3'-UTR Shortening Contributes to Subtype-Specific Cancer Growth by Breaking Stable ceRNA Crosstalk of Housekeeping Genes

Alternative polyadenylation regulation in cardiac development and cardiovascular disease

Cleavage and polyadenylation of pre-mRNAs is a necessary step for gene expression and function. Majority of human genes exhibit multiple polyadenylation sites, which can be alternatively used to generate different mRNA isoforms from a single gene. Alternative polyadenylation (APA) of pre-mRNAs is important for the proteome and transcriptome landscape. APA is tightly regulated during development and contributes to tissue-specific gene regulation. Mis-regulation of APA is linked to a wide range of pathological conditions. APA-mediated gene regulation in the heart is emerging as a new area of research. Here, we will discuss the impact of APA on gene regulation during heart development and in cardiovascular diseases. First, we will briefly review how APA impacts gene regulation and discuss molecular mechanisms that control APA. Then, we will address APA regulation during heart development and its dysregulation in cardiovascular diseases. Finally, we will discuss pre-mRNA targeting strategies to correct aberrant APA patterns of essential genes for the treatment or prevention of cardiovascular diseases. The RNA field is blooming due to advancements in RNA-based technologies. RNA-based vaccines and therapies are becoming the new line of effective and safe approaches for the treatment and prevention of human diseases. Overall, this review will be influential for understanding gene regulation at the RNA level via APA in the heart and will help design RNA-based tools for the treatment of cardiovascular diseases in the future.

CPSF6-mediated XBP1 3'UTR shortening attenuates cisplatin-induced ER stress and elevates chemo-resistance in lung adenocarcinoma

Alternative polyadenylation (APA) is a widespread mechanism generating RNA molecules with alternative 3' ends. Herein, we discovered that TargetScan includes a novel XBP1 transcript with a longer 3' untranslated region (UTR) (XBP1-UL) than that included in NCBI. XBP1-UL exhibited a lowered level in blood samples from lung adenocarcinoma (LUAD) patients and in those after DDP treatment. Consistently, XBP1-UL was reduced in A549 cells compared to normal BEAS-2B cells, as well as in DDP-treated/resistant A549 cells relative to controls. Moreover, due to decreased usage of the distal polyadenylation site (PAS) in 3'UTR, XBP1-UL level was lowered in A549 cells and decreased further in DDP-resistant A549 (A549/DDP) cells. Importantly, use of the distal PAS (dPAS) and XBP1-UL level were gradually reduced in A549 cells under increasing concentrations of DDP, which was attributed to DDP-induced endoplasmic reticulum (ER) stress. Furthermore, XBP1 transcripts with shorter 3'UTR (XBP1-US) were more stable and presented stronger potentiation on DDP resistance. The choice of proximal PAS (pPAS) was attributed to CPSF6 elevation, which was caused by BRCA1-distrupted R-loop accumulation in CPSF6 5'end. DDP-induced nuclear LINC00221 also facilitated CPSF6-induced pPAS choice in the pre-XBP1 3'end. Finally, we found that unlike the unspliced XBP1 protein (XBP1-u), the spliced form XBP1-s retarded p53 degradation to facilitate DNA damage repair of LUAD cells. The current study provides new insights into tumor progression and DDP resistance in LUAD, which may contribute to improved LUAD treatment.

Deep neural networks with knockoff features identify nonlinear causal relations and estimate effect sizes in complex biological systems

BACKGROUND

Learning the causal structure helps identify risk factors, disease mechanisms, and candidate therapeutics for complex diseases. However, although complex biological systems are characterized by nonlinear associations, existing bioinformatic methods of causal inference cannot identify the nonlinear relationships and estimate their effect size.

RESULTS

To overcome these limitations, we developed the first computational method that explicitly learns nonlinear causal relations and estimates the effect size using a deep neural network approach coupled with the knockoff framework, named causal directed acyclic graphs using deep learning variable selection (DAG-deepVASE). Using simulation data of diverse scenarios and identifying known and novel causal relations in molecular and clinical data of various diseases, we demonstrated that DAG-deepVASE consistently outperforms existing methods in identifying true and known causal relations. In the analyses, we also illustrate how identifying nonlinear causal relations and estimating their effect size help understand the complex disease pathobiology, which is not possible using other methods.

CONCLUSIONS

With these advantages, the application of DAG-deepVASE can help identify driver genes and therapeutic agents in biomedical studies and clinical trials.

