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Abstract Introduction: Suboptimal response to therapy, early disease relapse, and limited long-term survival remain critical challenges in a substantial number of patients with multiple myeloma (MM). While cross-sectional imaging studies are commonly obtained in clinical practice, only limited information is currently incorporated into risk stratification efforts and clinical decision making. Here, we investigate the use of novel image-based biomarkers to identify patients at high risk for adverse outcomes. Methods: We obtained the pretreatment 18F-FDG PET/CT scans of patients with newly diagnosed MM with available clinical and laboratory data seen at Mayo Clinic between 2006 and 2022. In this analysis, we included 637 patients with detectable metabolic tumor volume on their pretreatment scan. The native DICOM images were pre-processed and subjected to automated image segmentation using nnU-Net (nnU-Net v1.0, inference using a pre-trained hematologic malignancies model). Limitations of this automated segmentation approach include heterogeneity introduced by varying image quality, technical variability in PET reconstruction, and potential inclusion of non-neoplastic FDG-avid lesions in segmented regions. PyRadiomics was used to extract quantitative radiomics features for clinical prediction modeling. We evaluated the predictive power of tumor size-, shape-, and texture-related radiomics features for identifying high-risk disease (advanced ISS stage at diagnosis, the presence of high-risk FISH abnormalities, failure to achieve a stringent complete response [sCR] to first-line therapy by IWMG criteria, and early mortality). All radiomics features were quantile-normalized for downstream modeling. Forward and backward feature selection as well as testing for multicollinearity were used to remove redundant features. Results: Median age at diagnosis of the 637 myeloma patients was 64 years (range 22–90), and 387 patients (61%) were male. After a median follow-up of 4.4 years (95% CI 0.2–11.7), median overall survival (OS) was 7.3 years (95% CI 6.3–8.3). Increased total tumor volume (upper tertile vs lower tertiles), measured by the total tumor surface area, was associated with advanced ISS stage (III vs I+II; OR 1.73, 95% CI 1.24–2.42, p=0.001, n=637). Increased tumor density (dichotomized at the median), measured by the median gray level intensity (OR 1.93, 95% CI 1.94–3.12, p=0.007, n=303), and decreased tumor heterogeneity (lower tertile vs upper tertiles), measured by the variability of gray-level intensities (OR 1.88, 95% CI 1.49–3.12, p=0.012, n=303), were associated with the presence of high-risk cytogenetics. Both increased total tumor volume (4.9% increase per tertile, 95% CI 2.2–7.6, p<0.001, n=600) and tumor density (8.9% increase per tertile, 95% CI 4.5–13.3, p<0.001, n=600) were independently associated with more extensive bone marrow involvement at diagnosis. Increased tumor heterogeneity (upper tertiles vs lower tertile), as measured by rapid changes of gray level intensities, was associated with failure to achieve a stringent complete response to first-line therapy (OR 0.50, 95% CI 0.30–0.82, p=0.006, n=351). Increased tumor volume was associated with shorter OS (HR 1.35 per tertile, 95% CI 1.11–1.63, p=0.002, n=301), independent of age, sex, ISS stage, and the presence of high-risk cytogenetics. A simple additive score consisting of tertiles of total tumor volume, ISS stage, and plasma cell labeling index ≥2% identified patients at risk of mortality within 3 years of diagnosis (OR 2.00, 95% CI 1.40–2.85, p<0.001, n=126), with moderate discrimination (AUC=0.71). Sensitivity analysis demonstrated total tumor volume and texture as most predictive of overall survival in a random forest survival model (C-index 0.712, 95% CI 0.649–0.775) and tumor texture as most predictive of response to therapy in a random forest classification model (C-index 0.693, 95% CI 0.607–0.779). Conclusions: Automated image segmentation and radiomics feature extraction from 18F-FDG PET/CT scans produces biomarkers that capture disease stage, burden, and risk in newly diagnosed MM. Total tumor volume and heterogeneity are strongly associated with important disease characteristics and can be used to identify patients at high risk for therapeutic resistance, early mortality, and inferior long-term outcomes.

