Cell cycle, oncogenic and tumor suppressor pathways regulate numerous long and macro non-protein-coding RNAs

Comparative RNA Genomics

Over the last quarter of a century it has become clear that RNA is much more than just a boring intermediate in protein expression. Ancient RNAs still appear in the core information metabolism and comprise a surprisingly large component in bacterial gene regulation. A common theme with these types of mostly small RNAs is their reliance of conserved secondary structures. Large-scale sequencing projects, on the other hand, have profoundly changed our understanding of eukaryotic genomes. Pervasively transcribed, they give rise to a plethora of large and evolutionarily extremely flexible non-coding RNAs that exert a vastly diverse array of molecule functions. In this chapter we provide a-necessarily incomplete-overview of the current state of comparative analysis of non-coding RNAs, emphasizing computational approaches as a means to gain a global picture of the modern RNA world.

221S-1a inhibits endothelial proliferation in pathological angiogenesis through ERK/c-Myc signaling

Pathological angiogenesis plays a major role in many disease processes, including cancer and diabetic retinopathy. Antiangiogenic therapy is a potential management for pathologic angiogenesis. The novel synthetic compound 221S-1a, derived from captopril, tanshinol and borneol, may have antiangiogenic properties. On the basis of MS, NMR and HPLC analysis, the structure of 221S-1a was identified. The cellular uptake and metabolism of this compound was also observed. Next, the antiangiogenic properties of 221S-1a were evaluated in tumor-xenograft and OIR models in vivo. The inhibitory properties of 221S-1a on endothelial cell proliferation, migration, tube formation and sprouting were detected in vitro. Furthermore, 221S-1a induced G1/S phase arrest was detected by PI staining flow cytometry analysis and Cyclin D, Cyclin E expression. 221S-1a inhibited ERK1/2 activation and nuclear translocation, in addition to downregulation of c-Myc, a transcription factor that regulates cell cycle progression. Molecular docking indicated the interaction of 221S-1a with the ATP-binding site of ERK2, leading to the inhibition of ERK2 phosphorylation and a concomitant inhibition of ERK1 phosphorylation. In conclusion, 221S-1a inhibited the G1/S phase transition by blocking the ERK1/2/c-Myc pathway to reduce tumor and OIR retinal angiogenesis. These novel findings suggest that 221S-1a is a potential pharmacologic candidate for treating pathological angiogenesis.

An Isoxazoloquinone Derivative Inhibits Tumor Growth by Targeting STAT3 and Triggering Its Ubiquitin-Dependent Degradation

BACKGROUND

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, with shorter five-year survival than other breast cancer subtypes, and lacks targeted and hormonal treatment strategies. The signal transducer and activator of transcription 3 (STAT3) signaling is up-regulated in various tumors, including TNBC, and plays a vital role in regulating the expression of multiple proliferation- and apoptosis-related genes.

RESULTS

By combining the unique structures of the natural compounds STA-21 and Aulosirazole with antitumor activities, we synthesized a class of novel isoxazoloquinone derivatives and showed that one of these compounds, ZSW, binds to the SH2 domain of STAT3, leading to decreased STAT3 expression and activation in TNBC cells. Furthermore, ZSW promotes STAT3 ubiquitination, inhibits the proliferation of TNBC cells in vitro, and attenuates tumor growth with manageable toxicities in vivo. ZSW also decreases the mammosphere formation of breast cancer stem cells (BCSCs) by inhibiting STAT3.

CONCLUSIONS

We conclude that the novel isoxazoloquinone ZSW may be developed as a cancer therapeutic because it targets STAT3, thereby inhibiting the stemness of cancer cells.

The landscape of human p53-regulated long non-coding RNAs reveals critical host gene co-regulation

The role of long non-coding RNAs (lncRNAs) in p53-mediated tumor suppression has become increasingly appreciated in the past decade. Thus, the identification of p53-regulated lncRNAs can be a promising starting point to select and prioritize lncRNAs for functional analyses. By integrating transcriptome and transcription factor-binding data, we identified 379 lncRNAs that are recurrently differentially regulated by p53. Dissecting the mechanisms by which p53 regulates many of them, we identified sets of lncRNAs regulated either directly by p53 or indirectly through the p53-RFX7 and p53-p21-DREAM/RB:E2F pathways. Importantly, we identified multiple p53-responsive lncRNAs that are co-regulated with their protein-coding host genes, revealing an important mechanism by which p53 may regulate lncRNAs. Further analysis of transcriptome data and clinical data from cancer patients showed that recurrently p53-regulated lncRNAs are associated with patient survival. Together, the integrative analysis of the landscape of p53-regulated lncRNAs provides a powerful resource facilitating the identification of lncRNA function and displays the mechanisms of p53-dependent regulation that could be exploited for developing anticancer approaches.

