. About a quarter of patients who progress to MM are not diagnosed based on routine interval surveillance testing.