Lehman, Stacey L.

Abstract Background: Monoclonal B-cell lymphocytosis (MBL), a precursor to chronic lymphocytic leukemia (CLL), is an understudied yet common premalignant condition present in ~8 million adults in the United States. Based on flow cytometry, MBL can be classified into two immunophenotypes: CLL-type (CD5, CD23, and CD20 co-expression) and non-CLL-type (CD5-negative). While the majority of the data to date pertains to CLL-type MBL, the available evidence indicates non-CLL-type MBL is also associated with an increased risk of hematologic malignancies. Clonal hematopoiesis of indeterminate potential (CHIP) is another precursor condition associated with hematologic malignancies. The relationship between non-CLL-type MBL and CHIP and their combined effect remains unknown. Herein, we report findings on these two precursor conditions in the largest screening cohort to date. Methods: Using flow cytometry, we screened for MBL in the Mayo Clinic Biobank participants who were 40 years or older with no prior history of hematologic cancers. Using whole-exome sequencing of whole-blood DNA, CHIP was screened on 291 genes related to myeloid (56 genes) or lymphoid malignancies (235 genes). Incident hematologic malignancies were detected during follow-up using International Classification of Diseases (ICD) codes in the medical record. All diagnoses were manually reviewed for confirmation. Multivariable logistic regression was used to evaluate the association between non-CLL-type MBL and CHIP. Time to incident hematologic malignancy was calculated from date of MBL screening to the earliest date of incident malignancy, withdrawal, death, last medical visit, or study end. Overall survival (OS) was calculated from date of MBL screening to date of death or last known alive. Multivariable Cox regression, adjusted for age, sex and residency, was used to investigate associations between non-CLL-type MBL and CHIP with clinical outcomes; with results reported using hazard ratios (HR) and 95% confidence intervals (CI). Results: In total, 8,802 individuals with MBL screening and CHIP data were analyzed. Non-CLL-type MBL was detected in 249 (2.8%) individuals; 121 (49%) were male, and median age was 78 years (range, 47-95). We identified 757 (8.6%) individuals with CHIP in at least one of the 291 genes tested. The most frequently mutated CHIP genes were DNMT3A, TET2, ASXL1, PPM1D, and TP53. A total of 47 (0.5%) individuals had both non-CLL-type MBL and CHIP; the four genes with the highest number of CHIP variants in these individuals were DNMT3A (n=16), TET2 (n=10), ASXL1 (n=3), and ATM (n=3). An association between non-CLL-type MBL and any CHIP (OR=1.6, 95%CI:1.2-2.3, P=0.006) was observed. When analyzing CHIP in genes related to myeloid malignancies, the association with non-CLL-type MBL was also significant (OR=1.6, 95%CI:1.1-2.3, P=0.012); however, the association was not statistically significant for genes related to lymphoid malignancies (OR=1.6, 95%CI:0.8-3.3, P=0.165). With a median follow-up of 5.4 years, 104 individuals developed incident hematologic malignancies (66 lymphoid and 38 myeloid malignancies). Non-CLL-type MBL (HR=3.5, 95%CI:1.9-6.5, P<0.001) and CHIP (HR=3.2, 95%CI:2.1-5.1, P<0.001) were each associated with increased risk of incident hematologic malignancies. Co-existence of both precursor conditions was associated with a substantially higher risk of incident hematologic malignancies (HR=10.3, 95%CI:4.0-26.2, P<0.001) compared to individuals with neither precursor condition. Among individuals with non-CLL-like MBL, any CHIP was a borderline significant predictor for incident hematologic malignancy (HR=3.6, 95%CI:1.0-12.9, P=0.049). Compared to individuals with no precursor conditions, OS was not significantly different in those with non-CLL-type MBL-only (HR=1.1, 95%CI:0.8-1.5, P=0.40), those with CHIP-only (HR=1.2, 95%CI:0.99-1.4, P=0.06), or those with both CHIP and non-CLL-type MBL (HR=1.3, 95%CI:0.8-2.1, P=0.39). Conclusions: In the largest screening cohort to date evaluating the relationship of CHIP and non-CLL-type MBL, we found that non-CLL-type MBL and CHIP are associated with each other. Individuals with non-CLL-type MBL were more likely to have CHIP variants in DNMT3A, TET2, ASXL1, and ATM. Among individuals with non-CLL-type MBL, the presence of any CHIP was associated with increased risk of developing hematologic malignancy.