Traditional Chinese medicine for transformation of gastric precancerous lesions to gastric cancer: A critical review

Gastric cancer (GC) is a common gastrointestinal tumor. Gastric precancerous lesions (GPL) are the last pathological stage before normal gastric mucosa transforms into GC. However, preventing the transformation from GPL to GC remains a challenge. Traditional Chinese medicine (TCM) has been used to treat gastric disease for millennia. A series of TCM formulas and active compounds have shown therapeutic effects in both GC and GPL. This article reviews recent progress on the herbal drugs and pharmacological mechanisms of TCM in preventing the transformation from GPL to GC, especially focusing on anti-inflammatory, anti-angiogenesis, proliferation, and apoptosis. This review may provide a meaningful reference for the prevention of the transformation from GPL to GC using TCM.

Long non-coding RNA ESCCAL-1/miR-590/LRP6 signaling pathway participates in the progression of esophageal squamous cell carcinoma

BACKGROUND

Long non-coding RNAs (lncRNAs) have critical functions within esophageal squamous cell carcinoma (ESCC). However, the function and mechanism underlying ESCC-associated lncRNA-1 (ESCCAL-1) in ESCC tumorigenesis have not been well clarified.

METHODS

ESCCAL-1, miR-590 and LRP6 were quantified using qRT-PCR. Cell viability, migration and invasion abilities were measured using CCK-8 assay and transwell assays. The protein pression was determined with western blot assay. The xenograft model assays were used to examine the impact of ESCCAL-1 on tumorigenic effect in vivo. Direct relationships among ESCCAL-1, miR-590 and LRP6 were confirmed using dual-luciferase reporter assays.

RESULTS

The present work discovered the ESCCAL-1 up-regulation within ESCC. Furthermore, ESCCAL-1 was found to interact with miR-590 and consequently restrict its expression. Functionally, knocking down ESCCAL-1 or over-expressing miR-590 hindered ESCC cell growth, invasion, and migration in vitro. Moreover, inhibition of miR-590 could reverse the effect of knockdown of ESCCAL-1 on cells. Importantly, it was confirmed that LRP6 was miR-590's downstream target and LRP6 over-expression also partly abolished the role of miR-590 overexpression in ESCC cells.

CONCLUSION

We have uncovered a novel regulatory network comprising aberrant interaction of ESCCAL-1/miR-590/LRP6 participated in ESCC progression.

Clinical Perspectives of Non-Coding RNA in Oral Inflammatory Diseases and Neuropathic Pain: A Narrative Review

Non-coding RNAs (ncRNAs) represent a research hotspot by playing a key role in epigenetic and transcriptional regulation of diverse biological functions and due to their involvement in different diseases, including oral inflammatory diseases. Based on ncRNAs’ suitability for salivary biomarkers and their involvement in neuropathic pain and tissue regeneration signaling pathways, the present narrative review aims to highlight the potential clinical applications of ncRNAs in oral inflammatory diseases, with an emphasis on salivary diagnostics, regenerative dentistry, and precision medicine for neuropathic orofacial pain.

Multidimensional Mutational Profiling of the Indian HNSCC Sub-Population Provides IRAK1, a Novel Driver Gene and Potential Druggable Target

Head and neck squamous cell carcinomas (HNSCC) include heterogeneous group of tumors, classified according to their anatomical site. It is the sixth most prevalent cancer globally. Among South Asian countries, India accounts for 40% of HNC malignancies with significant morbidity and mortality. In the present study, we have performed exome sequencing and analysis of 51 Head and Neck squamous cell carcinoma samples. Besides known mutations in the oncogenes and tumour suppressors, we have identified novel gene signatures differentiating buccal, alveolar, and tongue cancers. Around 50% of the patients showed mutation in tumour suppressor genes TP53 and TP63. Apart from the known mutations, we report novel mutations in the genes AKT1, SPECC1, and LRP1B, which are linked with tumour progression and patient survival. A highly curated process was developed to identify survival signatures. 36 survival-related genes were identified based on the correlation of functional impact of variants identified using exome-seq with gene expression from transcriptome data (GEPIA database) and survival. An independent LASSO regression analysis was also performed. Survival signatures common to both the methods led to identification of 4 dead and 3 alive gene signatures, the accuracy of which was confirmed by performing a ROC analysis (AUC=0.79 and 0.91, respectively). Also, machine learning-based driver gene prediction tool resulted in the identification of IRAK1 as the driver (p-value = 9.7 e-08) and also as an actionable mutation. Modelling of the IRAK1 mutation showed a decrease in its binding to known IRAK1 inhibitors.

Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019

In coronavirus disease 2019 (COVID-19) patients, interleukin (IL)-6 is one of the leading factors causing death through cytokine release syndrome. Hence, identification of IL-6 downstream from clinical patients’ transcriptome is very valid for analyses of its mechanism. However, clinical study is conditional and time consuming to collect optional size of samples, as patients have the clinical heterogeneity. A possible solution is to deeply mine the relative existing data. Several transcriptome-based studies on other diseases or treatments have revealed different genes to be regulated by IL-6. Through our meta-analysis of these transcriptome datasets, 352 genes were suggested to be regulated by IL-6 in different biological conditions, some of which were related to virus infection and cardiovascular disease. Among them, 232 genes were not identified by current transcriptome studies from clinical research. ICAM1 and PFKFB3 were the most significantly upregulated genes in our meta-analysis and could be employed as biomarkers in patients with severe COVID-19. In general, a meta-analysis of transcriptome datasets could be an alternative way to analyze the immune response and complications of patients suffering from severe COVID-19 and other emergency diseases.

Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages

Insights into the modes of action (MoAs) of xenobiotics are of utmost importance for the definition of adverse outcome pathways (AOPs), which are essential for a mechanism-based risk assessment. A well-established strategy to reveal MoAs of xenobiotics is the use of omics. However, often an even more comprehensive approach is needed, which can be achieved using multi-omics. Since the immune system plays a central role in the defense against foreign substances and pathogens, with the innate immune system building a first barrier, we systematically reviewed multi-omics studies investigating the effects of xenobiotics on macrophages. Surprisingly, only nine publications were identified, combining proteomics with transcriptomics or metabolomics. We summarized pathways and single proteins, transcripts, or metabolites, which were described to be affected upon treatment with xenobiotics in the reviewed studies, thus revealing a broad range of effects. In summary, we show that macrophages are a relevant model system to investigate the toxicological effects induced by xenobiotics. Furthermore, the multi-omics approaches led to a more comprehensive overview compared to only one omics layer with slight advantages for combinations that complement each other directly, e.g., proteome and metabolome.

LUAD transcriptomic profile analysis of d-limonene and potential lncRNA chemopreventive target

d-Limonene, a type of natural extract obtained from citrus oils, was reported to have anti-cancer effects and be well-tolerated by cancer patients. Despite arousing interest as a cancer chemopreventive substance, the transcriptomic profile of d-limonene in humans is poorly understood. Based on the results of the transcriptomic profiling, a lncRNA named protein disulfide isomerase family A member three pseudogene (PDIA3P1) was found to be regulated by d-limonene. PDIA3P1 is an oncogene verified by three lung adenocarcinoma (LUAD) datasets. The knockdown of PDIA3P1 with siRNA decreased the viability, invasion, migration, and proliferation of LUAD cells. Based on The Cancer Genome Atlas (TCGA) LUAD datasets, PDIA3P1 regulates functions and pathways mainly including lipid metabolism, immunity, and the change of the chromosome structure. This study comprehensively performs the transcriptomic analysis of the d-limonene regulation on LUAD, and reveals that PDIA3P1 may be the mediator in helping d-limonene to prevent and suppress LUAD via lipid metabolism, immunity pathway, and the change in the chromosome structure.

A Novel Integrative Approach for Non-coding RNA Classification Based on Deep Learning

Background:

Molecular biomarkers show new ways to understand many disease processes. Noncoding RNAs as biomarkers play a crucial role in several cellular activities, which are highly correlated to many human diseases especially cancer. The classification and the identification of ncRNAs have become a critical issue due to their application, such as biomarkers in many human diseases.

Objective:

Most existing computational tools for ncRNA classification are mainly used for classifying only one type of ncRNA. They are based on structural information or specific known features. Furthermore, these tools suffer from a lack of significant and validated features. Therefore, the performance of these methods is not always satisfactory.

Methods:

We propose a novel approach named imCnC for ncRNA classification based on multisource deep learning, which integrates several data sources such as genomic and epigenomic data to identify several ncRNA types. Also, we propose an optimization technique to visualize the extracted features pattern from the multisource CNN model to measure the epigenomics features of each ncRNA type.

Results:

The computational results using a dataset of 16 human ncRNA classes downloaded from RFAM show that imCnC outperforms the existing tools. Indeed, imCnC achieved an accuracy of 94,18%. In addition, our method enables to discover new ncRNA features using an optimization technique to measure and visualize the features pattern of the imCnC classifier.

Master and servant: LINC00152 - a STAT3-induced long noncoding RNA regulates STAT3 in a positive feedback in human multiple myeloma

Background

The survival of INA-6 human multiple myeloma cells is strictly dependent upon the Interleukin-6-activated transcription factor STAT3. Although transcriptional analyses have revealed many genes regulated by STAT3, to date no protein-coding STAT3 target gene is known to mediate survival in INA-6 cells. Therefore, the aim here was to identify and analyze non-protein-coding STAT3 target genes. In addition to the oncogenic microRNA-21, we previously described five long noncoding RNAs (lncRNAs) induced by STAT3, named STAiRs. Here, we focus on STAT3-induced RNA 18 (STAiR18), an mRNA-like, long ncRNA that is duplicated in the human lineage. One STAiR18 locus is annotated as the already well described LINC00152/CYTOR, however, the other harbors the MIR4435-2HG gene and is, up to now, barely described.

Methods

CAPTURE-RNA-sequencing was used to analyze STAiR18 transcript architecture. To identify the STAiR18 and STAT3 phenotype, siRNA-based knockdowns were performed and microarrays were applied to identify their target genes. RNA-binding partners of STAiR18 were determined by Chromatin-Isolation-by-RNA-Purification (ChIRP) and subsequent sequencing. STAT3 expression in dependence of STAiR18 was investigated by immunoblots, chromatin- and RNA-immunoprecipitations.

