William Ritchie

Orchestrated intron retention regulates normal granulocyte differentiation.

Intron retention (IR) is widely recognized as a consequence of mis-splicing that leads to failed excision of intronic sequences from pre-messenger RNAs. Our bioinformatic analyses of transcriptomic and proteomic data of normal white blood cell differentiation reveal IR as a physiological mechanism of gene expression control. IR regulates the expression of 86 functionally related genes, including those that determine the nuclear shape that is unique to granulocytes. Retention of introns in specific genes is associated with downregulation of splicing factors and higher GC content. IR, conserved between human and mouse, led to reduced mRNA and protein levels by triggering the nonsense-mediated decay (NMD) pathway. In contrast to the prevalent view that NMD is limited to mRNAs encoding aberrant proteins, our data establish that IR coupled with NMD is a conserved mechanism in normal granulopoiesis. Physiological IR may provide an energetically favorable level of dynamic gene expression control prior to sustained gene translation.

Predicting microRNA targets and functions: traps for the unwary.

To the Editor: microRNAs (miRNAs) are short RNAs that are important in gene regulation in many organisms. In mammals, they guide the RNA-induced silencing complex to target sites typically located in the 3′ untranslated regions (UTR) of mRNAs, causing translational repression and/or mRNA degradation1. Despite recent advances in large-scale target screening techniques, experimental validation of miRNA targets remains cumbersome, and computational approaches remain the most commonly used method to identify putative target genes. Most algorithms use sequences collected from either the Ensembl2 or University of California Santa Cruz (UCSC)3 databases and then preprocess these sequences to correct for genes that do not have a predicted 3′ UTR of sufficient length. However, these databases use different criteria to define 3′ UTR boundaries (Supplementary Fig. 1 online) and these boundaries will change as more sequences from varied tissue types are added to them4. To determine whether these differences can alter target prediction, we applied four popular algorithms, miRanda5, TargetScan6, RNA22 (ref. 7) and PITA8 (Supplementary Table 1 online), to two 3′ UTR databases obtained from the Ensembl and the UCSC servers (Table 1 and Supplementary Methods online). When we ran TargetScan and Miranda on sequences from the same database, the results overlapped by 39.5%, whereas when we ran the same two algorithms on two different databases, the overlap was 11.5% (Supplementary Fig. 2 online). This result demonstrates the importance of using 3′ UTR sequences from both sources when comparing results between algorithms as optimally the overlap should approach 100%. Notably, MiRBase9 uses a modified version of miRanda on Ensembl data and TargetScan uses UCSC data. Current databases of miRNA target genes provide a list of hundreds of predictions for each miRNA. To reduce the number of predictions, investigators often consider only those targets that are predicted by multiple algorithms and consider this overlap as a higher-quality subset of predictions. To test the efficiency of intersecting multiple predictions, we performed an enrichment analysis on predictions from five commonly used databases: picTar10, TargetScan, RNA22, miRBase and PITA. The rationale of our analysis was the following: if the intersection of two of these datasets is enriched in true targets, then predictions taken from this intersection are more likely to be present in the intersection of two other datasets than in their exclusion (Supplementary Fig. 3 online). We found that this relation was not significantly true in 29/30 of the permutations tested and was of borderline significance in one (P = 0.03). From this analysis we concluded that the enrichment in true targets of overlapping predictions was weak at best. Admittedly, our test would be more reliable if we compared each overlap with a dataset of experimentally validated targets. However, such a set of quality verified targets, in which target site mutagenesis is shown to reduce the efficiency of miRNA regulation, is still too small to be used as a benchmark dataset (only 48 such targets are reported in the miRecords database; http://mirecords.umn.edu/miRecords/). We suggest that the routine identification of an overlap between miRNA target prediction algorithms should be discouraged owing to a lack of utility and rationale. Two more-logical approaches to filtering miRNA target predictions would be to examine coexpression of miRNA-target pairs (Supplementary Table 2 online) or to identify instances of multitargeting: genes that are targeted multiple times by the same miRNA. Four commonly used algorithms (picTar, TargetScan, miRanda and RNA22) can detect a number of multitargeting occurrences that is much higher than the number expected by chance (Supplementary Fig. 4 online). This demonstrates that multitargeting is widespread and nonrandom. In practical terms, picTAR and RNA22 are likely to reliably predict target genes when a given miRNA target site appears three or more times in the same 3′ UTR even though this method may omit many true targets. Because miRNAs can repress many genes, it is of interest to identify groups of genes targeted by the same miRNA that share a biological function or localization. This functional profiling of miRNA targets can be performed through the Gene Ontology (GO) website (http://www.geneontology.org/) and its associated tools. In addition to the known biases inherent in GO enrichment analyses, the choice of algorithm used to predict miRNA targets can be decisive in the outcome of functional profiling (Supplementary Fig. 5 online). To test how often different target prediction algorithms will predict a different enriched GO function, we created a program called MirGO (Supplementary Data online). This program uses publicly available data to discover the GO enriched function of a set of predicted targets of a given miRNA predicted by miRanda, TargetScan or picTar. Running MirGO 1,000 times on randomly selected miRNAs (Supplementary Fig. 6 online) showed that these three popular algorithms predicted different and unrelated functions in 94% (942/1,000) of cases tested. Notably, when we ran the same experiment considering only enriched GO functions predicted with very low P values (<0.001), their predicted function was discordant in only 4% (42/1,000) of the runs, even though the predicted genes were different for each of the algorithms. The approach used in MirGO has been implemented in many online resources such as

