An integrative transcriptomics approach identifies miR-503 as a candidate master regulator of the estrogen response in MCF-7 breast cancer cells

microRNAs as Biomarkers of Breast Cancer

Breast cancer (BC) is the most common type of cancer found in women. Detection of this cancer at an early stage is essential for effective treatment and a favorable prognosis. Potential early breast cancer biomarkers useful for diagnosing these tumors are microRNAs. These are small single-stranded RNA chains that can regulate the post-transcriptional expression of many different oncogenes. Cancer cells contain miRNAs that play a special role in the etiology of cancer development. The role of microRNAs in the initiation and development of breast cancer gives us great hope for the creation of molecular tools for early cancer detection. MicroRNAs are characterized by a high stability due to RNase, which protects them from degradation and enables their detection in various biological fluids. Researchers have described multiple serum microRNA signatures useful for detecting breast cancer. This review discusses the importance and potential usefulness of microRNAs in detecting breast cancer at an early stage, predicting the course of the disease, and assessing the effectiveness of treatment.

A transcriptomic biomarker predictive of cell proliferation for use in adverse outcome pathway-informed testing and assessment

High-throughput transcriptomics (HTTr) is increasingly being used to identify molecular targets of chemicals that can be linked to adverse outcomes. Cell proliferation (CP) is an important key event in chemical carcinogenesis. Here, we describe the construction and characterization of a gene expression biomarker that is predictive of the CP status in human and rodent tissues. The biomarker was constructed from 30 genes known to be increased in expression in prostate cancers relative to surrounding tissues and in cycling human MCF-7 cells after estrogen receptor (ER) agonist exposure. Using a large compendium of gene expression profiles to test utility, the biomarker could identify increases in CP in (i) 308 out of 367 tumor vs. normal surrounding tissue comparisons from 6 human organs, (ii) MCF-7 cells after activation of ER, (iii) after partial hepatectomy in mice and rats, and (iv) the livers of mice and rats after exposure to nongenotoxic hepatocarcinogens. The biomarker identified suppression of CP (i) under conditions of p53 activation by DNA damaging agents in human cells, (ii) in human A549 lung cells exposed to therapeutic anticancer kinase inhibitors (dasatinib, nilotnib), and (iii) in the mouse liver when comparing high levels of CP at birth to the low background levels in the adult. The responses using the biomarker were similar to those observed using conventional markers of CP including PCNA, Ki67, and BrdU labeling. The CP biomarker will be a useful tool for interpretation of HTTr data streams to identify CP status after exposure to chemicals in human cells or in rodent tissues.

ZNF217: An Oncogenic Transcription Factor and Potential Therapeutic Target for Multiple Human Cancers

Zinc finger protein 217 (ZNF217) is one of the well-researched members of the Krüppel-like factor transcription factor family. ZNF217 possesses a characteristic structure of zinc finger motifs and plays a crucial role in regulating the biological activities of cells. Recent findings have revealed that ZNF217 is strongly associated with multiple aspects of cancer progression, impacting patient prognosis. Notably, ZNF217 is subject to regulation by non-coding RNAs, suggesting the potential for targeted manipulation of such RNAs as a robust therapeutic avenue for managing cancer in the future. The main purpose of this article is to provide a detailed examination of the role of ZNF217 in human malignant tumors and the regulation of its expression, and to offer new perspectives for cancer treatment.

The EstroGene Database Reveals Diverse Temporal, Context-Dependent, and Bidirectional Estrogen Receptor Regulomes in Breast Cancer

As one of the most successful cancer therapeutic targets, estrogen receptor-α (ER/ESR1) has been extensively studied over the past few decades. Sequencing technological advances have enabled genome-wide analysis of ER action. However, comparison of individual studies is limited by different experimental designs, and few meta-analyses are available. Here, we established the EstroGene database through unified processing of data from 246 experiments including 136 transcriptomic, cistromic, and epigenetic datasets focusing on estradiol (E2)-triggered ER activation across 19 breast cancer cell lines. A user-friendly browser (https://estrogene.org/) was generated for multiomic data visualization involving gene inquiry under user-defined experimental conditions and statistical thresholds. Notably, annotation of metadata associated with public datasets revealed a considerable lack of experimental details. Comparison of independent RNA-seq or ER ChIP-seq data with the same design showed large variability and only strong effects could be consistently detected. Temporal estrogen response metasignatures were defined, and the association of E2 response rate with temporal transcriptional factors, chromatin accessibility, and heterogeneity of ER expression was evaluated. Unexpectedly, harmonizing 146 E2-induced transcriptomic datasets uncovered a subset of genes harboring bidirectional E2 regulation, which was linked to unique transcriptional factors and highly associated with immune surveillance in the clinical setting. Furthermore, the context dependent E2 response programs were characterized in MCF7 and T47D cell lines, the two most frequently used models in the EstroGene database. Collectively, the EstroGene database provides an informative and practical resource to the cancer research community to uniformly evaluate key reproducible features of ER regulomes and unravels modes of ER signaling.