Results

As identified by CAPTURE-RNA sequencing, a complex splice pattern originates from both STAiR18 loci, generating different transcripts. Knockdown of the most abundant STAiR18 isoforms dramatically decreased INA-6 cell vitality, suggesting a functional role in myeloma cells. Additionally, STAiR18 and STAT3 knockdowns yielded overlapping changes of transcription patterns in INA-6 cells, suggesting a close functional interplay between the two factors. Moreover, Chromatin isolation by RNA purification (ChIRP), followed by genome-wide RNA sequencing showed that STAiR18 associates specifically with the STAT3 primary transcript. Furthermore, the knockdown of STAiR18 reduced STAT3 levels on both the RNA and protein levels, suggesting a positive feedback between both molecules. Furthermore, STAiR18 knockdown changes the histone methylation status of the STAT3 locus, which explains the positive feedback and indicates that STAiR18 is an epigenetic modulator.

Conclusion

Hence, STAiR18 is an important regulator of myeloma cell survival and is strongly associated with the oncogenic function of STAT3. The close functional interplay between STAT3 and STAiR18 suggests a novel principle of regulatory interactions between long ncRNAs and signaling pathways.

Prospects and challenges of multi-omics data integration in toxicology

Exposure of cells or organisms to chemicals can trigger a series of effects at the regulatory pathway level, which involve changes of levels, interactions, and feedback loops of biomolecules of different types. A single-omics technique, e.g., transcriptomics, will detect biomolecules of one type and thus can only capture changes in a small subset of the biological cascade. Therefore, although applying single-omics analyses can lead to the identification of biomarkers for certain exposures, they cannot provide a systemic understanding of toxicity pathways or adverse outcome pathways. Integration of multiple omics data sets promises a substantial improvement in detecting this pathway response to a toxicant, by an increase of information as such and especially by a systemic understanding. Here, we report the findings of a thorough evaluation of the prospects and challenges of multi-omics data integration in toxicological research. We review the availability of such data, discuss options for experimental design, evaluate methods for integration and analysis of multi-omics data, discuss best practices, and identify knowledge gaps. Re-analyzing published data, we demonstrate that multi-omics data integration can considerably improve the confidence in detecting a pathway response. Finally, we argue that more data need to be generated from studies with a multi-omics-focused design, to define which omics layers contribute most to the identification of a pathway response to a toxicant.

Long non-coding RNAs in brain tumours: Focus on recent epigenetic findings in glioma

Glioma biology is a major focus in tumour research, primarily due to the aggressiveness and high mortality rate of its most aggressive form, glioblastoma. Progress in understanding the molecular mechanisms behind poor prognosis of glioblastoma, regardless of treatment approaches, has changed the classification of brain tumours after nearly 100 years of relying on anatomopathological criteria. Expanding knowledge in genetic, epigenetic and translational medicine is also beginning to contribute to further elucidating molecular dysregulation in glioma. Long non‐coding RNAs (lncRNAs) and their main representatives, large intergenic non‐coding RNAs (lincRNAs), have recently been under scrutiny in glioma research, revealing novel mechanisms of pathogenesis and reinforcing others. Among those confirmed was the reactivation of events significant for foetal brain development and neuronal commitment. Novel mechanisms of tumour suppression and activation of stem‐like behaviour in tumour cells have also been examined. Interestingly, these processes involve lncRNAs that are present both during normal brain development and in brain malignancies and their reactivation might be explained by epigenetic mechanisms, which we discuss in detail in the present review. In addition, the review discusses the lncRNAs‐induced changes, as well as epigenetic changes that are consequential for tumour formation, affecting, in turn, the expression of various types of lncRNAs.

Comparative RNA Genomics

Over the last two decades it has become clear that RNA is much more than just a boring intermediate in protein expression. Ancient RNAs still appear in the core information metabolism and comprise a surprisingly large component in bacterial gene regulation. A common theme with these types of mostly small RNAs is their reliance of conserved secondary structures. Large scale sequencing projects, on the other hand, have profoundly changed our understanding of eukaryotic genomes. Pervasively transcribed, they give rise to a plethora of large and evolutionarily extremely flexible noncoding RNAs that exert a vastly diverse array of molecule functions. In this chapter we provide a-necessarily incomplete-overview of the current state of comparative analysis of noncoding RNAs, emphasizing computational approaches as a means to gain a global picture of the modern RNA world.

A Support Vector Machine based method to distinguish long non-coding RNAs from protein coding transcripts

Background

In recent years, a rapidly increasing number of RNA transcripts has been generated by thousands of sequencing projects around the world, creating enormous volumes of transcript data to be analyzed. An important problem to be addressed when analyzing this data is distinguishing between long non-coding RNAs (lncRNAs) and protein coding transcripts (PCTs). Thus, we present a Support Vector Machine (SVM) based method to distinguish lncRNAs from PCTs, using features based on frequencies of nucleotide patterns and ORF lengths, in transcripts.