Nuclear-localized tiny RNAs are associated with transcription initiation and splice sites in metazoans

We have recently shown that transcription initiation RNAs (tiRNAs) are derived from sequences immediately downstream of transcription start sites. Here, using cytoplasmic and nuclear small RNA high-throughput sequencing datasets, we report the identification of a second class of nuclear-specific ∼17- to 18-nucleotide small RNAs whose 3′ ends map precisely to the splice donor site of internal exons in animals. These splice-site RNAs (spliRNAs) are associated with highly expressed genes and show evidence of developmental stage– and region–specific expression. We also show that tiRNAs are localized to the nucleus, are enriched at chromatin marks associated with transcription initiation and possess a 3′-nucleotide bias. Additionally, we find that microRNA-offset RNAs (moRNAs), the miR-15/16 cluster previously linked to oncosuppression and most small nucleolar RNA (snoRNA)-derived small RNAs (sdRNAs) are enriched in the nucleus, whereas most miRNAs and two H/ACA sdRNAs are cytoplasmically enriched. We propose that nuclear-localized tiny RNAs are involved in the epigenetic regulation of gene expression.

ASCT2/SLC1A5 controls glutamine uptake and tumour growth in triple-negative basal-like breast cancer

Alanine, serine, cysteine-preferring transporter 2 (ASCT2; SLC1A5) mediates uptake of glutamine, a conditionally essential amino acid in rapidly proliferating tumour cells. Uptake of glutamine and subsequent glutaminolysis is critical for activation of the mTORC1 nutrient-sensing pathway, which regulates cell growth and protein translation in cancer cells. This is of particular interest in breast cancer, as glutamine dependence is increased in high-risk breast cancer subtypes. Pharmacological inhibitors of ASCT2-mediated transport significantly reduced glutamine uptake in human breast cancer cell lines, leading to the suppression of mTORC1 signalling, cell growth and cell cycle progression. Notably, these effects were subtype-dependent, with ASCT2 transport critical only for triple-negative (TN) basal-like breast cancer cell growth compared with minimal effects in luminal breast cancer cells. Both stable and inducible shRNA-mediated ASCT2 knockdown confirmed that inhibiting ASCT2 function was sufficient to prevent cellular proliferation and induce rapid cell death in TN basal-like breast cancer cells, but not in luminal cells. Using a bioluminescent orthotopic xenograft mouse model, ASCT2 expression was then shown to be necessary for both successful engraftment and growth of HCC1806 TN breast cancer cells in vivo. Lower tumoral expression of ASCT2 conferred a significant survival advantage in xenografted mice. These responses remained intact in primary breast cancers, where gene expression analysis showed high expression of ASCT2 and glutamine metabolism-related genes, including GLUL and GLS, in a cohort of 90 TN breast cancer patients, as well as correlations with the transcriptional regulators, MYC and ATF4. This study provides preclinical evidence for the feasibility of novel therapies exploiting ASCT2 transporter activity in breast cancer, particularly in the high-risk basal-like subgroup of TN breast cancer where there is not only high expression of ASCT2, but also a marked reliance on its activity for sustained cellular proliferation.

