Michaud, Marina E.

The bone marrow immune microenvironment (BMME) is a critical factor in multiple myeloma (MM) pathogenesis. Despite higher incidence of MM among self-identified African Americans, the relationship between African genetic similarity and the BMME remains unclear. We present the largest analysis to date assessing the impact of Ancestry on the BMME in myeloma (N=320, including 64 with ≥50% African genetic similarity, AFR-High) leveraging our recently generated Immune Atlas. AFR-High was associated with enrichment of late T-effector cells, driven by rare cytotoxic CD4⁺ T cells, suggesting a distinct adaptive BMME. AFR-High exhibited expansion of late-differentiated adaptive NK cells with high cytotoxic GNLY and GZMH expression. AFR-High depicted reduced CD14⁺ monocytes, increased CD16⁺ non-classical monocytes, and expansion of macrophage-like monocyte populations with enrichment of metabolic adaptation, efferocytosis and phagocytic clearance programs, and immunoregulatory pathways. These findings reveal a shift from an innate inflammatory immune landscape toward adaptive cytotoxic and immunoregulatory remodeling associated with African genetic similarity in MM.

Abstract Although the human genome encodes a vast repertoire of noncoding RNAs that regulate gene expression, the noncoding genome remains underexplored due to technical challenges. Specifically, during transcriptomic sequencing data alignment, the overlap between noncoding and coding loci can create ambiguous read alignments that are subsequently discarded from downstream analysis. For this reason, most of the noncoding genome is excluded from standard genomic annotations used for sequencing alignment. To address this challenge and enable concurrent profiling of the coding and noncoding transcriptome, we systematically integrated standard coding (GENCODE) and noncoding (LncBook) genome annotations, preserving coding gene annotations and removing overlapping noncoding regions. The resulting integrated genome annotation expanded the number of annotated noncoding genes from 40,785 to 138,296 while preserving all coding genes and reducing ambiguous read assignment. To evaluate the utility of our integrated genome annotation for uncovering novel, biologically relevant noncoding RNAs (ncRNAs), we realigned CD138-positive bulk RNA-seq (N = 942) and CD138-negative single-cell RNA-seq (N = 478) data from the MMRF CoMMpass study, generating a comprehensive coding-noncoding atlas of the myeloma bone marrow microenvironment with noncoding genes representing 51% of highly variable genes and displaying significant cell type specificity. Tumor expression profiling based on this integrated profiling identified 15 clusters, including two enriched for amp(1q21) or t(4;14) and associated with shorter progression-free survival (PFS). Differential expression and systematic filtering yielded 19 candidate high-risk ncRNAs, including previously uncharacterized ENSG00000310209 , which was associated with poor PFS (HR = 1.141, P = 0.0025), increased IRF4 activity, Wnt pathway activation, CCL5 signaling, and the accumulation of anergic-like CD8+ T cells. These findings establish integrated coding-noncoding analysis as a strategic approach for discovering functional ncRNAs from transcriptomic sequencing data.

Abstract Multiple myeloma is a malignancy of clonally expanded plasma cells shaped by complex interactions with the immune microenvironment (IME). To investigate immune correlates of treatment response and disease progression, we conducted multi-omics profiling including CD138neg single-cell RNA sequencing of 243 bone marrow samples from 102 patients (631,226 cells) and CD138pos bulk RNA and whole-genome sequencing from 209 samples. In longitudinal analyses, interferon-γ signaling associated with markers of impaired T-cell memory after autologous stem cell transplant, whereas naïve B-cell abundance and immunoglobulin diversity correlated with improved progression-free survival (HR = 0.48; P = 2.3e−4). At disease progression, multiple myeloma cells upregulated cancer–testis antigens (CTAg) and immune effector genes, with concurrent B-cell depletion, enrichment of myeloid-derived suppressor cell expression, and phenotypic T-cell exhaustion. These findings highlight dynamic immune–tumor interactions, identifying naïve B-cell reconstitution as a biomarker of durable response and CTAgs as potential targets for high-risk disease at progression. Significance: Longitudinal profiling of multiple myeloma and the IME revealed dynamic immune–tumor interactions across the disease course. Altered expression in CD8+ T cells limited memory phenotype after transplant, whereas naïve B-cell recovery associated with sustained treatment response. At progression, CTAg expression associated with immunosuppression, revealing novel mechanisms of immune dysregulation.