Methods

The proposed method is based on SVM and uses the first ORF relative length and frequencies of nucleotide patterns selected by PCA as features. FASTA files were used as input to calculate all possible features. These features were divided in two sets: (i) 336 frequencies of nucleotide patterns; and (ii) 4 features derived from ORFs. PCA were applied to the first set to identify 6 groups of frequencies that could most contribute to the distinction. Twenty-four experiments using the 6 groups from the first set and the features from the second set where built to create the best model to distinguish lncRNAs from PCTs.

Results

This method was trained and tested with human (Homo sapiens), mouse (Mus musculus) and zebrafish (Danio rerio) data, achieving 98.21%, 98.03% and 96.09%, accuracy, respectively. Our method was compared to other tools available in the literature (CPAT, CPC, iSeeRNA, lncRNApred, lncRScan-SVM and FEELnc), and showed an improvement in accuracy by ≈3.00%. In addition, to validate our model, the mouse data was classified with the human model, and vice-versa, achieving ≈97.80% accuracy in both cases, showing that the model is not overfit. The SVM models were validated with data from rat (Rattus norvegicus), pig (Sus scrofa) and fruit fly (Drosophila melanogaster), and obtained more than 84.00% accuracy in all these organisms. Our results also showed that 81.2% of human pseudogenes and 91.7% of mouse pseudogenes were classified as non-coding. Moreover, our method was capable of re-annotating two uncharacterized sequences of Swiss-Prot database with high probability of being lncRNAs. Finally, in order to use the method to annotate transcripts derived from RNA-seq, previously identified lncRNAs of human, gorilla (Gorilla gorilla) and rhesus macaque (Macaca mulatta) were analyzed, having successfully classified 98.62%, 80.8% and 91.9%, respectively.

Conclusions

The SVM method proposed in this work presents high performance to distinguish lncRNAs from PCTs, as shown in the results. To build the model, besides using features known in the literature regarding ORFs, we used PCA to identify features among nucleotide pattern frequencies that contribute the most in distinguishing lncRNAs from PCTs, in reference data sets. Interestingly, models created with two evolutionary distant species could distinguish lncRNAs of even more distant species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4178-4) contains supplementary material, which is available to authorized users.

Expression Profiling of Long Noncoding RNA Splice Variants in Human Microvascular Endothelial Cells: Lipopolysaccharide Effects In Vitro

Endothelial cell interactions with lipopolysaccharide (LPS) involve both activating and repressing signals resulting in pronounced alterations in their transcriptome and proteome. Noncoding RNAs are now appreciated as posttranscriptional and translational regulators of cellular signaling and responses, but their expression status and roles during endothelial interactions with LPS are not well understood. We report on the expression profile of long noncoding (lnc) RNAs of human microvascular endothelial cells in response to LPS. We have identified a total of 10,781 and 8310 lncRNA transcripts displaying either positive or negative regulation of expression, respectively, at 3 and 24 h posttreatment. A majority of LPS-induced lncRNAs are multiexonic and distributed across the genome as evidenced by their presence on all chromosomes. Present among these are a total of 44 lncRNAs with known regulatory functions, of which 41 multiexonic lncRNAs have multiple splice variants. We have further validated splice variant-specific expression of EGO (NONHSAT087634) and HOTAIRM1 (NONHSAT119666) at 3 h and significant upregulation of lnc-IL7R at 24 h. This study illustrates the genome-wide regulation of endothelial lncRNA splice variants in response to LPS and provides a foundation for further investigations of differentially expressed lncRNA transcripts in endothelial responses to LPS and pathophysiology of sepsis/septic shock.

Non-coding RNA in hepatocellular carcinoma: Mechanisms, biomarkers and therapeutic targets

The majority of the human genome is not translated into proteins but can be transcribed into RNA. Even though the resulting non-coding RNAs (ncRNAs) do not encode for proteins, they contribute to diseases such as cancer. Here, we review examples of the functions of ncRNAs in liver cancer and their potential use for the detection and treatment of liver cancer.

STAT3-induced long noncoding RNAs in multiple myeloma cells display different properties in cancer

Interleukin-6 (IL-6)-activated Signal Transducer and Activator of Transcription 3 (STAT3) facilitates survival in the multiple myeloma cell line INA-6 and therefore represents an oncogenic key player. However, the biological mechanisms are still not fully understood. In previous studies we identified microRNA-21 as a STAT3 target gene with strong anti-apoptotic potential, suggesting that noncoding RNAs have an impact on the pathogenesis of human multiple myeloma. Here, we describe five long noncoding RNAs (lncRNAs) induced by IL-6-activated STAT3, which we named STAiRs. While STAiRs 1, 2 and 6 remain unprocessed in the nucleus and show myeloma-specific expression, STAiRs 15 and 18 are spliced and broadly expressed. Especially STAiR2 and STAiR18 are promising candidates. STAiR2 originates from the first intron of a tumor suppressor gene. Our data support a mutually exclusive expression of either STAiR2 or the functional tumor suppressor in INA-6 cells and thus a contribution of STAiR2 to tumorigenesis. Furthermore, STAiR18 was shown to be overexpressed in every tested tumor entity, indicating its global role in tumor pathogenesis. Taken together, our study reveals a number of STAT3-induced lncRNAs suggesting that the interplay between the coding and noncoding worlds represents a fundamental principle of STAT3-driven cancer development in multiple myeloma and beyond.

