Baughn, Linda B.

Abstract Introduction Detecting genetic abnormalities is mandatory during diagnostic workup and for potential individualization of therapy selection in multiple myeloma (MM) and its precursor conditions. At present, this requires invasive bone marrow (BM) biopsies, severely limiting early detection, patient monitoring, and the precise selection of therapy. The current standard for detecting genetic alterations in MM is fluorescence in situ hybridization (FISH), which cannot detect point mutations and other clinically relevant alterations. Consequently, the IMS-IMWG guidelines were recently updated to require next-generation sequencing for the classification of high-risk MM. Moreover, the importance of identifying alterations in therapeutic targets (e.g., BCMA, GPRC5D) for guiding immunotherapies is becoming increasingly recognized. To address this need, we recently launched GenoPredicta, a CLIA-approved Laboratory Developed Test that enables routine monitoring, informing diagnosis, and treatment selection by comprehensively and robustly characterizing MM genomes with whole genome sequencing (WGS) from a minimum of ~50 circulating tumor cells (CTCs) isolated from peripheral blood (PB) or tumor cells from BM. Here, we describe the characterization of clinical and research samples with GenoPredicta, highlighting resistance-conferring genetic alterations that can only be detected by sequencing and that are consistent with patients' clinical histories, while further demonstrating the complete concordance of GenoPredicta with prior FISH results. Methods Tumor cells were isolated from BM and/or PB samples using fluorescence-activated cell sorting (FACS) (after CD138+ enrichment for PB) and subjected to whole genome sequencing (WGS), from which we identified copy number alterations, structural variants, and single nucleotide variants and indels. For a subset of samples, the BM was also characterized by FISH, using a standard clinical panel for characterizing MM; for other samples prior FISH results were available from patients' clinical records. Results The analytical validation of GenoPredicta, conducted on a retrospective cohort of >60 viably frozen samples from >30 patients, showed complete concordance between BM and PB for detected genomic abnormalities, with all clinically relevant events (11 translocations and 125 CNVs) observed in BM recapitulated in PB (100% recall). All events identified by FISH in 14 samples (8 translocations and 30 CNVs) were also identified in the BM (100% recall), with 50 translocations and 30 CNVs not detected by FISH also absent in the WGS data (100% precision). The abnormalities detected in these samples also included multiple high-risk events not assayed by FISH, including biallelic TP53 loss (Del 17p coupled with a deleterious TP53 mutation, observed in 4 patients) and MYC::IGL translocations (2 patients). Moreover, for all fresh peripheral blood clinical samples with FISH results available from patients' histories, GenoPredicta recalled 100% of reported events. Among these clinical samples, we notably observed a case with both a biallelic GPRC5D deletion and a TNFRSF17 (BCMA) deletion combined with a truncating mutation on the remaining allele. This was consistent with the patient's clinical history showing progression after therapy with talquetamab (anti-GPRC5D bispecific), and previous nonresponse to teclistamab (anti-BCMA bispecific) after prior therapy with Cilta-cel (BCMA-directed CAR T). GenoPredicta also detected other mutations likely to confer resistance to immunotherapies, including loss-of-function mutations in IKZF3 and deletions of FCRL5 in frozen peripheral blood research samples. Conclusion We demonstrate that WGS-based characterization of MM from BM or CTCs is a viable replacement for FISH for clinical diagnosis and monitoring, with blood-based measurements enabling comprehensive profiling of the myeloma cancer genome. Importantly, this includes genetic alterations that confer resistance to therapy, allowing for both early detection of such alterations and more precise selection of therapy.

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.