SIGNIFICANCE

A resource database integrating 246 publicly available ER profiling datasets facilitates meta-analyses and identifies estrogen response temporal signatures, a bidirectional program, and model-specific biases.

Non-Coding RNAs Modulating Estrogen Signaling and Response to Endocrine Therapy in Breast Cancer

The largest part of human DNA is transcribed into RNA that does not code for proteins. These non-coding RNAs (ncRNAs) are key regulators of protein-coding gene expression and have been shown to play important roles in health, disease and therapy response. Today, endocrine therapy of ERα-positive breast cancer (BC) is a successful treatment approach, but resistance to this therapy is a major clinical problem. Therefore, a deeper understanding of resistance mechanisms is important to overcome this resistance. An increasing amount of evidence demonstrate that ncRNAs affect the response to endocrine therapy. Thus, ncRNAs are considered versatile biomarkers to predict or monitor therapy response. In this review article, we intend to give a summary and update on the effects of microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) on estrogen signaling in BC cells, this pathway being the target of endocrine therapy, and their role in therapy resistance. For this purpose, we reviewed articles on these topics listed in the PubMed database. Finally, we provide an assessment regarding the clinical use of these ncRNA types, particularly their circulating forms, as predictive BC biomarkers and their potential role as therapy targets to overcome endocrine resistance.

Krüppel-like factor 9 (KLF9) links hormone dysregulation and circadian disruption to breast cancer pathogenesis

BACKGROUND

Circadian disruption is an emerging driver of breast cancer (BCa), with epidemiological studies linking shift work and chronic jet lag to increased BCa risk. Indeed, several clock genes participate in the gating of mitotic entry, regulation of DNA damage response, and epithelial-to-mesenchymal transition, thus impacting BCa etiology. Dysregulated estrogen (17β-estradiol, E2) and glucocorticoid (GC) signaling prevalent in BCa may further contribute to clock desynchrony by directly regulating the expression and cycling dynamics of genes comprising the local breast oscillator. In this study, we investigated the tumor suppressor gene, Krüppel-like factor 9 (KLF9), as an important point of crosstalk between hormone signaling and the circadian molecular network, and further examine its functional role in BCa.

METHODS

Through meta-analysis of publicly available RNA- and ChIP-sequencing datasets from BCa tumor samples and cell lines, and gene expression analysis by RT-qPCR and enhancer- reporter assays, we elucidated the molecular mechanism behind the clock and hormone regulation of KLF9. Lentiviral knockdown and overexpression of KLF9 in three distinct breast epithelial cell lines (MCF10A, MCF7 and MDA-MB-231) was generated to demonstrate the role of KLF9 in orthogonal assays on breast epithelial survival, proliferation, apoptosis, and migration.

RESULTS

We determined that KLF9 is a direct GC receptor target in mammary epithelial cells, and that induction is likely mediated through coordinate transcriptional activation from multiple GC-responsive enhancers in the KLF9 locus. More interestingly, rhythmic expression of KLF9 in MCF10A cells was abolished in the highly aggressive MDA-MB-231 line. In turn, forced expression of KLF9 altered the baseline and GC/E2-responsive expression of several clock genes, indicating that KLF9 may function as a regulator of the core clock machinery. Characterization of the role of KLF9 using complementary cancer hallmark assays in the context of the hormone-circadian axis revealed that KLF9 plays a tumor-suppressive role in BCa regardless of molecular subtype. KLF9 potentiated the anti-tumorigenic effects of GC in E2 receptor + luminal MCF7 cells, while it restrained GC-enhanced oncogenicity in triple-negative MCF10A and MDA-MB-231 cells.

CONCLUSIONS

Taken together, our findings support that dysregulation of KLF9 expression and oscillation in BCa impinges on circadian network dynamics, thus ultimately affecting the BCa oncogenic landscape.