Abstract Background: Proteasome inhibitors (PIs) are a cornerstone of multiple myeloma (MM) therapy, exploiting the high rate of immunoglobulin production and protein turnover in malignant plasma cells. However, intrinsic and acquired resistance to PIs remains a significant barrier to durable clinical responses. Hypoalbuminemia is a frequent and clinically relevant symptom in MM, often associated with poor prognosis, but its underlying causes are not fully understood. To date, it has not been explored whether MM plasma cells actively consume albumin and whether this contributes to hypoalbuminemia or interferes with current therapeutics.Although albumin catabolism has been described in endothelial cells and some solid tumors, its role in hematologic malignancies has not been investigated. Here, we report for the first time that MM cells internalize and degrade extracellular albumin, predominantly via lysosomal pathways, and that this mechanism contributes directly to resistance against proteasome inhibition. Methods: Human MM cell lines (RPMI-8226, JJN3, MM1.S, H929, and KMS11), representing a range of PI sensitivities, were cultured in media with defined amino acid composition and varying concentrations of human serum albumin. Cell viability in response to PIs (bortezomib and carfilzomib) was measured using MTT and Cell Titer-Glo assays. To determine whether albumin affected drug sensitivity, PI dose-response assays were conducted under low and high albumin conditions, with or without lysosomal inhibitors (ammonium chloride and leupeptin). Intracellular albumin accumulation and degradation pathway activation were assessed via Western blotting for proteasomal and lysosomal markers. Results: MM cells exhibited active uptake of extracellular albumin through endocytosis. Once internalized, albumin was metabolized to provide both essential and nonessential amino acids, supporting cell proliferation and enhancing antioxidant defenses. A strong correlation was observed between the extent of albumin consumption and resistance to PIs. Notably, under high-albumin conditions, MM cells became significantly more resistant to PI-induced cytotoxicity. Even in the absence of other metabolic stressors, high concentrations of albumin alone were sufficient to trigger PI resistance. Mechanistically, although small quantities of albumin could be degraded by the proteasome, elevated albumin levels induced robust lysosomal activation, diverting protein degradation away from the proteasome and effectively bypassing PI-induced stress. Under low-albumin conditions, PI treatment led to intracellular albumin accumulation in sensitive cells. In contrast, high-albumin conditions enhanced lysosomal degradation, mitigating the effects of proteasome blockade. Protein profiling revealed the upregulation of lysosomal enzymes and reduced proteasome dependence in albumin-treated cells. Importantly, inhibition of lysosomal function with ammonium chloride (partial) or leupeptin (complete) restored PI sensitivity, even under high-albumin conditions. Conclusion: This study identifies albumin-driven lysosomal activation as a novel and clinically relevant mechanism of PI resistance in MM. For the first time, we demonstrate that MM cells consume albumin as a nutrient source, offering a plausible explanation for the hypoalbuminemia commonly observed in patients. Our findings suggest that lysosomal degradation serves as a compensatory protein catabolism pathway during elevated extracellular albumin uptake. This has important therapeutic implications: reliance on lysosomal degradation renders MM cells less susceptible to standard PIs, and dual inhibition of lysosomal and proteasomal pathways may overcome resistance. These findings lay the groundwork for designing next-generation therapeutics that simultaneously target proteasomal and lysosomal degradation pathways to overcome drug resistance in multiple myeloma and related hematological malignancies.