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 Background Mosaic chromosomal alterations (mCAs) are large-scale somatic gains, losses, or copy-neutral loss of heterozygosity (CNLOH) detectable by genotyping of peripheral blood DNA. They represent a form of clonal hematopoiesis and are observed in 0.5-5% of cancer-free individuals. The presence of any autosomal mCA has been associated with >3-fold risk of hematological malignancies. In particular, mCAs occurring in regions related to lymphoid malignancies have an 11-fold increased risk of lymphoid malignancies and a 68.6-fold risk for chronic lymphocytic leukemia (CLL). Monoclonal B-cell lymphocytosis (MBL), the precursor state to CLL, is defined by <5×10⁹/L clonal B cells in otherwise healthy individuals and is classified as low-count (<0.5x109/L) or high-count (0.5-5x10⁹/L) based on clonal B-cell count. MBL is also associated with increased risk of lymphoid malignancy (beyond CLL), with 4.3-fold and 74-fold risk in individuals with low- and high-count MBL, respectively. We previously reported a significant enrichment of autosomal mCAs in MBL, demonstrating a 1.7-fold association in those with low-count MBL and a 50.5-fold association in those with high-count MBL. Whether mCAs independently predict lymphoid malignancy risk after accounting for MBL status is unknown. Here, we evaluated the impact of mCAs on risk of incident lymphoid malignancies in individuals with MBL and in individuals screened negative for MBL. Methods CLL-type MBL (CD5 positive) was identified using flow cytometry assay on peripheral blood. Participants were age ≥40, had no prior hematologic malignancy, and were enrolled through the Mayo Clinic Biobank or the Division of Hematology at Mayo Clinic, Rochester. Participants were followed for incident lymphoid malignancy, including CLL, with diagnoses confirmed by medical record review. mCAs with cell fraction >1% were detected from array-based genotyping of whole blood DNA. Cox proportional hazards models, adjusted for age and sex, estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of developing an incident lymphoid malignancy in individuals with autosomal mCA versus those without an autosomal mCA. Results In 4,331 participants with available MBL and mCA status, the median age was 67 years, and 45% were male. Flow cytometry identified 3,231 individuals who screened negative for MBL, 754 individuals with low-count MBL, and 346 individuals with high-count MBL. Autosomal mCAs were present in 6.5% of individuals without MBL, 7.6% with low-count MBL, and 71.1% with high-count MBL. Over a median follow-up of 6.9 years, 237 individuals developed an incident lymphoid malignancy. The most common types were CLL, multiple myeloma, and diffuse large B-cell lymphoma. Ignoring MBL status, the presence of an autosomal mCA was associated with increased risk of lymphoid malignancy (HR = 2.65; 95% CI: 1.45–4.86; P = 0.002), replicating previous results. However, after excluding individuals with MBL, this association attenuated; those with mCA alone did not have a significantly elevated risk (HR = 1.60; 95% CI: 0.57-4.52; P = 0.38) compared to individuals without MBL or mCA. We next examined the effect of mCAs among individuals with MBL. In those with low-count MBL, the most frequent mCA events were 13q loss (2.1%), 12 gain (1.9%), and 4q CNLOH (1.2%), and individuals with an mCA had a borderline significant risk of developing a lymphoid malignancy (HR = 2.78; 95% CI: 1.01–7.67; P = 0.049) compared to those without an mCA. Similarly, in those with high-count MBL, the most frequent mCA events were 13q loss/CNLOH (31.2%), 12 gain (13.0%), and 11q loss (4.9%), and the presence of an mCA conferred an increased risk compared to those without mCA (HR = 1.51; 95% CI: 1.09-2.08; P = 0.012). Conclusions Autosomal mCAs were more frequent in individuals with high-count MBL compared to those with low-count or no MBL. mCAs showed limited predictive value for lymphoid malignancy among individuals without MBL. In contrast, in individuals with low-count MBL, autosomal mCAs emerged as a potential biomarker for identifying those at risk of developing a lymphoid malignancy. In high-count MBL, mCAs were also a biomarker, but were driven by known chromosomal abnormalities identified through clinical testing. These findings suggest that the utility of mCAs as a predictive marker for lymphoid malignancy is contingent on the presence of MBL and may inform risk stratification and surveillance strategies in this population.