EstroGene database reveals diverse temporal, context-dependent and directional estrogen receptor regulomes in breast cancer

As one of the most successful cancer therapeutic targets, estrogen receptor-α (ER/ESR1) has been extensively studied in decade-long. Sequencing technological advances have enabled genome-wide analysis of ER action. However, reproducibility is limited by different experimental design. Here, we established the EstroGene database through centralizing 246 experiments from 136 transcriptomic, cistromic and epigenetic datasets focusing on estradiol-treated ER activation across 19 breast cancer cell lines. We generated a user-friendly browser ( https://estrogene.org/ ) for data visualization and gene inquiry under user-defined experimental conditions and statistical thresholds. Notably, documentation-based meta-analysis revealed a considerable lack of experimental details. Comparison of independent RNA-seq or ER ChIP-seq data with the same design showed large variability and only strong effects could be consistently detected. We defined temporal estrogen response metasignatures and showed the association with specific transcriptional factors, chromatin accessibility and ER heterogeneity. Unexpectedly, harmonizing 146 transcriptomic analyses uncovered a subset of E2-bidirectionally regulated genes, which linked to immune surveillance in the clinical setting. Furthermore, we defined context dependent E2 response programs in MCF7 and T47D cell lines, the two most frequently used models in the field. Collectively, the EstroGene database provides an informative resource to the cancer research community and reveals a diverse mode of ER signaling.

The Intricate Interplay between the ZNF217 Oncogene and Epigenetic Processes Shapes Tumor Progression

The oncogenic transcription factor ZNF217 orchestrates several molecular signaling networks to reprogram integrated circuits governing hallmark capabilities within cancer cells. High levels of ZNF217 expression provide advantages to a specific subset of cancer cells to reprogram tumor progression, drug resistance and cancer cell plasticity. ZNF217 expression level, thus, provides a powerful biomarker of poor prognosis and a predictive biomarker for anticancer therapies. Cancer epigenetic mechanisms are well known to support the acquisition of hallmark characteristics during oncogenesis. However, the complex interactions between ZNF217 and epigenetic processes have been poorly appreciated. Deregulated DNA methylation status at ZNF217 locus or an intricate cross-talk between ZNF217 and noncoding RNA networks could explain aberrant ZNF217 expression levels in a cancer cell context. On the other hand, the ZNF217 protein controls gene expression signatures and molecular signaling for tumor progression by tuning DNA methylation status at key promoters by interfering with noncoding RNAs or by refining the epitranscriptome. Altogether, this review focuses on the recent advances in the understanding of ZNF217 collaboration with epigenetics processes to orchestrate oncogenesis. We also discuss the exciting burgeoning translational medicine and candidate therapeutic strategies emerging from those recent findings connecting ZNF217 to epigenetic deregulation in cancer.

Premenopausal and postmenopausal women during the COVID-19 pandemic

The current global COVID-19 mortality rate is estimated to be around 3.4%; however, it is dependent on age, sex, and comorbidities. Epidemiological evidence shows gender disparities in COVID-19 severity and fatality, with non-menopausal females having milder severity and better outcomes than age-matched males. However, the difference vanishes when comparing postmenopausal women with age-matched men. It has been suggested that, to some extent, this is due to the protective role of female hormones, such as anti-Müllerian hormone and oestradiol (E2), in non-menopausal women. Oestrogens have been hypothesized to be crucial in modulating viral infection and the progression of the disease via an action on immune/inflammatory responses and angiotensin-converting enzyme type 2 expression. Hence, the most likely explanation is that, because the levels of oestrogen in females after menopause decrease, oestrogen no longer offers a beneficial effect as seen in younger females. The COVID-19 pandemic has highlighted the serious negative effects arising from the state of E2 deficiency. Therefore, hormone replacement therapy gains further support as the damaging effect of the decline in ovarian function affects many biological systems, and recently with the COVID-19 pandemic, oestrogen's vital role within the immune system has become quite clear. However, additional clinical investigations regarding hormone replacement therapy are urgently needed to further verify the protective and therapeutic effects of E2 on menopausal women with COVID-19.

Are sex hormones promising candidates to explain sex disparities in the COVID-19 pandemic?

Emerging evidence suggests that the novel Coronavirus disease-2019 (COVID-19) is deadlier for men than women both in China and in Europe. Male sex is a risk factor for COVID-19 mortality. The meccanisms underlying the reduced morbidity and lethality in women are currently unclear, even though hypotheses have been posed (Brandi and Giustina in Trends Endocrinol Metab. 31:918-27, 2020). This article aims to describe the role of sex hormones in sex- and gender-related fatality of COVID-19. We discuss the possibility that potential sex-specific mechanisms modulating the course of the disease include both the androgen- and the estrogen-response cascade. Sex hormones regulate the respiratory function, the innate and adaptive immune responses, the immunoaging, the cardiovascular system, and the entrance of the virus in the cells. Recommendations for the future government policies and for the management of COVID-19 patients should include a dimorphic approach for males and females. As the estrogen receptor signaling appears critical for protection in women, more studies are needed to translate the basic knowledge into clinical actions. Understanding the etiological bases of sexual dimorphism in COVID-19 could help develop more effective strategies in individual patients in both sexes, including designing a good vaccine.