Abstract Introduction: The CARTITUDE-4 (NCT04181827) trial compared cilta-cel, a chimeric antigen receptor (CAR)-T cell treatment (tx) targeting B-cell maturation antigen (BCMA), with 2 standard-of-care regimens in patients (pts) with RRMM and 1–3 prior lines of therapy (LOT). Cilta-cel significantly improved overall survival (hazard ratio [HR] 0.55) and progression-free survival (PFS; HR 0.29). The DREAMM-7 (NCT04246047) and DREAMM-8 (NCT04484623) trials evaluated belamaf, an anti-BCMA antibody-drug conjugate (ADC), in combination with bortezomib and dexamethasone (BVd) and with pomalidomide and dexamethasone (BPd), respectively. Both trials demonstrated improved survival and response rates with belamaf in pts with ≥1 prior LOT. International Myeloma Working Group (IMWG) guidance for RRMM tx recommends using anti-BCMA T-cell redirecting therapy (TCRT), such as CAR-T (eg, cilta-cel), before anti-BCMA ADCs (eg, belamaf). As cilta-cel and belamaf have not been compared head to head, we conducted unanchored matching-adjusted indirect comparisons (MAICs) to estimate relative efficacies using CARTITUDE-4 study individual patient data (IPD) and published data from DREAMM-7 and DREAMM-8. Methods: Unanchored MAICs were performed using IPD from apheresed pts in the CARTITUDE-4 cilta-cel arm. Eligibility criteriafrom DREAMM-7 and DREAMM-8 were applied to the cilta-cel cohort. Further adjustments were made by weighting cilta-cel IPDto match reported baseline characteristics (including refractory status [for DREAMM-8], cytogenetic risk, International Staging System stage, and presence of extramedullary disease) from DREAMM-7 and DREAMM-8. Outcomes were compared using weighted IPD for cilta-cel and reported response rates and simulated IPD based on published Kaplan–Meier PFS curves for BVd and BPd. For each matched population, we compared PFS, ORR, and very good partial response or better (≥VGPR) and complete response or better (≥CR) rates. A weighted Cox proportional hazards model was used to estimate PFS HRs and 95% CIs. A weighted logistic regression analysis was used to derive relative response ratios (RRs) with 95% CIs to compare relative tx effects. Results: The MAICs included 208 apheresed pts from CARTITUDE-4 (cilta-cel), 243 pts from DREAMM-7 (BVd), and 155 pts from DREAMM-8 (BPd). To form comparable cohorts, we excluded cilta-cel pts who would not have been eligible for DREAMM-7 (n=87) or DREAMM-8 (n=55). Cilta-cel pts were most commonly excluded from the DREAMM-7 MAIC due to bortezomib refractoriness or anti-CD38 refractoriness (n=55 and n=50, respectively), and from the DREAMM-8 MAIC due to bortezomib refractoriness (n=55). After exclusions, 121 and 153 cilta-cel pts remained in the MAICs with BVd and BPd, respectively. After adjustment, cilta-cel was associated with significantly lower risk of progression or death compared with BVd (HR 0.46 [95% CI 0.28–0.75]; P=0.0020) and BPd (HR 0.61 [95% CI 0.39–0.96]; P=0.0320). ORR was significantly higher with cilta-cel vs BVd (92.9% vs 82.7%; RR 1.12 [95% CI 1.03–1.22]; P=0.0087) and vs BPd (89.3% vs 77.4%; RR 1.15 [95% CI 1.04–1.29]; P=0.0100). Rates of ≥VGPR and ≥CR were also higher with cilta-cel vs BVd (≥VGPR: 89.7% vs 65.8%; RR 1.36 [95% CI 1.21–1.53]; ≥CR: 86.0% vs 34.6%; RR 2.49 [95% CI 2.04–3.03]; both P<0.0001) and vs BPd (≥VGPR: 86.6% vs 63.9%; RR 1.36 [95% CI 1.18–1.56]; ≥CR: 81.8% vs 40.0%; RR 2.05 [95% CI 1.65–2.53]; both P<0.0001). Sensitivity analyses were consistent with the adjusted comparisons and showed statistically significant PFS and tx response benefits with cilta-cel vs BVd and BPd. Conclusions: These MAICs demonstrated superior PFS and response rates with cilta-cel compared with 2 belamaf-containing regimens (BVd and BPd). Results should be interpreted with caution as there were substantial differences in the pt populations of CARTITUDE-4 vs DREAMM-7 and DREAMM-8. However, adjusted cilta-cel cohort sizes remained large enough for robust comparisons that showed statistically significant differences across efficacy outcomes. Another limitation is the remaining potential unmeasured residual confounding differences. Nonetheless, these findings support IMWG guidance recommending anti-BCMA TCRTs prior to ADCs and provide valuable comparative evidence in the absence of head-to-head trials.

