Abstract 4406: Single cell multiomic analysis reveals how genomic, epigenomic and transcriptomic events drive progression of multiple myeloma precursor states

Abstract In this study we have leveraged Moffitt Cancer Center’s cohort of over 1, 000 bone marrow (BMBX) aspirates from normal donors, MM precursor diseases (MGUS, SMOL), active therapy naïve disease (NDMM), as well as early (post 1-3 lines of therapy, ERMM) and late-relapse (3+ lines of therapy, LRMM) MM patients, characterized clinically, cytogenetically (FISH), genetically (WES), and transcriptomically (RNA-seq). Transcriptomic analysis identified a subset of cancer hallmarks differentially expressed between MGUS and NDMM samples (e. g. cell identity, adhesion and inflammatory signaling, etc. ). Dimensionality reduction analysis, followed by unsupervised segmentation, identified clusters of co-expressing genes across this dataset. Enrichment analysis of aforementioned gene clusters, differentially expressed between MGUS and NDMM states, identified a number of putative transcription factors (GATA1/2, SUZ12, RUNX1, SOX2, TP63, NFE2L2, FOXM1 and NANOG), as well as polycomb complex and H3K27me3 as main drivers. Single cell ATAC-seq in 11 BMBX (4 SMOL, 4 NDMM, 1 ERMM, 2 LRMM) and single cell multiomics (simultaneous scATAC-seq/scRNA-seq) in additional 10 BMBX (2 healthy, 3 MGUS, 3 SMOL and 2 NDMM) confirmed that the H3K27me3 putatively regulated gene clusters were the only ones with significant chromatin accessibility changes. Single cell analysis confirmed differential expression and accessibility of cancer hallmarks identified in larger cohort, as well as putative driver TFs. Correlation between TF expression and motif accessibility produced an additional list of pioneer TFs putatively involved in progression from MM precursor states (ZEB1, EBF1, SPI1, PAX5, etc. ). Investigation of scMultiomic data demonstrated that NDMM and SMOL samples contain subpopulations of cells in MGUS and normal “states” (cell clusters in scMultiomics UMAP), confirming intra-sample heterogeneity, and that divergence within the multiomic plane occurs in the transition between MGUS and SMOL. Through pseudotime and single cell copy number analysis (epiAneufinder/scATAC-seq and inferCNV/scRNA-seq) we were able to reconstruct how MM FISH cytogenetic abnormalities alter the multiome of these cells, creating aforementioned intra-sample heterogeneity. Despite different initiating events, all samples shared a common biology putatively regulated by epigenetic dysregulation, suggesting polycomb complex hijacking as a therapeutic opportunity for precursor MM. Citation Format: Rafael Canevarolo, Praneeth Sudalagunta, Maria Silva, Mark Meads, Rachid Baz, Melissa Alsina, Kenneth H. Shain, Ariosto Siqueira Silva. Single cell multiomic analysis reveals how genomic, epigenomic and transcriptomic events drive progression of multiple myeloma precursor states abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 4406.