A microRNA Cluster Controls Fat Cell Differentiation and Adipose Tissue Expansion By Regulating SNCG

The H19X-encoded miR-424(322)/503 cluster regulates multiple cellular functions. Here, it is reported for the first time that it is also a critical linchpin of fat mass expansion. Deletion of this miRNA cluster in mice results in obesity, while increasing the pool of early adipocyte progenitors and hypertrophied adipocytes. Complementary loss and gain of function experiments and RNA sequencing demonstrate that miR-424(322)/503 regulates a conserved genetic program involved in the differentiation and commitment of white adipocytes. Mechanistically, it is demonstrated that miR-424(322)/503 targets γ-Synuclein (SNCG), a factor that mediates this program rearrangement by controlling metabolic functions in fat cells, allowing adipocyte differentiation and adipose tissue enlargement. Accordingly, diminished miR-424(322) in mice and obese humans co-segregate with increased SNCG in fat and peripheral blood as mutually exclusive features of obesity, being normalized upon weight loss. The data unveil a previously unknown regulatory mechanism of fat mass expansion tightly controlled by the miR-424(322)/503 through SNCG.

Roles of steroid receptors in the lung and COVID-19

COVID-19 symptoms and mortality are largely due to its devastating effects in the lungs. The disease is caused by the SARS (Severe Acute Respiratory Syndrome)-CoV-2 coronavirus, which requires host cell proteins such as ACE2 (angiotensin-converting enzyme 2) and TMPRSS2 (transmembrane serine protease 2) for infection of lung epithelia. The expression and function of the steroid hormone receptor family is important in many aspects that impact on COVID-19 effects in the lung - notably lung development and function, the immune system, and expression of TMPRSS2 and ACE2. This review provides a brief summary of current knowledge on the roles of the steroid hormone receptors [androgen receptor (AR), glucocorticoid receptor (GR), progesterone receptor (PR), mineralocorticoid receptor (MR) and oestrogen receptor (ER)] in the lung, their effects on host cell proteins that facilitate SARS-CoV-2 uptake, and provides a snapshot of current clinical trials investigating the use of steroid receptor (SR) ligands to treat COVID-19.

Estrogen deficiency during puberty affects the expression of microRNA30a and microRNA503 in the mandibular condyle

BACKGROUND

The aim of this study was investigated if estrogen deficiency during puberty affects the expression of miRNA30a and miRNA503 in maxillary and mandibular growth centers, and also evaluated if ERα and ERβ are correlated with miRNA30a and miRNA503 expressions.

METHODS

Samples from 12 female Wistar rats randomized into experimental group (OVX) and control group (SHAM). At an age of 45 days animals were euthanized for miRNA expression analyses. RT-qPCR was performed to determine miRNA30a and miRNA503 expression in growth sites: midpalatal suture, condyle, mandibular angle, symphysis/parasymphysis and coronoid process. The data was carried out using the parametric tests at 5% of significance level.

RESULTS

miRNA 30a and miRNA503 presented higher levels in the condylar site in SHAM group when compared with OVX (p = 0.002 and p = 0.020, respectively). In the growth centers, a statistical significant difference was observed only for miRNA30a (p = 0.004), when compared mandibular angle with condyle the in OVX group (p = 0.001). A strong positive correlation between miRNA503 and ERα in the condyle of OVX group was observed (r = 0.90; p = 0.039 and it also between miRNA503 and ERβ in the coronoid process of the OVX group (r = 0.88; p = 0.05).

CONCLUSION

The results suggested that estrogen regulates specific miRNAs in maxillary and mandibular growth centers, which may participate in posttranscriptional regulation of estrogen-regulated genes.