Background: Monoclonal B-cell lymphocytosis (MBL) is a common premalignant condition that can be classified into chronic lymphocytic leukemia (CLL)-type (CD5, CD23, and CD20 co-expression), and non-CLL-type (CD5-negative) based on flow cytometry immunophenotypes. CLL-type MBL is relatively well characterized with increased risk of hematologic (especially lymphoid) malignancies, serious infections, and decreased response to vaccinations. However, the prevalence, genetic predispositions, and clinical consequences of non-CLL-type MBL remain to be fully elucidated. Herein, we report findings in non-CLL-type MBL in a large screening cohort. Methods: We screened 10,330 individuals (40 years or older with no prior history of hematologic cancers) for MBL with highly sensitive flow cytometry, in the Mayo Clinic Biobank, with patients recruited from primary care-based clinics. Individuals were genotyped by Regeneron Genetics. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). Among those individuals residing in the 27 counties surrounding Rochester, Minnesota, we identified incident hematologic malignancies and melanomas using ICD codes and the Rochester Epidemiology Project, a population based medical records linkage system. All diagnoses were manually reviewed for confirmation. Cox regression was used to calculate hazard ratios (HR) and 95% CIs, adjusted for age and sex. Results: We identified 1,736 individuals with MBL and 8,341 individuals without MBL. Among those with MBL, 246 (14.2%) had non-CLL-type MBL as the major clone. The median age of non-CLL-type MBL was 77 years (range, 47-95). The prevalence of non-CLL-type MBL significantly increased with age, with 0.5% prevalence among those between 40 to 59 years of age, 2.3% prevalence among those between 60 and 79 years, and 7.8% prevalence in those 80 years of age or older. The prevalence of non-CLL-type MBL was significantly higher (P < .001) among males (3.1%) than females (2.0%). Using the genome-wide complex trait analysis tool, the heritability of non-CLL-type MBL was estimated to be ~26%, suggesting inherited genetics plays a role in etiology. To identify common inherited variants, we first evaluated the known CLL susceptibility variants, many of which also associated with CLL-type MBL. Among the 42 variants, none were statistically associated (all P > .05) with non-CLL-type MBL. We next conducted a genome-wide association study to identify novel variants, and the most significant variant resided in 10q26.3 (minor allele frequency [MAF]control = 0.7%, MAFMBL = 3.5%, OR = 6.4, 95% CI 3.6-11.3, P = 5.7 * 10-8). Among the 6,478 individuals (192 with non-CLL-type MBL and 6,286 without MBL) followed for incident hematologic malignancies, 36 developed lymphoid and 23 developed myeloid malignancies after a median of 4.2 years of follow up. Similar to CLL-type MBL, non-CLL-type MBL was associated with a 5.2-fold risk for lymphoid malignancies (95% CI 2.0-13.0, P < .001). Elevated but not significant risks were observed for myeloid malignancies (HR = 2.3, 95% CI 0.5-10.3, P = 0.27). The lymphoid malignancies developed by individuals with non-CLL-type MBL included diffuse large B-cell lymphoma, multiple myeloma, marginal zone lymphoma, and other low-grade lymphomas. We recently reported that individuals with CLL-type MBL are at higher risk for developing melanoma (HR = 1.9, 95% CI 1.3-2.8). Interestingly, non-CLL-type MBL had no evidence of an association with melanoma risk (HR = 0.4, 95% CI 0.1-1.8). We did not observe a significant difference in overall survival between individuals with non-CLL-type MBL vs those without MBL. Conclusions: In the largest screening cohort to date, we evaluated the etiology and clinical outcomes of non-CLL-type MBL, an understudied yet common condition that occurs in ~4 million adults in the United States. Non-CLL-type MBL is more common in men and older individuals, and evidence supports that inherited genetics plays an etiological role with 10q26.3 locus identified as a novel susceptibility locus. Individuals with non-CLL-type MBL had significantly increased risk of lymphoid malignancies, similar to CLL-type MBL, but, distinct from CLL-type MBL, no evidence of an increased risk of melanoma. Our study provides insights into the prevalence, genetic predispositions and clinical consequences of non-CLL-type MBL and how it differs from the classic CLL-type MBL.