Abstract Multiple myeloma (MM) is the second-most common hematological malignancy in the United States. Myeloma tumors have significant genetic heterogeneity that impacts disease progression and promotes resistance to treatment. RAS is a key oncogenic driver that activates the mitogen-activated protein kinase (MAPK) and the phosphatidylinositol 3-kinase (PI3K)/AKT pathways..Mutations in genes that code for RAS isozymes, KRAS, HRAS, or NRAS, lead to increased levels of activated GTP-RAS and are associated with the most aggressive forms of cancer. Mutations in the RAS family of genes are most common (40-50%) in myeloma. We and others have reported that RAS mutations may not be disease-initiating but rather arise during disease progression and relapse or as subclonal events that impart selective growth advantage and emerging drug resistance. In addition, non-mutant RAS can also be hyperactivated from upstream signaling (like receptor tyrosine kinases) or loss-of-function mutations in GTPase-activating proteins (GAPs). Given the importance of RAS mutations, allele-specific RAS inhibitors have long been considered an attractive strategy for myeloma treatment. However, multiple studies have reported various mechanisms of resistance to allele-specific RAS inhibitors as well as isoform-specific pan-RAS inhibitors, including newly acquired activating RAS mutations, RAS amplification, unchecked activation of co-expressed wild-type RAS (WT-RAS) isozymes, or acquired bypass mechanisms like new oncogenic fusions. Since MM remains incurable, we sought to improve upon currently available treatments by developing small-molecule inhibitors that preferentially inhibit myeloma cells with activated RAS isozymes. We have created NRasQ61X and KRasG12X mutations by CRISPR-Cas directed edits in a single endogenous RAS allele in human myeloma cell lines (HMCLs) that initially had two wild-type alleles. We found that these mutant-NRAS and mutant-KRAS edited cells have increased proliferation compared to cells with WT-RAS, as well as acquired resistance to several commonly used therapeutics. In this study, we used a triangulation method that combines our drug combination candidate prediction algorithm called ‘secDrug’ and the ‘Direct to Drug’ screening platform that evaluated 84 FDA-approved oncology drugs and emerging therapeutics in these RAS mutant myeloma lines. We identified BIRC5 as a potential target for RAS-mutant myeloma. BIRC5 expression is a key mechanism for the evasion of apoptosis. Notably, oncogenic RAS has been shown to promote MYC stabilization via upregulation of BIRC5. Earlier studies suggested that BIRC5 inhibitors are potent in targeting drug-resistant subclones in hematological malignancies. We performed in vitro cytotoxicity studies and cell-based assays using an in-house panel of HMCLs (n>50) representing WT- and mutant-RAS, as well as innate and acquired response/resistance to the standard of care drugs, proteasome inhibitors (PIs) and immunomodulatory drugs (IMiDs), to confirm the potency of novel selective BIRC5 inhibitors, as single agent (IC50 range 0.22-15.30 nM; Mean 4.431±1.041 nM) and in combination with PIs and IMiDs (Chou-Talalay's Combination Index or CI <0.3, indicating strong synergism). Further, we used bulk and single-cell whole-transcriptomics, siRNA-mediated gene knockdown studies, and functional validation to characterize the treatment-induced genes and molecular pathways underpinning the mechanism of action and drug synergy at the subclone level. Finally, we compared the efficacy of these BIRC5 inhibitors against several RAS inhibitors, including cyclorasin B4-27, a bicyclic peptidyl pan-RAS inhibitor, RMC-6236, a multi-selective noncovalent RAS(on) inhibitor, and ADT-007, a novel, highly potent, and selective pan-RAS inhibitor that we have synthesized, and observed comparable effects on cell death and apoptosis. Ex vivo analysis in bone marrow-derived CD138+ cells from myeloma patients using high-throughput Mass Cytometry (CyTOF or Cytometry by Time-Of-Flight) confirmed the dose-dependent reduction of MCL1, Ki-67, CCND1, c-KIT, and MYC. We will present these results that demonstrate the clinical potential of BIRC5 inhibitors as novel candidates in curbing progression and drug resistance in RAS-mutant myeloma.

