MDS-associated SF3B1 mutations enhance proinflammatory gene expression in patient blast cells

Abstract

Two factors known to contribute to the development of myelodysplastic syndrome (MDS) and other blood cancers are (i) somatically acquired mutations in components of the spliceosome and (ii) increased inflammation. Spliceosome genes, including SF3B1, are mutated at high frequency in MDS and other blood cancers; these mutations are thought to be neomorphic or gain-of-function mutations that drive disease pathogenesis. Likewise, increased inflammation is thought to contribute to MDS pathogenesis; inflammatory cytokines are strongly elevated in these patients, with higher levels correlating with worsened patient outcome. In the current study, we used RNAseq to analyze pre-mRNA splicing and gene expression changes present in blast cells isolated from MDS patients with or without SF3B1 mutations. We determined that SF3B1 mutations lead to enhanced proinflammatory gene expression in these cells. Thus, these studies suggest that SF3B1 mutations could contribute to MDS pathogenesis by enhancing the proinflammatory milieu in these patients.

Keywords: RNAseq; inflammation; pre-mRNA splicing; spliceosome.

Fig. 1.. The SF3B1-K700E mutation alters gene expression and pre-mRNA splicing in blast cells from MDS patients.

Panels A and B depict unsupervised hierarchical clustering of genes based on differential gene expression using HISAT2 mapping (A) or altered pre-mRNA splicing using DRIM-sq (B). WT 1–3 indicates three MDS patients without mutations in SF3B1, U2AF1, or SRSF2; K700E 4–7 indicates four MDS patients with SF3B1-K700E mutations. The schematics on the left in panel C depict different types of alternative pre-mRNA splicing, including exon skipping (ES), intron retention (IR), alternate 5’ splice site usage (A5SS), alternate 3’ splice site usage (A3SS), and mutually exclusive exons (MXE). The black lines indicate the canonical splicing event; the green lines indicate the alternative event. The pie charts depict the relative frequency of each type of alternative pre-mRNA splicing event identified using DRIM-seq (n=344 events total) or rMATS (14,397 events total). DRIM-seq does not report the mutually exclusive exon usage (MXE) class; rMATS does report this class of events.

Fig. 2.. SF3B1 mutations alter splicing of different genes in patient blast cells and CD34⁺ stem cells.

In panel A, the Venn diagram depicts the number of alternative pre-mRNA splicing events induced by SF3B1 mutations in either patient blast cells (the current study), CD34+ cells in study #1 [20], or CD34+ cells in study #2 [21]. In all studies, the analyses compared cells with SF3B1 mutations to those without any spliceosome mutation using DRIM-seq. In panel B, the Venn diagram depicts the number of genes with altered isoform usage induced by SF3B1 mutations in these same three groups.

Fig. 3.. Identification of intron features that are altered in genes that undergo SF3B1-K700E-induced alternative pre-mRNA splicing.

Panels (A) and (B) depict sequence logo plots for genes with altered 3’ splice site usage (A) or exon skipping (B) induced by the SF3B1-K700E mutation compared to control introns in genes whose splicing is not affected by SF3B1 mutation (comparisons using DRIM-seq). Panel (C) depicts the predicted strength of the branch point in genes that undergo SF3B1-K700E alternate 3’ splice site usage compared to genes that are not affected by SF3B1 mutation. Branch point strength was calculated as outlined in [28]. A higher score indicates a stronger predicted branch point.

Fig. 4.. The SF3B1-K700E mutation increases production of the pro-inflammatory mediator protein S100A8.

(A) depicts gene expression data from the RNAseq analysis (transcripts per million, TPM) for S100A8 in patient blast cells. The figure also depicts the results of flow cytometry analysis to monitor S100A8 protein levels in either patient blast cells (B) or in the CD34⁺ sub-population (C). These plots display S100A8 levels as gMFI. WT = samples from patients without a spliceosome gene mutation. K700E = samples from patients with a SF3B1-K700E mutation. (D,E) S100A8 was monitored at the mRNA level by qPCR or at the protein level by ELISA in K562 cells expressing either WT SF3B1 or SF3B1-K700E. The qPCR results were normalized relative to βactin with expression in WT cells defined as 1. Data represent mean, SEM.

Fig. 5.. SF3B1-K700E mutations increase expression of pro-inflammatory genes in K562 cells.

Expression of the indicated genes was monitored by qPCR in K562 cells either carrying a SF3B1-K700E mutation (K700E) or wild type for SF3B1 (WT). All data were normalized so that expression in WT cells was defined as 1. qPCR data were analyzed relative to βactin. As a control, the data also were compared to a second control housekeeping gene, Gapdh (panel G). Data represent mean, SEM.