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Alternative splicing in multiple myeloma
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Figure 4. MZB1, an important prognostic gene in multiple myeloma, was significantly alternative spliced in SF3B1-mutated patient samples. (A) Screenshot from JunctionSeq identifying two significant novel splice junction usage in addition to a known splice junction and three differentially used exons in the SF3B1 mutants. (B) Sashimi plot showing differential exon and splice junction usage between a SF3B1 mutated and control sample. (Note that all SF3B1 mutated samples displayed the same differential splicing pattern.) (C) Box plots of MZB1 transcript expression levels. Two transcripts showed a significant switch in level of expression between the two groups.
the differentially expressed transcripts, 79 corresponded with a change at the gene level (22%). The differentially expressed genes at both the gene and transcript level included the protein coding genes EREG, IL1B, and MINA, which were found to be upregulated in the SF3B1 mutants and have been associated with cell proliferation.27-29 Other transcripts that were significantly differentially upregulat- ed included a number of RNA splicing and spliceosome genes including DHX9, CLASRP, SNRPE, BCAS2, and EIF4A3.30-32 These genes have significant changes at the transcript level only and indicate a change in isoform ratio without an effect on the overall gene expression level (Online Supplementary Tables S8 and S10).
Gene set enrichment analysis of differentially spliced genes
To identify the impact of mutated SF3B1 at a pathway level we carried out GSEA on the total set of differential gene expression results. The Hallmark pathways33 with significant (false discovery rate [FDR] <0.05) normalized enrichment scores (NES) between the two sample groups were identified (Figure 5A). This analysis showed decreased gene enrichment for protein secretion (P=0.01, NES= -1.93) and unfolded protein response (UPR) (P=0.01, NES=1.83) pathways. Conversely GSEA identified enrich-
ment for TNFA signaling via NF-κB (P=0.01, NES=1.98), KRAS signaling (P=0.008, NES=1.69), and I2/STAT5 sig- naling (P=0.01, NES=0.65) pathways in SF3B1 mutant samples.
Significantly alternatively spliced genes are themselves involved in alternative splicing
We identified protein-protein interactions (PPI) using the list of significantly alternatively (JunctionSeq & DEXSeq) spliced genes as input (n=618) and only selected high confidence interactions (minimum interaction score of 0.700). The resulting PPI network (Figure 5B) identified a large cluster of differentially spliced genes associated with mRNA processing and splicing pathways. Genes identified in the mRNA processing pathway included SRRM2, SUGP1, and PPIE. Other pathways in the differ- entially spliced gene clusters included RNA decay and pro- tein ubiquitination.
Identifying the full extent of splice variation as a potential driver mechanism in multiple myeloma
To determine the extent of alternative splicing in MM, irrespective of mutations in SF3B1, we split the dataset (n=598) into three groups. The groups consisted of the top and bottom 20% (both n=120) and middle 60% (n=358) in
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