CAFuncAPA: a knowledgebase for systematic functional annotations of APA events in human cancers

Abstract

Alternative polyadenylation (APA) is a widespread posttranscriptional regulation process. APA generates diverse mRNA isoforms with different 3' UTR lengths, affecting mRNA expression, miRNA binding regulation and alternative splicing events. Previous studies have demonstrated the important roles of APA in tumorigenesis and cancer progression through diverse aspects. Thus, a comprehensive functional landscape of diverse APA events would aid in a better understanding of the underlying mechanisms related to APA in human cancers. Here, we built CAFuncAPA (https://relab.xidian.edu.cn/CAFuncAPA/) to systematically annotate the functions of 15478 APA events in human pan-cancers. Specifically, we first identified APA events associated with cancer survival and tumor progression. We annotated the potential downstream effects of APA on genes/isoforms expression, regulation of miRNAs, RNA binding proteins (RBPs) and alternative splicing events. Moreover, we also identified up-regulators of APA events, including the effects of genetic variants on poly(A) sites and RBPs, as well as the effect of methylation phenotypes on APA events. These findings suggested that CAFuncAPA can be a helpful resource for a better understanding of APA regulators and potential functions in cancer biology.

Figure 1.

Content of CAFuncAPA. CAFuncAPA contains five APA downstream effects and two up-regulator analyses. The downstream effects included analyses of APA effects on genes/isoforms expression, miRNA binding regulation, RNA binding protein (RBP) regulation and alternative splicing regulation. The up-regulator analyses included the effect of the genetic variants on APA events (genetic variants on PAS and RBP genes), and the effect of methylation phenotypes on APA events.

Figure 2.

Example of functional analyses of CAFuncAPA. (A) Genomic structure of APA events of TCGA. Genome browsers also provide transcript isoform and other structural information such as SNPs. (B) K–M survival analysis showed that APA event in MAPK1 was associated with KIRC survival. Patients with higher PDUI had better survival than patients with lower PDUI. (C) Correlation analysis between APA events and the expression of MAPK1. A negative correlation showed that a lower PDUI (shorter 3’UTR) was significantly correlated with higher gene expression. (D) The expression of MAPK1 showed a significant association with KIRC survival. (E) Escaped miR-149-5p may potentially inhibit CMTM3 and CRTC2, resulting in an oncogene-miRNA-suppressor axis in cancer. (F) APA event on HNRNPA1 in breast cancer may potentially affect the AS event on APH1A. (G) Different genotypes of HNRNPU showed an association with APA events on CD55 in breast cancer.

Figure 3.

The main functions of CAFuncAPA. (A) The logo and the top navigation bar of the main functions in CAFuncAPA. (B) ‘Quick search’ function of CAFuncAPA. Users can choose the cancer type and the gene symbol of interest. (C) Cancer type included in CAFunAPA. Users can obtain cancer-specific APA genes through this function. (D) Functional analyses included in CAFuncAPA. Users can obtain APA genes related to each functional annotation. (E) The Download function in CAFuncAPA. (F) The Landscape of functional annotation analyses in CAFuncAPA. (G) The Help function contains a brief introduction of CAFuncAPA and its functions.