Identification of disease-related aberrantly spliced transcripts in myeloma and strategies to target these alterations by RNA-based therapeutics.
Daisuke OgiyaZuzana ChyraSigitas J VerselisMorgan O'KeefeJacquelyn CobbIvane AbiatariSrikanth TalluriAnjana Anilkumar SitharaTeru HideshimaMichael P ChuRoman HájekDavid M DorfmanLinda M PilarskiKenneth C AndersonSophia AdamiaPublished in: Blood cancer journal (2023)
Novel drug discoveries have shifted the treatment paradigms of most hematological malignancies, including multiple myeloma (MM). However, this plasma cell malignancy remains incurable, and novel therapies are therefore urgently needed. Whole-genome transcriptome analyses in a large cohort of MM patients demonstrated that alterations in pre-mRNA splicing (AS) are frequent in MM. This manuscript describes approaches to identify disease-specific alterations in MM and proposes RNA-based therapeutic strategies to eradicate such alterations. As a "proof of concept", we examined the causes of aberrant HMMR (Hyaluronan-mediated motility receptor) splicing in MM. We identified clusters of single nucleotide variations (SNVs) in the HMMR transcript where the altered splicing took place. Using bioinformatics tools, we predicted SNVs and splicing factors that potentially contribute to aberrant HMMR splicing. Based on bioinformatic analyses and validation studies, we provided the rationale for RNA-based therapeutic strategies to selectively inhibit altered HMMR splicing in MM. Since splicing is a hallmark of many cancers, strategies described herein for target identification and the design of RNA-based therapeutics that inhibit gene splicing can be applied not only to other genes in MM but also more broadly to other hematological malignancies and solid tumors as well.
Keyphrases
- multiple myeloma
- genome wide
- single cell
- newly diagnosed
- end stage renal disease
- rna seq
- ejection fraction
- gene expression
- escherichia coli
- stem cells
- clinical trial
- prognostic factors
- bone marrow
- peritoneal dialysis
- transcription factor
- combination therapy
- drug induced
- genome wide identification
- patient reported
- case control