Abstract Introduction Cila-cel is associated with a 10-15% risk of delayed neurotoxicity (DNT) with rates of cranial nerve palsies (IEC-NP) and parkinsonism (IEC-PKS) seen at a rate of 10% and 1-4% respectively and can occur as early as 3-4 weeks after infusion. We and others have shown that high post-infusion peak absolute lymphocyte count (ALCpeak) of >3x10^9/L is associated with an increased risk of delayed neurotoxicity (Lim et al., ASCO 2025) whilst the risk was negligible (~1%) when ALCpeak fell below that threshold. Since December 2024, we implemented prophylactic administration of dexamethasone (PPX DEX) when ALC was >3x10^9/L (defined as high ALCpeak). Outcome of these patients are described here. Methods Analysis of clinical outcome included 230 pts treated between Feb 2022 and Nov 2024 as a historical cohort and 102 patients treated between Dec 2024 and May 2025 after the introduction of dexamethasone prophylaxis using an oral dose of 10mg twice a day for at least three days in the high ALCpeak cohort. Results No significant differences were seen between the new and historical cohort in pre-lymphodepletion disease burden (bone marrow plasma cell %, involved light chain or M-spike level), and rates of all/high-grade CRS or ICANS, IEC-HS and rates of tocilizumub use. Median follow-up in the new cohort of 102 pts was 3.6 months (95% CI 3.3-4.2). Eleven (10.8%) developed DNT [3 (2.9%) with IEC-PKS, 8 (7.8%) with IEC-NP]. High ALCpeak of >3x10^9/L was observed in 51 (50%) pts. Among pts with high ALCpeak, DNT was observed in 10 (20%) pts [3 (5.9%) with IEC-PKS, 7 (13.7%) with IEC-NP] whereas among 51 pts with ALCpeak <3x10^9/L, DNT was observed in 1 (2%) pt [1 (2%) with IEC-NP]. In the high ALCpeak cohort, 38 (75%) received DEX [6 (12%) for toxicity management, 32 (63%) PPX DEX]. Of the 38 pts treated with DEX, DNT was observed in 6 (16%) pts (2 (5.3%) IEC-PKS, 4 (10.5%) IEC-CNP). We next compared DNT rates between this new cohort of high ALCpeak pts receiving DEX (n=38) against the historical cohort with high ALCpeak (n=98). Estimated 90-day DNT by Kaplan-Meier method was (19.2% vs 20.5%; p=0.53): IEC-PKS (5.8% vs 7.2%; p=0.60) and IEC-NP (11.7% vs 13.3%; p=0.58). In patients with high ALCpeak, the use of DEX did not appear to significantly reduce the risk of DNT compared to historical controls (HR 0.76, 0.33-1.78), IEC-PKS (HR 0.67, 0.14-3.10) or IEC-NP (0.73, 0.24-2.23). We next compared ALC expansion over the first month post CAR-T infusion (area under the curve, AUC). Among the new cohort of 102 patients, no difference was seen in the AUC of pts who received DEX but did not develop DNT vs those who developed DNT (31.0 vs 57.9, p=0.28); No difference in AUC was seen in the new high ALCpeak cohort receiving DEX vs the historical cohort with high ALCpeak (36.0 vs 43.8, p=0.15) Of the eight cases of IEC-NP, 4 received PPX DEX. No noticeable differences were observed in the severity of presentation, laterality of cranial nerve involvement and rates of multiple cranial nerve involvement between these 4 cases who received PPX DEX and the 16 cases from the historical cohort. At the time of database freeze, 3 of the 4 cases had resolved and 1 was improving. Median time to complete symptom resolution was 38 days vs 69 days in the historical cohort. Of the three cases of IEC-PKS, 2 received PPX DEX. Median time to symptom onset for IEC-PKS was 46 days (vs. 24 days in historical cohort). Both cases had severe symptoms non-responsive to first line high-dose methylprednisolone, second line intrathecal chemotherapy and third line high-dose cyclophosphamide. Both pts subsequently died from sepsis 28 and 67 days post-cyclophosphamide. Conclusion While ALCpeak >3x10^9/L predicts risk of DNT in pts treated with cilta-cel, the use of PPX DEX does not appear to significantly reduce ALC expansion and does not appear to significantly reduce the risk of DNT, IEC-PKS or IEC-NP. Other strategies to reduce ALC or alter T cell functions may need to be considered.