ASTD: The Alternative Splicing and Transcript Diversity database

The Alternative Splicing and Transcript Diversity database (ASTD) gives access to a vast collection of alternative transcripts that integrate transcription initiation, polyadenylation and splicing variant data. Alternative transcripts are derived from the mapping of transcribed sequences to the complete human, mouse and rat genomes using an extension of the computational pipeline developed for the ASD (Alternative Splicing Database) and ATD (Alternative Transcript Diversity) databases, which are now superseded by ASTD. For the human genome, ASTD identifies splicing variants, transcription initiation variants and polyadenylation variants in 68%, 68% and 62% of the gene set, respectively, consistent with current estimates for transcription variation. Users can access ASTD through a variety of browsing and query tools, including expression state-based queries for the identification of tissue-specific isoforms. Participating laboratories have experimentally validated a subset of ASTD-predicted alternative splice forms and alternative polyadenylation forms that were not previously reported. The ASTD database can be accessed at http://www.ebi.ac.uk/astd.

Targeting ASCT2-mediated glutamine uptake blocks prostate cancer growth and tumour development

Glutamine is conditionally essential in cancer cells, being utilized as a carbon and nitrogen source for macromolecule production, as well as for anaplerotic reactions fuelling the tricarboxylic acid (TCA) cycle. In this study, we demonstrated that the glutamine transporter ASCT2 (SLC1A5) is highly expressed in prostate cancer patient samples. Using LNCaP and PC‐3 prostate cancer cell lines, we showed that chemical or shRNA‐mediated inhibition of ASCT2 function in vitro decreases glutamine uptake, cell cycle progression through E2F transcription factors, mTORC1 pathway activation and cell growth. Chemical inhibition also reduces basal oxygen consumption and fatty acid synthesis, showing that downstream metabolic function is reliant on ASCT2‐mediated glutamine uptake. Furthermore, shRNA knockdown of ASCT2 in PC‐3 cell xenografts significantly inhibits tumour growth and metastasis in vivo, associated with the down‐regulation of E2F cell cycle pathway proteins. In conclusion, ASCT2‐mediated glutamine uptake is essential for multiple pathways regulating the cell cycle and cell growth, and is therefore a putative therapeutic target in prostate cancer.

Targeting Amino Acid Transport in Metastatic Castration-Resistant Prostate Cancer: Effects on Cell Cycle, Cell Growth, and Tumor Development

BACKGROUND L-type amino acid transporters (LATs) uptake neutral amino acids including L-leucine into cells, stimulating mammalian target of rapamycin complex 1 signaling and protein synthesis. LAT1 and LAT3 are overexpressed at different stages of prostate cancer, and they are responsible for increasing nutrients and stimulating cell growth. METHODS We examined LAT3 protein expression in human prostate cancer tissue microarrays. LAT function was inhibited using a leucine analog (BCH) in androgen-dependent and -independent environments, with gene expression analyzed by microarray. A PC-3 xenograft mouse model was used to study the effects of inhibiting LAT1 and LAT3 expression. Results were analyzed with the Mann-Whitney U or Fisher exact tests. All statistical tests were two-sided. RESULTS LAT3 protein was expressed at all stages of prostate cancer, with a statistically significant decrease in expression after 4-7 months of neoadjuvant hormone therapy (4-7 month mean = 1.571; 95% confidence interval = 1.155 to 1.987 vs 0 month = 2.098; 95% confidence interval = 1.962 to 2.235; P = .0187). Inhibition of LAT function led to activating transcription factor 4-mediated upregulation of amino acid transporters including ASCT1, ASCT2, and 4F2hc, all of which were also regulated via the androgen receptor. LAT inhibition suppressed M-phase cell cycle genes regulated by E2F family transcription factors including critical castration-resistant prostate cancer regulatory genes UBE2C, CDC20, and CDK1. In silico analysis of BCH-downregulated genes showed that 90.9% are statistically significantly upregulated in metastatic castration-resistant prostate cancer. Finally, LAT1 or LAT3 knockdown in xenografts inhibited tumor growth, cell cycle progression, and spontaneous metastasis in vivo. CONCLUSION Inhibition of LAT transporters may provide a novel therapeutic target in metastatic castration-resistant prostate cancer, via suppression of mammalian target of rapamycin complex 1 activity and M-phase cell cycle genes.