Background: Multiple myeloma (MM) is an incurable plasma cell malignancy with several recurrent primary cytogenetic abnormalities including t(11,14)(q13;q32), resulting in increased expression of CCND1. Although 40% of patients with t(11;14) MM respond favorably to the BCL-2 inhibitor venetoclax (ven), 60% fail to achieve an objective response. Previous studies have suggested upregulation of PMAIP1, encoding the pro-apoptotic NOXA protein, in association with ven sensitivity (Leblay, Blood, 2024). Here we sought to evaluate the role for NOXA in ven response in t(11;14) MM. Methods: We analyzed whole exome, whole genome and RNA sequencing data of CD138+ tumor cells from 1,359 patients with MM in the CoMMpass and Mayo Clinic cohorts. The histone mark H3K27ac was assessed in t(11;14)+ KMS12PE and U266B1 human myeloma cell lines using ChIP-seq. Gene expression and protein levels of PMAIP1 (NOXA) were also detected by qRT-PCR and Western blot, respectively. Live cell detection was evaluated by Annexin V and PI using flow cytometry and by YoYo3 dye using IncuCyte following treatment with ven. Results: The t(11;14) MM subtype was associated with a 1.6-5.5-fold increased expression of PMAIP1 compared to non-t(11,14) MM in the CoMMpass and Mayo Clinic cohorts (p<0.0001). These findings are consistent with a significant correlation between CCND1 and PMAIP1 expression in both cohorts (p<0.001). To evaluate whether cyclin D1 is directly associated with increasing expression of PMAIP1 in t(11;14) MM, we generated a cyclin D1 knock out (KO) version of the U266B1 line using CRISPR/cas9. Two independent U266B1 KO cell lines showed reduced expression of PMAIP1 and NOXA protein compared to the WT U266B1 consistent with a role for cyclin D1 in regulating PMAIP1 expression. In addition, the KO lines had a 4.8-fold reduced H3K27ac signal at the PMAIP1 locus in comparison to the WT control suggesting a role for cyclin D1 in promoting H3K27ac. We previously observed increased expression of CCND1 in association with the G allele compared to the A allele of rs9344 in both the CoMMpass and Mayo Clinic cohorts (Leukemia, in press). We next asked whether the G risk allele of rs9344 within CCND1 impacted gene expression and H3k27ac levels at the PMAIP1 locus. To study the allele specific effect of CCND1, we used the CRISPR/cas9 edited KMS12PE WT (rs9344 AA) and Knock In (KI) (rs9344 GG) cell lines. In the KI cells, the G allele was accompanied by an ~2-fold increased expression of PMAIP1 and NOXA protein detected by western blot (<0.05). Increased PMAIP1 expression in KI lines was also accompanied by a 2.2-fold increased H3K27ac further suggesting a role for the G allele of rs9344 in promoting H3K27ac and gene expression at the PMAIP1 locus. Finally, we evaluated the consequence of PMAIP1 expression levels in relation to ven response. Increased expression of PMAIP1 and elevated levels of NOXA protein in the KMS12PE KI lines was associated with increased sensitivity to ven resulting in ~50% increase in cell death of KI vs. WT lines (p<0.02). Conclusion: We demonstrate a role for cyclin D1 in regulating PMAIP1 expression through H3K27ac resulting in increased NOXA protein. Levels of NOXA are associated with the G allele of rs9344 and increased venetoclax response.

