mRNA 3' 末端加工和聚腺苷酸化的改变广泛涉及许多癌症类型的生物学，包括胶质母细胞瘤 (GBM)，这是最具侵袭性的肿瘤类型之一。尽管从细胞系的功能研究中鉴定出了几种负责替代多腺苷酸化 (APA) 的 RNA 结合蛋白 (RBP)，但它们对体内肿瘤 APA 景观的贡献尚未得到彻底解决。在这项研究中，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-seq 数据集，以确定区分 GBM 主要分子亚型的 APA 模式。我们将这些数据与 RBP 足迹数据以及 ENCODE 联盟测试的大型面板中单个 RBP 耗尽时发生的 APA 事件叠加。我们的分析揭示了 22 个高度一致且具有统计显着性的 RBP-APA 关联，其中 TCGA 和 ENCODE 数据集中 RBP 表达的变化都伴随着 APA。其中，我们在 PRRC2B 基因中发现了一个先前未知的 PTBP1 调节的 APA 事件，在 SC5D 基因中发现了一个 HNRNPU 调节的事件。巴塞尔大学医院获得的配对肿瘤中心-外周 GBM 样本的 RNA 测序数据进一步支持了这两种观点。此外，我们在 siRNA 敲低和过表达实验中验证了 PTBP1 对 PRRC2B 中 APA 的调节，然后在两种胶质母细胞瘤细胞系中进行 RNA 测序。我们在此介绍的转录组分析工作流程能够识别癌症中一致的 RBP-APA 关联。版权所有 © 2024 Mironov、Franchitti、Ghosh、Ritz、Hutter、De Bortoli 和 Zavolan。

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 in vivo 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.Copyright © 2024 Mironov, Franchitti, Ghosh, Ritz, Hutter, De Bortoli and Zavolan.