Abstract Multiple Myeloma (MM) is an incurable plasma cell malignancy that progresses from the precursor condition monoclonal gammopathy of undetermined significance (MGUS). African Americans (AA) have the highest incidence of MGUS and MM of any population group in the U.S., with ∼1.5-2-fold higher age-adjusted incidence than European Americans (EA) for reasons that remain unclear. Despite the increased incidence, MM tumors in AA patients show fewer TP53 deletions/mutations and high-risk cytogenetic features compared to EA patients. Studies also show that, with equal access to care, AA patients have better overall survival (OS) independent of age. Given recent studies demonstrating accelerated biological aging in AA individuals, we hypothesize that immunosenescence that occurs with aging reduces the immune pressure on MM cells, resulting in the increased emergence of less aggressive tumors. To test this, we utilized viably frozen bone marrow samples from the Mayo Clinic Myeloma Biobank. We profiled samples from 128 individuals (N= 53 and 75 AA vs. EA, respectively) with either newly diagnosed MM (NDMM) or treated MM (N= 27 and 38 AA vs. EA, respectively), MGUS (N=18 and 23 AA vs. EA, respectively), or healthy controls (N= 8 and 14 AA vs. EA, respectively) by mass cytometry (CyTOF) (N= 17 MGUS, 55 MM and 22 healthy controls) using the CyTOF Human Immune Profile Assay or by single cell RNA-sequencing (scRNA-seq, N= 24 MGUS/SMM and 10 MM). Profiling of the CD45+ non-tumor lymphocytes by scRNA-seq revealed AA patients exhibited increased T cell populations (odds ratio (OR)=2.3), including a reduction in CD8+ effector memory (OR=0.94) and an increase in CD8+ cytotoxic effector (OR=1.02) in a multivariate model adjusting for age and sex. Analysis by CyTOF confirmed an increase in overall CD3+ T cells (49.5% vs. 35.3%, p=0.0001) including increases in CD8+ terminal effector (9.5% vs. 5.2%, p=0.021) and CD4+ terminal effector T cells (5.5% vs. 2.7%, p=5.7x10^-6) among AA patients, and this difference remained after adjusting for age and sex. Within the CD8+ terminal effector T cells, we also noted increases in CD57+/CD28- senescent T cells, consistent with immune exhaustion that occurs with biological aging. We are currently working to assess whether AA patients with MGUS and MM exhibit accelerated biological aging as measured by frailty index, peripheral senescence associated secretory phenotypes, and PBMC epigenetic clock scores. We plan to extend our analysis of the immune microenvironment to assess patient T cell function ex vivo. Finally, we will evaluate whether MM cells from AA patients exhibit increased sensitivity to control cytotoxic T cell induced cell death in vitro compared to cells from EA patients. The results from this study will allow further understanding of components causing the increased risk for MM development seen in AA individuals. Citation Format: Alani Perkin, Megan Moore Weivoda, Linda Baughn. Immunosenescence driven T-cell remodeling may underlie increased risk of Multiple Myeloma in African Americans [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr A051.

Abstract Motivation Efforts to address health disparities are often limited by the lack of robust computational tools for inferring genetic ancestry by calculating an individual’s genetic similarity to continental groups. We have already shown that a preferred alternative to self-described race is using ancestry-informative markers (AIMs) that can be classified into ancestral components and used to estimate their similarity to those of known populations to identify continental groups. However, real-world genomic data can present challenges, including limited availability of germline DNA, a small number of AIMs for each sample, and the use of different variant calling software, limiting the application of existing solutions. Results Here, we describe a novel supervised machine-learning tool AncestryGeni, which infers genetic ancestry for samples with even a hundred markers and is applicable to any genomic data, including whole exome sequencing (WES) and RNA sequencing (RNA-Seq) data. Applying AncestryGeni to a real-world genomic dataset obtained from the Multiple Myeloma Research Foundation (MMRF) CoMMpass study, we show that it is more accurate than the commonly used FastNGSadmix when using nonstandard genomic material. We also demonstrate that when using AncestryGeni, the tumor-derived sequence obtained from WES and RNA-Seq can be a robust data source to accurately estimate an individual’s genetic similarity to a continental group. Availability and implementation AncestryGeni pipeline is available at https://github.com/eelhaik/AncestryGeni/tree/main.