Introduction: Cyclin D1, encoded by the CCND1 gene, is primarily known as a major regulator of cell cycle progression. Emerging studies have demonstrated a role for cyclin D1 in regulating gene transcription. In mantle cell lymphoma with t(11;14), cyclin D1 strongly binds to the promoters of highly transcribed genes and its overexpression led to genome-wide transcriptional downregulation. However, the transcriptional role for cyclin D1 in t(11;14) MM remains undefined. This study aims to elucidate the global chromatin and transcriptional changes induced by cyclin D1 in t(11;14) MM. Methods: Knockout (KO) of CCND1 in U266B1, a MM cell line carrying t(11;14), was performed by the Synthego (Redwood City, CA) using CRISPR/Cas9, which generated a frameshift insertion of base pair (bp) “A” after 69,641,478 bp within exon 1. Two independent KO clones were used for downstream analysis. ChIP-seq and ATAC-seq were performed for KO (n=2) and wild-type clones (WT, n=2). ChIP-seq used antibodies against H3K4me3 (promoter) and H3K4me1 and H3K27ac (enhancer). Libraries were sequenced to 2x51 bp on the Illumina NextSeq 2000 platform. Total RNA libraries (in triplicate) were sequenced to 2x150 bp. ChIP-seq and ATAC-seq reads were mapped to hg38 with BWA, and peaks were identified by MACS2 at FDR 0.01. RNA-seq reads were mapped to hg38 with STAR and gene raw counts were estimated using featureCounts. Differential peaks and differentially expressed genes between KO and WT were identified using edgeR at FDR 0.05 and fold-change 2. Only peaks present in at least 2 samples and genes having reads-per-million value 0.1 in at least 1 sample were included, excluding those from chrY. Pathway analysis was performed with the Enrichr package. Results: Differential expression analysis identified 2-fold more genes that were down-regulated than up-regulated in KO compared to WT (467 vs. 233). Pathway analysis revealed an enrichment of TNF-alpha signaling via NF-kappaB, inflammatory response, and apoptosis in association with down-regulated genes, while up-regulated genes are enriched in myogenesis, KRAS signaling, and epithelial mesenchymal transition pathway. In parallel, differential chromatin analysis identified 2.5% (1,161) of the peaks from H3K27ac and 0.5-1% (359-610) of the peaks for the other 3 marks that showed significant changes of signal levels between KO and WT. For the promoter mark H3K4me3, there are largely a comparable number of peaks showing increased (191 peaks) and decreased (168 peaks) signals, respectively, in KO compared to WT. However, for ATAC-seq and H3K4me1, about 70% of the differential peaks showed an increased signal in KO, in contrast with H3K27ac for which 60% of differential peaks showed decreased signal in KO. The preferential loss of H3K27ac occupancy is consistent with the observation of a higher proportion of genes being down-regulated in KO. These results indicated that knockout of CCND1 led to a global increase of chromatin accessibility, but a reduction of H3K27ac and gene expression. Further annotation revealed that, for H3K27ac and H3K4me1/ATAC-seq, 92% and 97% of the differential peaks were located >2kb away from the transcription start sites (TSSs) of expressed genes. Even for H3K4me3, 88% of the differential peaks are >2kb away from TSSs. The results suggest that the changes of chromatin upon CCND1 knockout predominantly occurred at distal regulatory regions. For up- and down-regulated genes, we estimated ChIP-seq and ATAC-seq signals in the TSS 2kb regions, revealing that up-regulated genes were overall associated with increased signals. Further analysis found that, for ATAC-seq and H3K4me3, 44% and 59% of the differential peaks located in the promoter regions were associated with differentially expressed genes, which dropped to ~20% for the two enhancer marks. These data indicate that changes in chromatin state impact the expression of the associated genes. Conclusion: Knockout of CCND1 impacts local chromatin state, particularly at enhancer regions, and the transcriptional program. In promoter-proximal regulatory regions, the changes of chromatin accessibility and H3K4me3 are strongly correlated with the expression changes of nearby genes. Further studies will identify the genes targeted by the differential enhancers and their possible roles in MM pathogenesis mediated by cyclin D1 following the t(11;14) event.