A Review on Recent Computational Methods for Predicting Noncoding RNAs

Noncoding RNAs (ncRNAs) play important roles in various cellular activities and diseases. In this paper, we presented a comprehensive review on computational methods for ncRNA prediction, which are generally grouped into four categories: (1) homology-based methods, that is, comparative methods involving evolutionarily conserved RNA sequences and structures, (2) de novo methods using RNA sequence and structure features, (3) transcriptional sequencing and assembling based methods, that is, methods designed for single and pair-ended reads generated from next-generation RNA sequencing, and (4) RNA family specific methods, for example, methods specific for microRNAs and long noncoding RNAs. In the end, we summarized the advantages and limitations of these methods and pointed out a few possible future directions for ncRNA prediction. In conclusion, many computational methods have been demonstrated to be effective in predicting ncRNAs for further experimental validation. They are critical in reducing the huge number of potential ncRNAs and pointing the community to high confidence candidates. In the future, high efficient mapping technology and more intrinsic sequence features (e.g., motif and k-mer frequencies) and structure features (e.g., minimum free energy, conserved stem-loop, or graph structures) are suggested to be combined with the next- and third-generation sequencing platforms to improve ncRNA prediction.

Maternal phthalate exposure promotes allergic airway inflammation over 2 generations through epigenetic modifications

BACKGROUND

Prenatal and early postnatal exposures to environmental factors are considered responsible for the increasing prevalence of allergic diseases. Although there is some evidence for allergy-promoting effects in children because of exposure to plasticizers, such as phthalates, findings of previous studies are inconsistent and lack mechanistic information.

OBJECTIVE

We investigated the effect of maternal phthalate exposure on asthma development in subsequent generations and their underlying mechanisms, including epigenetic alterations.

METHODS

Phthalate metabolites were measured within the prospective mother-child cohort Lifestyle and Environmental Factors and Their Influence on Newborns Allergy Risk (LINA) and correlated with asthma development in the children. A murine transgenerational asthma model was used to identify involved pathways.

RESULTS

In LINA maternal urinary concentrations of mono-n-butyl phthalate, a metabolite of butyl benzyl phthalate (BBP), were associated with an increased asthma risk in the children. Using a murine transgenerational asthma model, we demonstrate a direct effect of BBP on asthma severity in the offspring with a persistently increased airway inflammation up to the F2 generation. This disease-promoting effect was mediated by BBP-induced global DNA hypermethylation in CD4⁺ T cells of the offspring because treatment with a DNA-demethylating agent alleviated exacerbation of allergic airway inflammation. Thirteen transcriptionally downregulated genes linked to promoter or enhancer hypermethylation were identified. Among these, the GATA-3 repressor zinc finger protein 1 (Zfpm1) emerged as a potential mediator of the enhanced susceptibility for T_H2-driven allergic asthma.

CONCLUSION

These data provide strong evidence that maternal BBP exposure increases the risk for allergic airway inflammation in the offspring by modulating the expression of genes involved in T_H2 differentiation through epigenetic alterations.

The long noncoding RNA-ROR promotes the resistance of radiotherapy for human colorectal cancer cells by targeting the p53/miR-145 pathway

BACKGROUND AND AIM

Long intergenic noncoding RNAs (lincRNAs) have critical roles in elevating efficacy of anticancer therapy and tumor progression. Recent studies show that Regulator of Reprogramming (ROR) is aberrantly expressed in several types of cancer, including colorectal cancer (CRC). Radiotherapy is considered as a standard preoperative treatment. However, a considerable number of CRCs are resistant to radiotherapy. In this study, we evaluated the role of lincRNA-ROR in radiotherapy for CRC and detected the underlying molecular mechanism.

METHODS

Real-time polymerase chain reaction was employed to quantify the expression level of lincRNA-ROR in different CRC cell lines and tissue samples. Cell viability and apoptosis assays were used to confirm the radiotherapy-mediated effects by lincRNA-ROR altered expression. The direct impact of lincRNA-ROR on the expression of p53/miR-145 by loss-of-function and gain-of-function strategy was also analyzed. A xenograft mouse model was used to evaluate the role of linc-ROR in CRC treatment.

RESULTS

We discovered that lincRNA-ROR was upregulated in CRC cell lines and tissue samples. We further showed that knockdown of lincRNA-ROR enhanced the sensitivity to radiotherapy for CRC by inhibiting cell viability and promoting apoptosis. Activity of the p53/miR-145 pathway may help explain the role of lincRNA-ROR for stress-induced regulation in CRC therapy. Combined specific knockdown of lincRNA-ROR and radiotherapy treatment in xenograft model resulted in a significant reduction in the tumor growth.