Abstract Cyclin D1, encoded by CCND1, is a cell cycle regulator, overexpressed in ~15% of multiple myeloma (MM) cases via CCND1::IGH super-enhancer juxtaposition through t(11;14). Cyclin D1 also plays a non-canonical role in transcriptional regulation, but in t(11;14) MM its function in gene regulation remains undefined. We investigated the global transcriptional and epigenomic consequences of CCND1overexpression in t(11;14) MM. To define a CCND1 signature, RNA-seq from two independent primary MM patient cohorts, CoMMpass and Mayo, was utilized to compare high CCND1 t(11;14) cases (≥300 transcripts-per-million [TPM], n=271) vs. low CCND1 hyperdiploid cases (<30 TPM, n=233). Two CCND1 knockout (KO) clones in t(11;14) MM U266B1 were also generated by CRISPR/Cas9, introducing a frameshift insertion (A) after chr11:69641478 (hg38) in exon 1. ATAC-seq and ChIP-seq (H3K4me3, H3K4me1, and H3K27ac) were performed in duplicates, and RNA-seq in triplicates in U266B1 wild-type (WT) and KO. Libraries were sequenced on Illumina NextSeq 2000 (2x51 bp for ChIP/ATAC, 2x150 bp for RNA-seq). Reads were mapped to hg38 by BWA (ChIP/ATAC) or STAR (RNA-seq), peaks called by MACS2 (FDR< 0.01), peak and gene raw counts estimated by featureCounts. Differential peaks (fold-change ≥1.5) and differentially expressed genes (fold-change ≥2) were identified by edgeR (FDR<0.05), including peaks detected in ≥2 samples and genes with TPM ≥0.1 in ≥1 sample. Interactions between promoters and distal regulatory regions were identified using publicly available chromatin interaction data in blood cell types. Pathway analysis was performed using Enrichr. Co-immunoprecipitation was performed in t(11;14) KMS12BM cells. Differential analysis comparing CCND1-high t(11;14) and CCND1-low MM cases in the two patient cohorts identified 21 upregulated and 21 downregulated genes associated with CCND1 expression which were also captured in the wild-typevs. CCND1 KO U266 cells. Enriched pathways (p<0.05) included Notch signaling, early/late estrogen response, epithelial-mesenchymal transition and reduced mitotic spindle and myogenesis. Dysregulated genes included those related to apoptosis, ubiquitin-proteosome, extracellular matrix, adhesion, and immune response, demonstrating a broader role for cyclin D1 in MM beyond cell cycle control. To explore the epigenomic basis of this transcriptional regulation, for each of the 42 differentially expressed genes we examined the changes of histone marks and chromatin accessibility in promoter and the interacting distal regulatory regions in the U266 KO model. Ten of the 21 genes upregulated in CCND1-high (downloaded in KO; e.g., argininosuccinate synthase 1 [ASS1], PMAIP1, MYEOV, CCR7, and DTX1) and 12 of the 21 genes downregulated in CCND1-high (upregulated in KO; e.g., UACA, RASAL2, PTPRZ1, PPT2, and IL23R) showed concordant changes in histone marks and/or chromatin accessibility, predominantly in distal regulatory regions, suggesting a chromatin-mediated mechanism of gene regulation by cyclin D1. The most prominent changes involved H3K27ac, a mark defining active enhancers. As H3K27ac is deposited by histone acetyltransferases CBP, we tested for the possible cyclin D1-CBP interaction. Co-IP confirmed this interaction, suggesting a role for this complex in chromatin remodeling and transcriptional control in t(11;14) MM. One gene notably upregulated in association with CCND1 is ASS1, which encodes a urea cycle enzyme responsible for endogenous arginine synthesis. Metabolomic studies demonstrated KO cells had elevated aspartate and citrulline and lowered arginine and ornithine