The 3D genome of plasma cells in multiple myeloma

Abstract

Multiple myeloma (MM) is a hematological malignancy characterized by expanding clonal plasma cells in the bone marrow (BM) that produce monoclonal immunoglobulin. It is an incurable disease, accounting for about 10% of blood malignancies and the second most common hematologic malignancy. Therefore, in-depth research into the molecular mechanisms and therapeutic targets of the disease is crucial. For the first time, we performed high-throughput chromosome conformation capture (Hi-C) analysis of plasma cells in five multiple myeloma patients, and integrated it with genome resequencing and transcriptomic associated with genomic variation and gene expression. As a result, 19 specific TAD (Topologically Associating Domain) boundaries in MM samples related to the immune response and Wnt signaling pathways were identified. Additionally, Loop structures were also analyzed, revealing that promoter-enhancer-associated loops were the most prevalent. Genomic characteristics of MM patients were explored, identifying SNPs, InDels, and CNVs, with variations in the CDS region potentially affecting gene function. Transcriptome analysis showed differentially expressed genes in MM patients, mainly involved in p53 signaling and cell adhesion. Multi-omics analysis identified overlapping genes related to MM, including those involved in MHC class II protein complex assembly and antigen presentation. The study provides insights into the complex genomic and transcriptomic changes in MM plasma cells, potentially aiding in identifying therapeutic targets.

Keywords: 3D genome; Genome resequencing; Multiple myeloma; Plasma cell; Transcriptome.

Fig. 1

Overview of 3D organization in MM plasma cells. (A) Genome-wide contact maps of MMC1 patients. (B) P(s) curves (at 100 kb resolution) averaged across all autosomes in the genome of each sample. (C) Compartment state of chromosome 1 indicated by PC1 values of MMC1 patients. Red represents A compartment and cyan represents B compartment. (D) Compared with Control, the MM patients showed a few compartment changes in common. (E) The most enriched terms for genes with A to B or B to A switching. F. Enrichment analysis of genes with A-to-B switching event.

Fig. 2

TAD and loop characteristics. (A) Number of TADs in each sample. (B) Boxplots showing TAD sizes in each sample. (C,D) GO enrichment biological process (BP) (C) and KEGG (D) analysis of genes with TAD boundary of difference. (E) Hi–C contact matrix and TADs on Chr 1: 1–10 Mb in control and MMC1 patient.

Fig. 3

Loop characteristics in MM. (A) The identified Loop is classified into three types. E-E, E-P, and P-P are the number of enhancer-enhancer interaction, enhancer-promoter interaction, and promoter-promoter interaction loops, respectively. Loop classification according to the number of enhancers (B) and promoters (C) of each loop contained. (D) Distribution of chromatin loop in each chromosome in control (red) and MM (green) groups. GO enrichment biological process (BP) (E) and KEGG (F) analysis of genes with loops of difference.

Fig. 4

Genomic variations of MM. (A) Distribution of variations on the genome. From outside to inside were chromosome position, gene density, SNP density and InDel density respectively. (B) Distribution of SNPs of each type based on all samples. (C) Veen diagram showing number of genes with variations (including Non-synonymous SNP, InDel and SV) shared among the five MM patients. KEGG (D) and Reactome (E) enrichment analysis of the shared genes with variations in the CDS region.

Fig. 5

Analysis on DEGs. (A) FPKM density distribution of each sample. (B) Correlation heatmap between samples. (C) MA plot of differentially expressed genes between MM patients and Control. (D) Hierarchical clustering of differentially expressed genes. (E) Bubble chart of KEGG pathway enrichment on DEGs. Top 20 enriched pathways (with smallest Q-value) were shown.

Fig. 6

Multi-omics analysis. (A) Venn diagram showing the overlapped genes for differentiated compartment change, TADs and loops. (B) Venn diagram showing overlap between genes with CDS variation and DEGs. (C) Enrichment analysis on overlapping genes between genes with CDS variation and DEGs. (D) FPKM of ARHGAP24, ALDH1A2, CALCRL, and NSG2 genes in four MM patients and Control.