Abstract Monoclonal antibodies targeting CD38 are a therapeutic mainstay in multiple myeloma (MM). Although they have contributed to improved outcomes, most patients still experience disease relapse, and little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape has been implicated as a mechanism of tumor-cell evasion in immunotherapy. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, we analyzed whole-genome and whole-exome sequencing data from patients 701 newly diagnosed MM, 67 patients at relapse with naivety to anti-CD38 antibodies, and 50 patients collected at relapse after anti-CD38 antibodies. We report a loss of CD38 in 10 of 50 patients (20%) after CD38 therapy, 3 of whom exhibited a loss of both copies. Two of these cases showed convergent evolution in which distinct subclones independently acquired similar advantageous variants. Functional studies on missense mutations involved in biallelic CD38 events revealed that 2 variants, L153H and C275Y, decreased binding affinity and antibody-dependent cellular cytotoxicity of the commercial antibodies daratumumab and isatuximab. However, a third mutation, R140G, conferred selective resistance to daratumumab, while retaining sensitivity to isatuximab. Clinically, patients with MM are often rechallenged with CD38 antibodies after disease progression and these data suggest that next-generation sequencing may play a role in subsequent treatment selection for a subset of patients.

Abstract Multiple myeloma (MM) is an incurable malignancy of clonally expanded plasma cells shaped by complex interactions with the immune microenvironment. To investigate immune factors driving treatment response and resistance, we conducted multi-omics profiling including CD138 neg single-cell RNA sequencing of 243 bone marrow samples from 102 patients (631,226 cells) and CD138 pos bulk RNA and whole-genome sequencing from 209 samples. Longitudinal analyses revealed that interferon gamma signaling impairs T cell memory after autologous stem cell transplant, while naïve B cell abundance and immunoglobulin diversity correlated with improved progression-free survival (HR = 0.48, p = 2.3e -4 ). At disease progression, MM cells upregulated cancer-testis antigens and immune effector genes, with concurrent B cell depletion, enrichment of myeloid-derived suppressor cell genes in monocytes, and T cell exhaustion. These findings highlight dynamic immune-tumor interactions, identifying naïve B cell reconstitution as a biomarker of durable response, and cancer-testis antigens as potential targets for high-risk disease at progression. Statement of Significance Longitudinal profiling of multiple myeloma and the immune microenvironment revealed dynamic immune-tumor interactions across the disease course. Dysfunctional CD8⁺ T cells limited memory formation post-transplant, while naïve B recovery associated with sustained treatment response. At progression, cancer-testis antigen expression associated with immunosuppression, revealing novel mechanisms of immune escape.

e19545 Background: Cytogenetic abnormalities (CA) at diagnosis are important prognostic factors in multiple myeloma (MM), but there is limited information on how these abnormalities evolve at first relapse and their significance. Methods: This retrospective study included patients aged ≥18 years, with a confirmed diagnosis of MM who experienced at least one disease relapse and had fluorescence in situ hybridization analysis within six months of both diagnosis and relapse. Data on CA and clinical outcomes were collected. High-risk (HR) secondary CA were defined as the presence of deletion of chromosome 17p (del17p) or gain or amplification of chromosome 1q. The primary objective was to evaluate changes in HR secondary CA at first relapse, while the secondary objective was to assess the impact of the cytogenetic changes on overall survival (OS) from diagnosis. Based on the presence or absence of HR secondary CA, patients who were tested for HR secondary CA at both time points were classified into four groups: 1) persistent absence of HR secondary CA, 2) emergence of HR secondary CA at relapse, 3) persistent presence of HR secondary CA, and 4) loss of HR secondary CA at relapse. Results: A total of 233 patients diagnosed between 2004 and 2023 were included. HR secondary CA were tested in 98.7% (n= 230) of patients at diagnosis, with 24.8% (n=57) testing positive. At first relapse, testing for HR secondary CA was performed in 97.4% (n=227) of patients, of whom 23.8% (n=54) tested positive. Del17p was evaluated in 98.3% (n=229) of patients at baseline and 95.7% (n=223) at relapse, with positivity increasing from 10.9% (n=25) to 15.3% (n=34). Gain or amplification of chromosome 1q was evaluated in 49.4% (n=115) at baseline and 25.5% (n=60) at relapse, with positivity rate rising from 28.7% (n=33) to 38.3% (n=23). There were no differences in overall response rate or very-good-partial-response-or-better rates to the initial therapy at diagnosis between the groups. (Table) Emergence/persistence of HR CA were associated with lower OS from diagnosis. Conclusions: Emergence of HR secondary CA at first relapse in MM has prognostic significance. These findings highlight the importance of serial cytogenetic testing for risk stratification. Response rate to initial line of therapy and overall survival from diagnosis among patients tested for HR secondary CA both at diagnosis and first relapse (n=224). Outcome Persistent absence of HR secondary CA(n=142) Emergence of HR secondary CA at relapse (n=25) Persistent presence of HR secondary CA (n=27) Loss of HR secondary CA at relapse(n=30) p-value Overall response rate a 75% (106) 76% (19) 63% (17) 67% (20) 0.5 b Very-good-partial response or better response rate 43% (61) 36% (9) 44% (12) 40% (12) >0.9 b Median (95% CI) OS from diagnosis in years 11.3 (9.7-13.4) 7.5 (5.1-12.1) 6.1 (4.2-9.4) 10.1 (6.5-14.1) <0.0001 c a Partial response or better; b Chi-square test; c Log-rank test.