compared to WT cells (p<0.01) demonstrating impaired urea cycle function. Further, KO cells displayed significantly reduced ASS1 protein expression, cell growth and S-phase entry compared to WT cells in arginine-replete conditions, with both WT and KO cell types further inhibited by arginine depletion (p<0.05). Together, a cyclin D1-associated gene signature was identified supporting its role in t(11;14) MM beyond the CDK4/6 mediated cell cycle control, including a role in metabolic plasticity and survival under arginine depleted conditions. These findings highlight cyclin D1 as a therapeutic vulnerability and open new avenues for personalized treatment strategies.

Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage as morphology and cytogenetics cannot reliably distinguish them. In this study, using genomic data from 374 patients with MGUS or SMM (277 training, 97 validation), to our knowledge, we demonstrate for the first time the ability to identify malignant transformation in MGUS and SMM. We introduce the concept of genomic MM and genomic MGUS to differentiate the subsets of MGUS and SMM that are biologically malignant with genomic features indistinguishable from MM from the subset that is premalignant and unlikely to progress to malignancy. Importantly, we find that most SMM has biological features of malignant transformation indistinguishable from MM. As expected, this subset that we consider having genomic MM is associated with a high risk of progression to MM although some patients remained progression-free beyond 5 years. Conversely, 60% of MGUS and 10% of SMM have no evidence of malignant transformation (genomic MGUS), with no progression during follow-up. Integration of genomic features with the 2/20/20 International Myeloma Working Group model significantly improved the prediction of progression among genomic MM. These findings support the use of genomic criteria to refine the classification and the risk stratification in myeloma precursor conditions.

ABSTRACT Introduction A novel therapy for heavily pretreated triple‐class–exposed multiple myeloma (TCE MM) is B‐cell maturation antigen (BCMA)‐targeted immunotherapy. While the number of TCE+BCMA‐exposed patients is growing, real‐world data for this group are limited. Methods We present real‐world data from patients with TCE+BCMA‐exposed MM who initiated a subsequent line of therapy (LOT) using a US‐based claims database, Komodo's Healthcare Map. Results We identified 656 TCE+BCMA‐exposed patients; mean age was 66.5 years. Time from MM diagnosis to index was 5.4 years; mean number of prior LOTs was 5.9. The most prevalent prior therapy received within each drug class was daratumumab (98.5%), pomalidomide (86.0%), carfilzomib (85.8%) and belantamab mafodotin (74.5%). A total of 137 different subsequent treatment regimens were observed following TCE+BCMA exposure; the most common regimen was teclistamab (10.4%). The top three targeted agents within the subsequent regimen were carfilzomib (20.2%), pomalidomide (20.1%) and bortezomib (16.6%). Among this TCE+BCMA‐exposed population who received subsequent treatment, the median time to next treatment or death was 6.8 (95% CI, 6.1–7.5) months; time to treatment discontinuation or death was 3.5 (95% CI, 3.2–3.7) months. Conclusion This first real‐world analysis of patients with heavily pretreated TCE+BCMA‐exposed MM shows poor clinical outcomes, frequent therapy retreatment and no standard‐of‐care, highlighting the need for novel treatments. Clinical Trial Registration The authors have confirmed clinical trial registration is not needed for this submission.