The Estrogen Receptor α Signaling Pathway Controls Alternative Splicing in the Absence of Ligands in Breast Cancer Cells

Background: The transcriptional activity of estrogen receptor α (ERα) in breast cancer (BC) is extensively characterized. Our group has previously shown that ERα controls the expression of a number of genes in its unliganded form (apoERα), among which a large group of RNA-binding proteins (RBPs) encode genes, suggesting its role in the control of co- and post-transcriptional events. Methods: apoERα-mediated RNA processing events were characterized by the analysis of transcript usage and alternative splicing changes in an RNA-sequencing dataset from MCF-7 cells after siRNA-induced ERα downregulation. Results: ApoERα depletion induced an expression change of 681 RBPs, including 84 splicing factors involved in translation, ribonucleoprotein complex assembly, and 3′end processing. ApoERα depletion results in 758 isoform switching events with effects on 3′end length and the splicing of alternative cassette exons. The functional enrichment of these events shows that post-transcriptional regulation is part of the mechanisms by which apoERα controls epithelial-to-mesenchymal transition and BC cell proliferation. In primary BCs, the inclusion levels of the experimentally identified alternatively spliced exons are associated with overall and disease-free survival. Conclusion: Our data supports the role of apoERα in maintaining the luminal phenotype of BC cells by extensively regulating gene expression at the alternative splicing level.

Alternative polyadenylation: An enigma of transcript length variation in health and disease

Alternative polyadenylation (APA) is a molecular mechanism during a pre-mRNA processing that involves usage of more than one polyadenylation site (PA-site) generating transcripts of varying length from a single gene. The location of a PA-site affects transcript length and coding potential of an mRNA contributing to both mRNA and protein diversification. This variation in the transcript length affects mRNA stability and translation, mRNA subcellular and tissue localization, and protein function. APA is now considered as an important regulatory mechanism in the pathophysiology of human diseases. An important consequence of the changes in the length of 3'-untranslated region (UTR) from disease-induced APA is altered protein expression. Yet, the relationship between 3'-UTR length and protein expression remains a paradox in a majority of diseases. Here, we review occurrence of APA, mechanism of PA-site selection, and consequences of transcript length variation in different diseases. Emerging evidence reveals coordinated involvement of core RNA processing factors including poly(A) polymerases in the PA-site selection in diseases-associated APAs. Targeting such APA regulators will be therapeutically significant in combating drug resistance in cancer and other complex diseases. This article is categorized under: RNA Processing > 3' End Processing RNA in Disease and Development > RNA in Disease Translation > Regulation.

Transforming growth factor‑β1 functions as a competitive endogenous RNA that ameliorates intracranial hemorrhage injury by sponging microRNA‑93‑5p

Intracerebral hemorrhage (ICH) has the highest mortality rate of all stroke subtypes but an effective treatment has yet to be clinically implemented. Transforming growth factor-β1 (TGF-β1) has been reported to modulate microglia-mediated neuroinflammation after ICH and promote functional recovery; however, the underlying mechanisms remain unclear. Non-coding RNAs such as microRNAs (miRNAs) and competitive endogenous RNAs (ceRNAs) have surfaced as critical regulators in human disease. A known miR-93 target, nuclear factor erythroid 2-related factor 2 (Nrf2), has been shown to be neuroprotective after ICH. It was hypothesized that TGF-β1 functions as a ceRNA that sponges miR-93-5p and thereby ameliorates ICH injury in the brain. Short interfering RNA (siRNA) was used to knock down TGF-β1 and miR-93 expression was also pharmacologically manipulated to elucidate the mechanistic association between miR-93-5p, Nrf2, and TGF-β1 in an in vitro model of ICH (thrombin-treated human microglial HMO6 cells). Bioinformatics predictive analyses showed that miR-93-5p could bind to both TGF-β1 and Nrf2. It was found that neuronal miR-93-5p was dramatically decreased in these HMO6 cells, and similar changes were observed in fresh brain tissue from patients with ICH. Most importantly, luciferase reporter assays were used to demonstrate that miR-93-5p directly targeted Nrf2 to inhibit its expression and the addition of the TGF-β1 untranslated region restored the levels of Nrf2. Moreover, an miR-93-5p inhibitor increased the expression of TGF-β1 and Nrf2 and decreased apoptosis. Collectively, these results identified a novel function of TGF-β1 as a ceRNA that sponges miR-93-5p to increase the expression of neuroprotective Nrf2 and decrease cell death after ICH. The present findings provided evidence to support miR-93-5p as a potential therapeutic target for the treatment of ICH.