Micro-RNA response to imatinib mesylate in patients with chronic myeloid leukemia

Background Micro-RNAs (miRNAs) control gene expression by destabilizing targeted transcripts and inhibiting their translation. Aberrant expression of miRNAs has been described in many human cancers, including chronic myeloid leukemia. Current first-line therapy for newly diagnosed chronic myeloid leukemia is imatinib mesylate, which typically produces a rapid hematologic response. However the effect of imatinib on miRNA expression in vivo has not been thoroughly examined. Design and Methods Using a TaqMan Low-Density Array system, we analyzed miRNA expression in blood samples from newly diagnosed chronic myeloid leukemia patients before and within the first two weeks of imatinib therapy. Quantitative real-time PCR was used to validate imatinib-modulated miRNAs in sequential primary chronic myeloid leukemia samples (n=11, plus 12 additional validation patients). Bioinformatic target gene prediction analysis was performed based on changes in miRNA expression. Results We observed increased expression of miR-150 and miR-146a, and reduced expression of miR-142-3p and miR-199b-5p (3-fold median change) after two weeks of imatinib therapy. A significant correlation (P<0.05) between the Sokal score and pre-treatment miR-142-3p levels was noted. Expression changes in the same miRNAs were consistently found in an additional cohort of chronic myeloid leukemia patients, as compared to healthy subjects. Peripheral blood cells from chronic phase and blast crisis patients displayed a 30-fold lower expression of miR-150 compared to normal samples, which is of particular interest since c-Myb, a known target of miR-150, was recently shown to be necessary for Bcr-Abl-mediated transformation. Conclusions We found that imatinib treatment of chronic myeloid leukemia patients rapidly normalizes the characteristic miRNA expression profile, suggesting that miRNAs may serve as a novel clinically useful biomarker in this disease.

mimiRNA: a microRNA expression profiler and classification resource designed to identify functional correlations between microRNAs and their targets

MOTIVATION microRNAs (miRNAs) are short non-coding RNAs that regulate gene expression by inhibiting target mRNA genes. Their tissue- and disease-specific expression patterns have immense therapeutic and diagnostic potential. To understand these patterns, a reliable compilation of miRNA and mRNA expression data is required to compare multiple tissue types. Moreover, with the appropriate statistical tools, such a resource could be interrogated to discover functionally related miRNA-mRNA pairs. RESULTS We have developed mimiRNA, an online resource that integrates expression data from 1483 samples and permits visualization of the expression of 635 human miRNAs across 188 different tissues or cell types. mimiRNA incorporates a novel sample classification algorithm, ExParser, that groups identical miRNA or mRNA experiments from separate sources. This enables mimiRNA to provide reliable expression profiles and to discover functional relations between miRNAs and mRNAs such as miRNA targets. Additionally, mimiRNA incorporates a decision tree algorithm to discover distinguishing miRNA features between two tissue or cell types. We validate the efficacy of our resource on independent experimental data and through biologically relevant analyses. AVAILABILITY http://mimirna.centenary.org.au. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Global MicroRNA Profiling of the Mouse Ventricles during Development of Severe Hypertrophic Cardiomyopathy and Heart Failure

MicroRNAs (miRNAs) regulate post-transcriptional gene expression during development and disease. We have determined the miRNA expression levels of early- and end-stage hypertrophic cardiomyopathy (HCM) in a severe, transgenic mouse model of the disease. Five miRNAs were differentially expressed at an early stage of HCM development. Time-course analysis revealed that decreased expression of miR-1 and miR-133a commences at a pre-disease stage, and precedes upregulation of target genes causal of cardiac hypertrophy and extracellular matrix remodelling, suggesting a role for miR-1 and miR-133a in early disease development. At end-stage HCM, 16 miRNA are dysregulated to form an expression profile resembling that of other forms of cardiac hypertrophy, suggesting common responses. Analysis of the mRNA transcriptome revealed that miRNAs potentially target 15.7% upregulated and 4.8% downregulated mRNAs at end-stage HCM, and regulate mRNAs associated with cardiac hypertrophy and electrophysiology, calcium signalling, fibrosis, and the TGF-β signalling pathway. Collectively, these results define the miRNA expression signatures during development and progression of severe HCM and highlight critical miRNA regulated gene networks that are involved in disease pathogenesis.