Dasari, Surendra

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.

Abstract The loss of skeletal muscle mass during aging is a significant health concern linked to adverse outcomes in older individuals. Understanding the molecular basis of age‐related muscle loss is crucial for developing strategies to combat this debilitating condition. Long noncoding RNAs (lncRNAs) are a largely uncharacterized class of biomolecules that have been implicated in cellular homeostasis and dysfunction across a many tissues and cell types. To identify lncRNAs that might contribute to skeletal muscle aging, we screened for lncRNAs whose expression was altered in vastus lateralis muscle from older compared to young adults. We identified FRAIL1 as an aging‐induced lncRNA with high abundance in human skeletal muscle. In healthy young and older adults, skeletal muscle FRAIL1 was increased with age in conjunction with lower muscle function. Forced expression of FRAIL1 in mouse tibialis anterior muscle elicits a dose‐dependent reduction in skeletal muscle fiber size that is independent of changes in muscle fiber type. Furthermore, this reduction in muscle size is dependent on an intact region of FRAIL1 that is highly conserved across non‐human primates. Unbiased transcriptional and proteomic profiling of the effects of FRAIL1 expression in mouse skeletal muscle revealed widespread changes in mRNA and protein abundance that recapitulate age‐related changes in pathways and processes that are known to be altered in aging skeletal muscle. Taken together, these findings shed light on the intricate molecular mechanisms underlying skeletal muscle aging and implicate FRAIL1 in age‐related skeletal muscle phenotypes.

Introduction: Recently, we demonstrated transcriptional down-regulation of hypertrophy pathways in myectomy tissue derived from patients with obstructive hypertrophic cardiomyopathy (HCM) despite translational activation of associated hypertrophy pathways. Previous studies of other forms of cardiac hypertrophy demonstrate hypertrophy pathways are activated via histone acetylation and histone deacetylase (HDAC) inhibitors prevented development of hypertrophy. Whether histone modifications regulate hypertrophy pathways in HCM remains unexplored. Methods: Chromatin immunoprecipitation sequencing (ChIP-seq) was performed on myectomy tissues from 40 patients with HCM and 23 controls to characterize differential histone marks for H3K4me3 (active promoter), H3K9ac (active promoter), H3K9me3 (heterochromatin), H3K27ac (active enhancer), H3K27me3 (repression) across the genome. The differential histone marks were integrated with RNA-sequencing (RNA-seq) data derived from the same patients. Results: Overall, we identified 2,912 (7%) differential H3K4me3 peaks impacting 5 pathways, 23,339 (21%) differential H3K9ac peaks impacting 87 pathways, 33 (0.05%) differential H3K9me3 peaks, and 58,837 (42%) differential H3K27ac peaks impacting 50 pathways. There was increased H3K27ac (q-value = 0.002) and H3K9ac (q-value = 0.009) at RAS-MAPK loci. Univariate analysis of concordance between H3K9ac with RNA-seq data showed activation of cardiac hypertrophy signaling (z-score=4.5; -log [BH p-value] = 3.1), while H3K27me showed down-regulation of cardiac hypertrophy signaling (z-score=-2.4; -log [BH p-value] = 2.4). Multivariate integration of the ChIP-seq data with RNA-seq data identified 3,189 transcripts concordant with all five histone marks impacting 254 pathways, 18 (7%) of which are involved in cardiac hypertrophy. Conclusions: Myectomy tissue from patients with obstructive HCM shows enrichment of histone modifications at cardiac hypertrophy loci with activation via H3K27 and H3K9 acetylation and repression via H3K27 methylation. Further studies are needed to understand the balance and temporal relationship between these competing regulators in HCM pathobiology and the potential for epigenetic therapies.