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

Alterations in mRNA 3-prime 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 in vivo was not thoroughly addressed. In this study we analyzed a large RNA-seq data set of glioblastoma (GBM) patient 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 32 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 SC5D gene and an HNRNPU-regulated event in the PRRC2B 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. The transcriptome analysis workflow that we present here enables the identification of concordant RBP-APA associations in cancers.

mRNA 3'端加工与多聚腺苷酸化的改变广泛参与多种癌症的生物学进程，其中包括胶质母细胞瘤（glioblastoma, GBM）——一类极具侵袭性的肿瘤亚型。尽管已有多项细胞系功能研究鉴定出若干参与可变多聚腺苷酸化（alternative polyadenylation, APA）的RNA结合蛋白（RNA-binding protein, RBP），但此类蛋白在体内肿瘤的APA调控图谱中的具体贡献尚未得到充分阐释。本研究针对来自癌症基因组图谱（The Cancer Genome Atlas, TCGA）的大型胶质母细胞瘤患者RNA测序（RNA-seq）数据集展开分析，旨在筛选可区分胶质母细胞瘤主要分子亚型的APA模式；随后，我们将上述APA模式与RBP结合足迹数据，以及ENCODE联盟（ENCODE Consortium）针对大规模敲降单个RBP后所检测到的APA事件进行整合分析。本次分析共鉴定出32组高度一致且具有统计学显著性的RBP-APA关联关系，即TCGA与ENCODE数据集均显示，RBP表达水平的变化伴随对应APA事件的改变。其中，我们发现了此前未被报道的PTBP1调控SC5D基因APA事件，以及HNRNPU调控PRRC2B基因的APA事件；巴塞尔大学附属医院获取的配对肿瘤中心-外周胶质母细胞瘤样本的RNA测序数据，进一步验证了这两类APA事件。本研究构建的转录组分析流程，可用于在癌症中筛选具有一致性的RBP-APA关联关系。