Abstract Multiple myeloma (MM) is the most common blood cancer in African American (AA) individuals. AAs have an increased risk of developing Monoclonal Gammopathy of Undetermined Significance (MGUS) and MM compared to non-Hispanic White (NHW) individuals. While several studies have shown a pivotal role for the immune tumor microenvironment (iTME) in MM pathogenesis, the composition of the iTME in AAs with MM is under investigated. Viably frozen whole bone marrow (BM) aspirates from 128 individuals (53 AA and 75 NHW) with either MM (n=65), MGUS (n=28), smoldering MM (SMM, n=13), or healthy controls (n=22) were evaluated by single cell RNA-sequencing (scRNA-seq) or mass cytometry (CyTOF). We characterized 34 (14 AA and 20 NHW) by scRNA-seq and 94 (39 AA and 55 NHW) by CyTOF. CyTOF samples were stained with Maxpar Direct Immune Profiling Assay Kit (Fluidigm), acquired on a Helios mass cytometer and analyzed in Cytobank. Data were analyzed by logistic equivalent regression model with p<0.05 for significance. ScRNA-seq samples were processed as in Yao, 2022. Data were normalized using scvi-tools and clustered by Uniform manifold approximation and projection (UMAP). Differentially expressed markers between clusters were identified using Model-based Analysis of Single-cell Transcriptomics (MAST) in Seurat R package at FDR < 0.05 and log2 fold change > 0.55. ScRNA-seq of the CD45+ non-tumor lymphocytes revealed 17 immune populations (HSC, erythroblast, MDSC, GMP, CD1c+ DC, CD4+ and CD8+ T cell, CD14+ M1 macrophage, CD16+monocyte, monocyte, pDC, naïve B, pre-B, pro-B, memory B, NK/MAIT). CD3E/D+cells were clustered into naïve/central memory (CCR7+, LEF1+, SELL+), memory (GZMK+), effector (GZMB+, GZMH+, FGFBP2+), g/d (TRDC+), MAIT (SLC4A10+, KLRB1+) and IFN CD8+ T cells (IFIT1+, IFIT2+,IFIT3+). Disease progression was associated with increases in median CD4+ and CD8+ GZMK+ T cells, memory B cells and a reduction in all monocyte clusters. Within the diseased cohort in comparison to NHW patients, AA patients had increased CD3+ T cells (CD4 and CD8+) (AA 57.5% vs. NHW 44.3%) and a reduction in overall monocytes (AA 10.5% vs. 26.5%). These results were validated by CyTOF, which confirmed an increase in CD3+ T cells (AA 53.7% vs. NHW 35.7%, p<0.001) including increases in CD8+ (AA 7.0% vs. NHW 3.2%, p<0.05) and CD4+ terminal effector T cells (AA 5.7% vs. NHW 2.7%, p<0.05) and a reduction in monocytes (AA 18.3% vs. NHW 26.6%) among AAs. After adjusting for age and sex, AAs retained an increase in T cells (OR 1.59 (95%CI 1.2-2.01, p=0.00023)) and a reduction in monocytes (OR 0.88 (95%CI 0.78-1, p=0.045)). Despite the increase in CD8+ T cells in AA patients, we identified reduced GZMK+ T cells and reductions in exhaustion markers (TIGIT, LAG3, TOX) in CD8+ T cells in comparison to NHWs. Nevertheless, the distribution of the immune populations was similar between healthy AA and NHW individuals. Our multiomics approach to characterize the iTME identified significant differences among AA compared to NHW patients with MM. Citation Format: Suganti Shivaram, Hongwei Tang, Huihuang Yan, Shulan Tian, Guyu Qin, Emilie Anderson, Neeraj Sharma, Abiola Bolarinwa, Cinthya Zepeda-Mendoza, Stacey Lehman, Felicia Gomez, Amit Mitra, Surendra Dasari, Taxiarchis Kourelis, Shaji Kumar, Linda Baughn. Characterization of the Immune Tumor Microenvironment in a Diverse Cohort of Patients with Multiple Myeloma [abstract]. In: Proceedings of the Blood Cancer Discovery Symposium; 2024 Mar 4-6; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P06.