Leveraging multi-omics data to infer regulators of mRNA 3’ end processing in glioblastoma

Alterations in mRNA 3' end processing and polyadenylation are widely implicated in the biology of many cancer types, including glioblastoma (GBM), one the most aggressive tumor types. Although several RNA-binding proteins (RBPs) responsible for alternative polyadenylation (APA) were identified from functional studies in cell lines, their contribution to the APA landscape in tumors <i>in vivo</i> was not thoroughly addressed. In this study we analyzed a large RNA-seq data set of glioblastoma (GBM) samples from The Cancer Genome Atlas (TCGA) to identify APA patterns differentiating the main molecular subtypes of GBM. We superimposed these to RBP footprinting data and to APA events occurring upon depletion of individual RBPs from a large panel tested by the ENCODE Consortium. Our analysis revealed 22 highly concordant and statistically significant RBP-APA associations, whereby changes in RBP expression were accompanied by APA in both TCGA and ENCODE datasets. Among these, we found a previously unknown PTBP1-regulated APA event in the PRRC2B gene and an HNRNPU-regulated event in the SC5D gene. Both of these were further supported by RNA-sequencing data of paired tumor center-periphery GBM samples obtained at the University Hospital of Basel. In addition, we validated the regulation of APA in PRRC2B by PTBP1 in siRNA-knockdown and overexpression experiments followed by RNA-sequencing in two glioblastoma cell lines. The transcriptome analysis workflow that we present here enables the identification of concordant RBP-APA associations in cancers.

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Publication Details

Journal
Frontiers in Molecular Biosciences
Published
2024-08-12
DOI
https://doi.org/10.3389/fmolb.2024.1363933
Citations
2
Primary Topic
RNA Research and Splicing
Type
article
Field-Weighted Citation Impact
0.47
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article

Leveraging multi-omics data to infer regulators of mRNA 3’ end processing in glioblastoma

Marie‐Françoise Ritz, Michele De Bortoli, Mihaela Zavolan, Gregor Hütter et al.
2 citations
Frontiers in Molecular Biosciences
RNA Research and Splicing
0.47
article

Leveraging multi-omics data to infer regulators of mRNA 3’ end processing in glioblastoma

Marie‐Françoise Ritz, Michele De Bortoli, Mihaela Zavolan, Gregor Hütter, Lorenzo Franchitti, Shreemoyee Ghosh, Aleksei Mironov
article en
2 citations

Abstract

Alterations in mRNA 3' end processing and polyadenylation are widely implicated in the biology of many cancer types, including glioblastoma (GBM), one the most aggressive tumor types. Although several RNA-binding proteins (RBPs) responsible for alternative polyadenylation (APA) were identified from functional studies in cell lines, their contribution to the APA landscape in tumors <i>in vivo</i> was not thoroughly addressed. In this study we analyzed a large RNA-seq data set of glioblastoma (GBM) samples from The Cancer Genome Atlas (TCGA) to identify APA patterns differentiating the main molecular subtypes of GBM. We superimposed these to RBP footprinting data and to APA events occurring upon depletion of individual RBPs from a large panel tested by the ENCODE Consortium. Our analysis revealed 22 highly concordant and statistically significant RBP-APA associations, whereby changes in RBP expression were accompanied by APA in both TCGA and ENCODE datasets. Among these, we found a previously unknown PTBP1-regulated APA event in the PRRC2B gene and an HNRNPU-regulated event in the SC5D gene. Both of these were further supported by RNA-sequencing data of paired tumor center-periphery GBM samples obtained at the University Hospital of Basel. In addition, we validated the regulation of APA in PRRC2B by PTBP1 in siRNA-knockdown and overexpression experiments followed by RNA-sequencing in two glioblastoma cell lines. The transcriptome analysis workflow that we present here enables the identification of concordant RBP-APA associations in cancers.

Frontiers in Molecular BiosciencesVol. 11
University of Basel (CH), University of Turin (IT)
Good health and well-being
Openalex Percentile: Top 36%
RNA Research and Splicing
0.47
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