Abstract 908: Comprehensive analysis of alternative polyadenylation across cancer phenotypes
Authors: Imada Eddie L. , Sanchez Diego F. , Matam Tejasvi , Collado-Torres Leonardo , Wilks Christopher , Dinalankara Wikum , Stupnikov Alexey , Langmead Ben , Lupold Shawn E. , Marchionni Luigi 
Published: August 2019

The three-prime untranslated region (3'-UTR) of a mRNA influences its biological behavior, from stability, post-transcriptional control through miRNAs, and availability for translation. Alternative polyadenylation (APA) can modulate 3' end site selection, and approximately 50% of coding genes are subject to it. Global transcript shortening has been reported in normal and cancer cells. APA can be seen as a regulatory step that controls differential expression of transcript isoforms, hence it can be analyzed similarly to gene expression, comparing relevant phenotypes (e.g., tumor vs. normal, survival) with appropriate statistical methods (e.g., generalized linear models, Cox proportional hazards models).We analyzed APA across 16 cancer types, taking advantage of the following public domain resources: 1) recount2, an annotation-agnostic RNA expression database for over 72,000 human samples (Collado-Torres et al, 2017); 2) Snaptron, a search engine and database that enables one to summarize expression for specific genomic regions and features (Wilks et al, 2017); and 3) APADB, the largest database collection of Human APA sites for coding and non-coding genes (Müller et al, 2014). We leveraged Snaptron to extract expression levels for 100-base-pair windows upstream and downstream APA sites defined in APADB. We annotated these genomic features, corresponding to short and long transcript isoforms, using metadata from recount2. As a proof of concept, we analyzed differential APA isoform expression in TCGA, comparing tumor vs. normal samples, and identifying APA events associated with recurrence and survival, as well as other well-defined clinical, morphologic and molecular classifications.Our preliminary results show hundreds of genes switching PA sites to shorten or extend 3'-UTR length in primary tumors when compared to normal tissues. Some of these genes are associated with cell cycle and proliferation, indicating that PA sites are dynamically used in primary tumors as another mechanism to evade and modulate post-transcriptional control. Even more interestingly, a substantial fraction of these APA isoforms were associated to tumor recurrence and survival independently from standard clinical and pathological variables.In conclusion, by leveraging public domain resources, such as APADB, recount2, and Snaptron, we created a comprehensive resource that enables to detect dynamic usage of PA sites across cancer phenotypes. Furthermore, the association of many APA isoforms with tumor progression suggests that these could serve as clinically useful biomarkers. Most importantly, the comprehensive resource we have built accounts for over 72,000 human samples, hence it is not limited to the cancer phenotypes we explored in this study. Once released in the public domain, our APA expression atlas will empower the scientific community at large to explore APA across many other cancer and human disease phenotypes.

Citation Format: Eddie L. Imada, Diego F. Sanchez, Tejasvi Matam, Leonardo Collado-Torres, Christopher Wilks, Wikum Dinalankara, Alexey Stupnikov, Ben Langmead, Shawn E. Lupold, Luigi Marchionni. Comprehensive analysis of alternative polyadenylation across cancer phenotypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 908.