Abstract Introduction: Multiple Myeloma (MM) is a complex hematologic malignancy, where patients often display one or more potentially high risk cytogenetic alterations associated with poor outcomes. Traditional high risk cytogenetics events in myeloma, such as NSD2 t(4;14) translocations, gain of 1q21, or deletion of 17p13, have often been studied in isolation, but emerging evidence suggests the combination of these high risk alterations has a greater negative prognostic impact than any on their own. This has been recently reflected in risk stratification guidelines from IMS and IMWG, which consider certain events, such as t(4;14), as high risk only in combination with gain of 1q21 or deletion of 1p32. Still, the mechanisms through which multi-hit high risk events disrupt the microenvironment and promote poor outcomes remains unclear. We hypothesize that myelomas with multiple high risk alterations remodel the immune environment to promote tumor progression and immune escape. Methods: To study the role of multi-hit high risk cytogenetics on the immune microenvironment, we analyzed CD138-bone marrow aspirate single-cell RNA sequencing (scRNAseq) data from 337 newly diagnosed MM patients from the MMRF CoMMpass study, generated as part of the Immune Atlas initiative. Cytogenetic alterations for these patients were derived from whole-genome and whole-exome sequencing of CD138+ bone marrow aspirates from the MMRF CoMMpass cohort. Patients were classified as multi-hit high-risk MM if they exhibited either (i) two high-risk cytogenetic events, including NSD2 t(4;14), MAF t(14;16), del(17p13), or (ii) one high-risk event with gain of 1q21. Results: Based on cytogenetic information, 33 patients in the Immune Atlas cohort were classified as 'multi-hit’ high-risk, while 34 patients had only a single high-risk alteration. These multi-hit high risk patents displayed significantly worse progression free survival compared to standard risk patients, adjusting for age, therapy, and ASCT (HR=2.34, p<7.2e-5), while single-hit patients showed a non-significant trend towards worse outcomes (HR=1.51, p=0.071). The most frequent multi-hit risk event in the cohort was NSD2 t(4;14) in combination with 1q21, observed in 23 patients. Compositional analysis of the immune populations in the scRNAseq data revealed that relative to both standard and single-hit high risk patients, multi-hit high risk patients displayed significant reductions in IFN-I stimulated CD4+ and CD8+ T cell populations, marked by decreased expression for antiviral response markers such as ISG15, XAF1, and IFI44L. Enrichment of inflammatory CD16+ non-classical monocytes was also observed. Further analysis of the most frequent multi-hit risk event, NSD2 with 1q21, revealed distinct enrichment of late-activated cytotoxic HLA+ CD8+T cells and cytotoxic CD4+.T cells. Neither alteration was observed in patients with single-hit NSD2 or 1q21. Further analysis on the interactions between high risk events revealed distinct transcriptomic profiles dependent on the high risk events involved, particularly in multi-hit events involving mutations or deletions of TP53 or gain of 1q21. Reduction in IFN-I signaling across various immune populations was primarily restricted to multi-hit risk events involving gain of 1q21. Conversely, patients with biallelic loss of TP53 displayed significant enrichment of these same IFN-I populations. Given this contrast in IFN-I signaling spanning multiple immune subtypes, we hypothesized that the malignant myeloma cells might similarly display altered IFN-I activity. Utilizing CD138+ myeloma bulk RNA sequencing data from CoMMpass, we found that IFN-I response scores strongly correlated between paired scRNA immune and bulk RNAseq tumor datasets (R2: 0.75, p=1.63e-32). Across 660 patients with bulk RNAseq and cytogenetic data, we confirmed significant reductions in IFN-I response scores in tumor cells in multi-hit high risk involving 1q21, and significant enrichment in those with complete loss of TP53 relative to standard-risk MM. Conclusions: Overall, we do observe that MM patients with multiple high risk cytogenetic alterations display distinct immunologic traits relative to standard risk or single-hit high risk patients in addition to significantly worse outcomes. Furthermore, we find variability in the immune alterations observed based on the cytogenetic events involved, further illustrating the heterogeneity in how MM shapes the immune microenvironment.

