Dataset Information

Identification of disease-related aberrantly spliced transcripts in myeloma and strategies to target these alterations by RNA-based therapeutics.

ABSTRACT: 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.

SUBMITTER: Ogiya D

PROVIDER: S-EPMC9898564 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of disease-related aberrantly spliced transcripts in myeloma and strategies to target these alterations by RNA-based therapeutics.

Ogiya Daisuke D Chyra Zuzana Z Verselis Sigitas J SJ O'Keefe Morgan M Cobb Jacquelyn J Abiatari Ivane I Talluri Srikanth S Sithara Anjana Anilkumar AA Hideshima Teru T Chu Michael P MP Hájek Roman R Dorfman David M DM Pilarski Linda M LM Anderson Kenneth C KC Adamia Sophia S

Blood cancer journal 20230203 1

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 ...[more]

PMID: 36737429

Similar Datasets

Project description:Mutations in TDP-43 (an RNA binding protein) are known to cause amyotrophic lateral sclerosis (ALS). Previously, our group and several other studies showed that TDP-43 binds to several RNA targets in the mammalian CNS. ALS causing mutations in the C-terminal region of TDP-43 that is involved in splicing regulation may lead to aberrant splicing of several RNA transcripts. The main aim of this study is to identify the effect of an ALS causing mutation on the splicing regulation of previously known targets of TDP-43. Mice overexpressing a mutant human TDP-43 (hTDP-43) gene were obtained from The Jackson Laboratory (strain name - B6;CB-Tg(Prnp-TARDBP*A315T) 95Balo/J; Stock no:010700). Mutant hTDP43 was expressed under the control of a prion protein promoter that drives the expression mainly in the mouse CNS and the male transgenic mice developed symptoms around 12 weeks of age while the female mice develop symptoms approximately 20 weeks of age. Therefore, Tg animals that are 50 days old were considered pre-symptomatic and 100 days old (Tg) animals were considered to be in the post-symptomatic stages of the disease for exon array experiments. Age and sex matched pre and post-symptomatic transgenic animals and their wild type littermates were euthanised by cervical dislocation and tissues (brain and spinal cord) were harvested immediately for total RNA isolation experiments (n=3 per group). 200 ng of total RNA from transgenic TDP-43 mice and wild type animals was converted to cDNA and then amplified using the Applause WT-Amp Plus ST kit (NuGEN). Amplified cDNA was then fragmented and biotin labeled using the Encore Biotin Module kit (NuGEN) according to the manufacturer's instruction manual. Labelled cDNA was then hybridised onto Affymetrix GeneChip Exon 1.0 ST arrays in a hybridisation oven at 45 degrees C for 20 hours at 60rpm. After hybridization, washing and staining of the arrays were carried out using Affymetrix fluidics station 450 followed by scanning using GeneChip scanner. GeneChip Command Console Software (AGCC) controlled both the fluidics station and the scanner. CEL files generated by AGCC were uploaded onto Partek software and the data analysis was carried out using the exon array analysis workflow. Exon 1.0 ST arrays contain many more probes, which are classified into three major types based on their source. They are Core, extended and full probe set annotation. Core annotation refers the probe sets that are the most reliable of the three and is derived based on evidences from Refseq and GenBank. Extended annotations refer to probe sets that are generated based on EST sequences, ENSEMBL gene collections and other databases including those used for generating core probe sets. The full annotation refers to probe sets that are purely based on computational predictions. Core probe set annotation, unlike the extended or full annotation excludes the speculative probes reducing the incidence of false positives and was employed for exon array analysis. Alt-splice Anova, a statistical tool available in Partek was used for identifying novel alternative splicing events.

Dataset Information

Identification of disease-related aberrantly spliced transcripts in myeloma and strategies to target these alterations by RNA-based therapeutics.

Publications

Identification of disease-related aberrantly spliced transcripts in myeloma and strategies to target these alterations by RNA-based therapeutics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets