Mironov Aleksei, Franchitti Lorenzo, Ghosh Shreemoyee, Ritz Marie-Francoise, Hutter Gregor, De Bortoli Michele, Zavolan Mihaela
Biozentrum, University of Basel, Basel, Switzerland.
Department of Clinical and Biological Sciences, University of Turin, Turin, Italy.
Front Mol Biosci. 2024 Aug 12;11:1363933. doi: 10.3389/fmolb.2024.1363933. eCollection 2024.
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 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.
mRNA 3' 端加工和多聚腺苷酸化的改变在包括胶质母细胞瘤(GBM)在内的多种癌症类型的生物学过程中广泛存在,GBM是最具侵袭性的肿瘤类型之一。尽管通过细胞系功能研究鉴定出了几种负责可变多聚腺苷酸化(APA)的RNA结合蛋白(RBP),但它们对肿瘤中APA格局的贡献尚未得到充分研究。在本研究中,我们分析了来自癌症基因组图谱(TCGA)的胶质母细胞瘤(GBM)样本的大型RNA测序数据集,以识别区分GBM主要分子亚型的APA模式。我们将这些模式与RBP足迹数据以及ENCODE联盟测试的大量样本中单个RBP缺失时发生的APA事件进行叠加。我们的分析揭示了22个高度一致且具有统计学意义的RBP-APA关联,其中RBP表达的变化在TCGA和ENCODE数据集中均伴随着APA。在这些关联中,我们在PRRC2B基因中发现了一个先前未知的由PTBP1调节的APA事件,以及在SC5D基因中发现了一个由HNRNPU调节的事件。巴塞尔大学医院获得的配对肿瘤中心-边缘GBM样本的RNA测序数据进一步支持了这两个事件。此外,我们在两个胶质母细胞瘤细胞系中进行了RNA测序的siRNA敲低和过表达实验,验证了PTBP1对PRRC2B中APA的调节作用。我们在此展示的转录组分析工作流程能够识别癌症中一致的RBP-APA关联。