CONCLUSION

LincRNA-ROR decreases sensitivity to radiotherapy via the negative regulation of p53/miR-145 and may represent a potential target for the treatment of CRC.

Long non-coding RNAs in human early embryonic development and their potential in ART

BACKGROUND

Human long non-coding RNAs (lncRNAs) are an emerging category of transcripts with increasingly documented functional roles during development. LncRNAs and roles during human early embryo development have recently begun to be unravelled.

OBJECTIVE AND RATIONALE

This review summarizes the most recent knowledge on lncRNAs and focuses on their expression patterns and role during early human embryo development and in pluripotent stem cells (PSCs). Public mRNA sequencing (mRNA-seq) data were used to illustrate these expression signatures.

SEARCH METHODS

The PubMed and EMBASE databases were first interrogated using specific terms, such as 'lncRNAs', to get an extensive overview on lncRNAs up to February 2016, and then using 'human lncRNAs' and 'embryo', 'development', or 'PSCs' to focus on lncRNAs involved in human embryo development or in PSC.Recently published RNA-seq data from human oocytes and pre-implantation embryos (including single-cell data), PSC and a panel of normal and malignant adult tissues were used to describe the specific expression patterns of some lncRNAs in early human embryos.

OUTCOMES

The existence and the crucial role of lncRNAs in many important biological phenomena in each branch of the life tree are now well documented. The number of identified lncRNAs is rapidly increasing and has already outnumbered that of protein-coding genes. Unlike small non-coding RNAs, a variety of mechanisms of action have been proposed for lncRNAs. The functional role of lncRNAs has been demonstrated in many biological and developmental processes, including cell pluripotency induction, X-inactivation or gene imprinting. Analysis of RNA-seq data highlights that lncRNA abundance changes significantly during human early embryonic development. This suggests that lncRNAs could represent candidate biomarkers for developing non-invasive tests for oocyte or embryo quality. Finally, some of these lncRNAs are also expressed in human cancer tissues, suggesting that reactivation of an embryonic lncRNA program may contribute to human malignancies.

WIDER IMPLICATIONS

LncRNAs are emerging potential key players in gene expression regulation. Analysis of RNA-seq data from human pre-implantation embryos identified lncRNA signatures that are specific to this critical step. We anticipate that further studies will show that these new transcripts are major regulators of embryo development. These findings might also be used to develop new tests/treatments for improving the pregnancy success rate in IVF procedures or for regenerative medicine applications involving PSC.

Evolution of the unspliced transcriptome

BACKGROUND

Despite their abundance, unspliced EST data have received little attention as a source of information on non-coding RNAs. Very little is know, therefore, about the genomic distribution of unspliced non-coding transcripts and their relationship with the much better studied regularly spliced products. In particular, their evolution has remained virtually unstudied.

RESULTS

We systematically study the evidence on unspliced transcripts available in EST annotation tracks for human and mouse, comprising 104,980 and 66,109 unspliced EST clusters, respectively. Roughly one third of these are located totally inside introns of known genes (TINs) and another third overlaps exonic regions (PINs). Eleven percent are "intergenic", far away from any annotated gene. Direct evidence for the independent transcription of many PINs and TINs is obtained from CAGE tag and chromatin data. We predict more than 2000 3'UTR-associated RNA candidates for each human and mouse. Fifteen to twenty percent of the unspliced EST cluster are conserved between human and mouse. With the exception of TINs, the sequences of unspliced EST clusters evolve significantly slower than genomic background. Furthermore, like spliced lincRNAs, they show highly tissue-specific expression patterns.

CONCLUSIONS

Unspliced long non-coding RNAs are an important, rapidly evolving, component of mammalian transcriptomes. Their analysis is complicated by their preferential association with complex transcribed loci that usually also harbor a plethora of spliced transcripts. Unspliced EST data, although typically disregarded in transcriptome analysis, can be used to gain insights into this rarely investigated transcriptome component. The frequently postulated connection between lack of splicing and nuclear retention and the surprising overlap of chromatin-associated transcripts suggests that this class of transcripts might be involved in chromatin organization and possibly other mechanisms of epigenetic control.

The Use of Three Long Non-Coding RNAs as Potential Prognostic Indicators of Astrocytoma

Long noncoding RNAs (lncRNAs) are pervasively transcribed and play a key role in tumorigenesis. The aim of the study was to determine the lncRNA expression profile in astrocytomas and to assess its potential clinical value. We performed a three-step analysis to establish the lncRNA profile for astrocytoma: a) the lncRNA expression was examined on 3 astrocytomas as well as 3 NATs (normal adjacent tissues) using the lncRNA microarray; b) the top-hits were validated in 40 astrocytomas (WHO grade II-IV) by quantitative real time-PCR (qRT-PCR); c) the hits with significant differences were re-evaluated using qRT-PCR in 90 astrocytomas. Finally, 7 lncRNAs were found to have a significantly different expression profile in astrocytoma samples compared to the NAT samples. Unsupervised clustering analysis further revealed the potential of the 7-lncRNA profile to differentiate between tumors and NAT samples. The upregulation of ENST00000545440 and NR_002809 was associated with advanced clinical stages of astrocytoma. Using Kaplan-Meier survival analysis, we showed that the low expression of BC002811 or XLOC_010967, or the high expression of NR_002809 was significantly associated with poor patient survival. Moreover, Cox proportional hazard regression analysis revealed that this prognostic impact was independent of other clinicopathological factors. Our results indicate that the lncRNA profile may be a potential prognostic biomarker for the prediction of post-surgical outcomes.