7541 Background: Multiple myeloma (MM) is characterized by recurrent cytogenetic abnormalities, including translocations involving the immunoglobulin heavy chain locus on chromosome 14 and trisomies, which are considered primary and clonal. Throughout disease progression, MM cells may acquire additional abnormalities, which include chromosome 1 abnormalities (gain or amplification of 1q or deletion of 1p) and chromosome 17 abnormalities (del 17p or monosomy 17p). All these factors are considered high-risk markers that predict below-average outcomes. While outcomes related to 1q have been documented, their relationship with other abnormalities and clinical characteristics is less clearly defined. Methods: We created a cohort of newly diagnosed MM (NDMM) patients from April 1996 to December 2023 for whom FISH testing was performed using a panel that included 1q findings. Data on clinical and laboratory characteristics, other FISH abnormalities, and survival outcomes were collected from existing databases and the electronic medical record (EMR). Results: The cohort included 875 patients, with a median age of 65. Of these patients, 60% were male and 91% identified as white. A 1q abnormality was observed in 443 patients (51%); 87% exhibited a gain of 1q, while 13% showed amplification of 1q. Among those tested, other abnormalities included del13 (58%), t(11;14) (25%), t(4;14) (17%), t(14;16) (6%), del 17p (13%), and trisomies (51%). The distribution of abnormalities concerning the presence of 1q is presented in the table. Patients with 1q abnormalities were more likely to present with additional high-risk cytogenetic abnormalities. The median overall survival (OS) for those with a 1q abnormality was 73 months, compared to 105 months for those without it. Among these, patients with 1q amplification tended to have worse outcomes than those with a 1q gain, though this observation did not reach statistical significance. Conclusions: Abnormalities of chromosome 1, including 1q gain and amplification, can be seen in nearly 50% of patients with NDMM who are tested. 1q abnormalities are associated with other high-risk cytogenetic abnormalities. Measures of disease burden are higher among those with a 1q abnormality. Interestingly, we observed a higher proportion of patients with lambda light chain and those with IgA among those with a 1q abnormality. The presence of a 1q abnormality was associated with inferior survival, with a trend towards worse outcomes among those with 1q amplification compared to 1q gain. Clinical characteristics and cytogenetic associations of multiple myeloma patients with and without 1q abnormalities. 1q abnormality present 1q abnormality absent P del13 78% 39% <0.01 t(4;14) 25% 8% <0.01 t(11;14) 22% 27% NS t(14;16) 15% 3% <0.01 Trisomies 48% 53% NS 17p del 24% 12% <0.01 Lambda light chain 45% 26% <0.01 IgA 32% 16% <0.01 Hemoglobin 10.3 g/dL 11.2 g/dL <0.01