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.

Introduction: In recent years, multiple myeloma (MM) research has increasingly focused on unraveling the complex interactions between malignant plasma cells and their surrounding bone marrow microenvironment (BMME). To further elucidate these interactions, we developed a comprehensive single-cell atlas of the MM BMME, integrating both coding and noncoding (ncRNA) transcriptional profiles. By correlating these profiles with specific cytogenetic abnormalities in myeloma cells, we aim to uncover how ncRNAs regulate the phenotypic and functional states of myeloma cells and, consequently, shape the cellular landscape of the BMME. A detailed understanding of how the noncoding transcriptome affects the cellular components and immune landscape of the BMME is essential for advancing our knowledge of MM pathogenesis and identifying novel biomarkers and therapeutic targets. Methods: Our atlas was constructed using single-cell RNA sequencing data from 481 samples of CD138neg cells sorted from bone marrow aspirates of MM patients enrolled in the MMRF CoMMpass study. This dataset includes accompanying whole-genome sequencing and survival data, enabling correlative analysis between transcriptional profiles, cytogenetic abnormalities, and patient outcomes. To generate a combined coding and non-coding transcriptome, we developed an expanded human reference genome by systematically merging mRNA and ncRNA transcripts from the LncBook2.0 and GENECODEv42 reference genomes. The sequencing data was aligned to this expanded genome, followed by quality control processing, batch correction, clustering, and supervised analysis. Results: The resulting coding and non-coding atlas comprises over 1.9 million cells, spanning immune, plasma, and stromal compartments. Remarkably, ncRNAs constituted 46% of the associated genes, including 22,102 long ncRNAs (lncRNAs) and 3,112 small ncRNAs. Subclustering analysis of the major immune compartments (B lymphoid, myeloid, and NK and T lymphoid) yielded 70 subclusters, with ncRNAs representing 24-38% of the top 100 differentially expressed genes within each compartment. This underscores the significant role of ncRNAs in distinguishing immune subpopulations. Moreover, examining the association between specific cytogenetic abnormalities and the immune composition of the BMME, 30 subclusters were found to be differentially abundant (P < 0.05) between cytogenetic abnormalities, supporting our hypothesis that myeloma cell genotypes significantly shape the immune microenvironment. For instance, patients with CCND1 amplification displayed an increase CD4+ central memory T cells with a decrease in CD8+ cytotoxic T cells. Similarly, patients with 1q21 gain exhibited an increase in TGFβ-stimulated monocytes, while a decrease in cytotoxic CD8+ T and CD56dim NK cells was observed in patients with 17p13 deletion. Next, examining which ncRNAs are associated with specific cytogenetic abnormalities, we identified 14 ncRNAs significantly differentially expressed across cytogenetic abnormalities. Increased expression of six of these ncRNAs were associated with poor overall survival both independently and in combination (P < 0.05, HR = 3.7). Notably, three of these ncRNAs have documented roles in cancer progression but have not been previously studied in the context of MM. Subsequently stratifying patients based on their enrichment of these outcome-associated ncRNAs revealed even stronger associations with immune composition, including an increase in CD4+ regulatory T cells (P < 0.05). This further supports our hypothesis that myeloma cell genotypes shape the BMME. Lastly, by constructing a gene regulatory network to predict the interactions between coding and noncoding RNAs, we illustrate the regulatory networks of ncRNAs modulating the phenotypes of myeloma and immune cell subpopulations. Conclusion: In summary, we present the first high-resolution transcriptomic atlas of the MM BMME, integrating both coding and noncoding RNAs. This study reveals distinct immune subpopulations associated with specific myeloma cell genotypes and highlights the central role of ncRNAs in modulating the phenotypic and functional states of both malignant and non-malignant cells in the MM BMME. Our findings emphasize the potential of ncRNAs as therapeutic targets and prognostic markers for MM, offering new avenues for research and clinical intervention.