Alternative Splicing Is a Frequent Event and Impacts Clinical Outcome in Myeloma: A Large RNA-Seq Data Analysis of Newly-Diagnosed Myeloma Patients

Alternative splicing is an important post-translational change that alters gene function. Misregulation of alternative splicing has been implicated in number of disease processes including cancer. Here we have analyzed alternative splicing in myeloma using high throughput RNA-seq. Our analytic pipeline for RNA-seq data used in this investigation not only provides information on expression levels for genes, but also provides information on the expression of known splice variants of genes (isoforms), and can identify novel exon level events across individuals (i.e. exon skipping events).

We conducted a study of 328 newly-diagnosed patients with multiple myeloma treated homogeneously with novel agent combination containting lenalidomide, bortezomib and dexamethsone with or without high-dose melphalan followed by lenalidomide maintenance in the IFM/DFCI study. RNA isolated from purified CD138+ MM cells collected at the time of diagnosis and from 18 normal donor plasma cells were processed by RNA-seq (100 million paired end reads on Illumina HiSeq) and analyzed using a custom computational and statistical pipeline. Following read alignment to hg19, we utilized RSEM to quantify both gene-level and isoform-level expression of known ENSEMBL transcripts. We then implemented a novel testing approach based on compositional regression to discover genes that show significant isoform switching between the 328 MM samples and 18 Normal Plasma Cell (NPC) samples from healthy donors. Using various programs and their modifications, we also identified novel alternative splicing events, such as exon skipping and mutually exclusive exon usage, among others. Patient data for MM characteristics, cytogenetic and FISH as well as clinical survival outcomes were also analyzed and correlated with genomic data.

We observed over 600 genes showing significant changes in relative isoform abundances (isoform switching) between MM and normal samples. A number of previously characterized genes including MYCL1 (adj. p = 0.0014) and CCND3 (adj. p = 0.0013), and MAP kinase-related genes (MAP3K8, MAPKAPK2, MAPKAPK3, MAP4K4) exhibited significant isoform switching compared to normal, in addition to some not well characterized genes. Genes showing the greatest magnitude of isoform switching include MEFV (adj. p = 2.7 x 10^-5), showing a two fold change in the relative major isoform abundance compared to normal, and has been previously shown to have a role in lymphoid neoplasms. We applied hierarchical clustering to the isoforms showing significant changes in isoform-switching and identified 4 distinct clusters, which are currently being investigated for correlation with clinical subtypes of MM. Exon level analyses of alternative splicing events, such as exon skipping, are currently underway.

Clinical data including MM characteristics, cytogenetics, FISH and survival outcomes was available for a subset of 265 patients. We found that 109 genes showed significant isoform switching between t(4;14) and non-t(4;14) patients, such as CD44 (adj. p =1.8 x 10^-6) and WHSC1 (adj. p =5.1 x 10^-28). Comparing del17p (28 in total) and non del17p patients, we found no significant splicing changes after multiple testing adjustment. Of these genes, only a subset (40%) were shown to be differentially expressed in terms of total gene expression, suggesting the importance of examining alternative splicing events in addition to total gene expression.

With respect to treatment response, we compared the expression of gene isoforms between patients achieving complete response (CR) versus others and identified 38 isoforms associated with response to treatment (adj. p value < 0.05), with SEPT9, SLC2A5, and UBX6 having the strongest associations (adj. p-value < 3 x 10^-4). Using a univariate cox regression model, 4 spliced isoforms relating to 3 genes were identified as having significant correlation with event-free survival (EFS) (FDR-adjusted cox p value < 0.05). We are in the process of now integrating the gene expression data with altered splicing data to develop an integrated survival model.

In summary, this study highlights the significant frequency, biological and clinical importance of alternative splicing in MM and points to the need for evaluation of not only the expression level of genes but also post-translational modifications. The genes identified here are important targets for therapy as well as possible immune modulation.