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes.

Comparison of splice sites reveals that long noncoding RNAs are evolutionarily well conserved

Large-scale RNA sequencing has revealed a large number of long mRNA-like transcripts (lncRNAs) that do not code for proteins. The evolutionary history of these lncRNAs has been notoriously hard to study systematically due to their low level of sequence conservation that precludes comprehensive homology-based surveys and makes them nearly impossible to align. An increasing number of special cases, however, has been shown to be at least as old as the vertebrate lineage. Here we use the conservation of splice sites to trace the evolution of lncRNAs. We show that >85% of the human GENCODE lncRNAs were already present at the divergence of placental mammals and many hundreds of these RNAs date back even further. Nevertheless, we observe a fast turnover of intron/exon structures. We conclude that lncRNA genes are evolutionary ancient components of vertebrate genomes that show an unexpected and unprecedented evolutionary plasticity. We offer a public web service (http://splicemap.bioinf.uni-leipzig.de) that allows to retrieve sets of orthologous splice sites and to produce overview maps of evolutionarily conserved splice sites for visualization and further analysis. An electronic supplement containing the ncRNA data sets used in this study is available at http://www.bioinf.uni-leipzig.de/publications/supplements/12-001.

The Landscape of long noncoding RNA classification

Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long noncoding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the noncoding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual unambiguous classification framework results in a number of challenges in the annotation and interpretation of noncoding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel the function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then, we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets.

Long non-coding RNA MALAT1 regulates hyperglycaemia induced inflammatory process in the endothelial cells

To examine whether the long non-coding RNA (lncRNA) metastasis associated lung adenocarcinoma transcript 1 (MALAT1) is altered in the endothelial cells in response to glucose and the significance of such alteration. We incubated human umbilical vein endothelial cells with media containing various glucose levels. We found an increase in MALAT1 expression peaking after 12 hrs of incubation in high glucose. This increase was associated with parallel increase in serum amyloid antigen 3 (SAA3), an inflammatory ligand and target of MALAT1 and was further accompanied by increase in mRNAs and proteins of inflammatory mediators, tumour necrosis factor alpha (TNF-α) and interleukin 6 (IL-6). Renal tissue from the diabetic animals showed similar changes. Such cellular alterations were prevented following MALAT1 specific siRNA transfection. Results of this study indicate that LncRNA MALAT1 regulates glucose-induced up-regulation of inflammatory mediators IL-6 and TNF-α through activation of SAA3. Identification of such novel mechanism may lead to the development of RNA-based therapeutics targeting MALAT1 for diabetes-induced micro and macro vascular complications.

Long non-coding RNAs differentially expressed between normal versus primary breast tumor tissues disclose converse changes to breast cancer-related protein-coding genes

Breast cancer, the second leading cause of cancer death in women, is a highly heterogeneous disease, characterized by distinct genomic and transcriptomic profiles. Transcriptome analyses prevalently assessed protein-coding genes; however, the majority of the mammalian genome is expressed in numerous non-coding transcripts. Emerging evidence supports that many of these non-coding RNAs are specifically expressed during development, tumorigenesis, and metastasis. The focus of this study was to investigate the expression features and molecular characteristics of long non-coding RNAs (lncRNAs) in breast cancer. We investigated 26 breast tumor and 5 normal tissue samples utilizing a custom expression microarray enclosing probes for mRNAs as well as novel and previously identified lncRNAs. We identified more than 19,000 unique regions significantly differentially expressed between normal versus breast tumor tissue, half of these regions were non-coding without any evidence for functional open reading frames or sequence similarity to known proteins. The identified non-coding regions were primarily located in introns (53%) or in the intergenic space (33%), frequently orientated in antisense-direction of protein-coding genes (14%), and commonly distributed at promoter-, transcription factor binding-, or enhancer-sites. Analyzing the most diverse mRNA breast cancer subtypes Basal-like versus Luminal A and B resulted in 3,025 significantly differentially expressed unique loci, including 682 (23%) for non-coding transcripts. A notable number of differentially expressed protein-coding genes displayed non-synonymous expression changes compared to their nearest differentially expressed lncRNA, including an antisense lncRNA strongly anticorrelated to the mRNA coding for histone deacetylase 3 (HDAC3), which was investigated in more detail. Previously identified chromatin-associated lncRNAs (CARs) were predominantly downregulated in breast tumor samples, including CARs located in the protein-coding genes for CALD1, FTX, and HNRNPH1. In conclusion, a number of differentially expressed lncRNAs have been identified with relation to cancer-related protein-coding genes.