Sex-Specific MicroRNAs in Neurovascular Units in Ischemic Stroke

Accumulating evidence pinpoints sex differences in stroke incidence, etiology and outcome. Therefore, more understanding of the sex-specific mechanisms that lead to ischemic stroke and aggravation of secondary damage after stroke is needed. Our current mechanistic understanding of cerebral ischemia states that endothelial quiescence in neurovascular units (NVUs) is a major physiological parameter affecting the cellular response to neuron, astrocyte and vascular smooth muscle cell (VSMC) injury. Although a hallmark of the response to injury in these cells is transcriptional activation, noncoding RNAs such as microRNAs exhibit cell-type and context dependent regulation of gene expression at the post-transcriptional level. This review assesses whether sex-specific microRNA expression (either derived from X-chromosome loci following incomplete X-chromosome inactivation or regulated by estrogen in their biogenesis) in these cells controls NVU quiescence, and as such, could differentiate stroke pathophysiology in women compared to men. Their adverse expression was found to decrease tight junction affinity in endothelial cells and activate VSMC proliferation, while their regulation of paracrine astrocyte signaling was shown to neutralize sex-specific apoptotic pathways in neurons. As such, these microRNAs have cell type-specific functions in astrocytes and vascular cells which act on one another, thereby affecting the cell viability of neurons. Furthermore, these microRNAs display actual and potential clinical implications as diagnostic and prognostic biomarkers in ischemic stroke and in predicting therapeutic response to antiplatelet therapy. In conclusion, this review improves the current mechanistic understanding of the molecular mechanisms leading to ischemic stroke in women and highlights the clinical promise of sex-specific microRNAs as novel diagnostic biomarkers for (silent) ischemic stroke.

ZNF217: the cerberus who fails to guard the gateway to lethal malignancy

The aberrant expression of the zinc finger protein 217 (ZNF217) promotes multiple malignant phenotypes, such as replicative immortality, maintenance of proliferation, malignant heterogeneity, metastasis, and cell death resistance, via diverse mechanisms, including transcriptional activation, mRNA N⁶-methyladenosine (m⁶A) regulation, and protein interactions. The induction of these cellular processes by ZNF217 leads to therapeutic resistance and patients' poor outcomes. However, few ZNF217 related clinical applications or trials, have been reported. Moreover, looming observations about ZNF217 roles in m⁶A regulation and cancer immune response triggered significant attention while lacking critical evidence. Thus, in this review, we revisit the literature about ZNF217 and emphasize its importance as a prognostic biomarker for early prevention and as a therapeutic target.

TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis

Motivation

The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)–mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate detailed networks from longitudinal miRNA–mRNA datasets.

Results

We present TimiRGeN, an R package that uses time point-based differential expression results to identify miRNA–mRNA interactions influencing signaling pathways of interest. miRNA–mRNA interactions can be visualized in R or exported to PathVisio or Cytoscape. The output can be used for hypothesis generation and directing in vitro or further in silico work such as GRN construction.

Availability and implementation

TimiRGeN is available for download on Bioconductor (https://bioconductor.org/packages/TimiRGeN) and requires R v4.0.2 or newer and BiocManager v3.12 or newer.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Looming Effects of Estrogen in Covid-19: A Rocky Rollout

In the face of the Covid-19 pandemic, an intensive number of studies have been performed to understand in a deeper way the mechanisms behind better or worse clinical outcomes. Epidemiologically, men subjects are more prone to severe acute respiratory syndrome-coronavirus type 2 (SARS-CoV-2) infections than women, with a similar scenario being also stated to the previous coronavirus diseases, namely, SARS-CoV in 2003 and Middle East Respiratory Syndrome coronavirus diseases (MERS-CoV) in 2012. In addition, and despite that aging is regarded as an independent risk factor for the severe form of the disease, even so, women protection is evident. In this way, it has been expected that sex hormones are the main determinant factors in gender differences, with the immunomodulatory effects of estrogen in different viral infections, chiefly in Covid-19, attracting more attention as it might explain the case-fatality rate and predisposition of men for Covid-19 severity. Here, we aim to provide a mini-review and an overview on the protective effects of estrogen in Covid-19. Different search strategies were performed including Scopus, Web of Science, Medline, Pubmed, and Google Scholar database to find relative studies. Findings of the present study illustrated that women have a powerful immunomodulating effect against Covid-19 through the effect of estrogen. This study illustrates that estrogens have noteworthy anti-inflammatory and immuno-modulatory effects in Covid-19. Also, estrogen hormone reduces SARS-CoV-2 infectivity through modulation of pro-inflammatory signaling pathways. This study highlighted the potential protective effect of estrogen against Covid-19 and recommended for future clinical trial and prospective studies to elucidate and confirm this protective effect.

LncRNA PVT1 promotes cervical cancer progression by sponging miR-503 to upregulate ARL2 expression

Cervical cancer (CC) is a huge threat to the health of women worldwide. Long non-coding RNA plasmacytoma variant translocation 1 gene (PVT1) was proved to be associated with the development of diverse human cancers, including CC. Nevertheless, the exact mechanism of PVT1 in CC progression remains unclear. Levels of PVT1, microRNA-503 (miR-503), and ADP ribosylation factor-like protein 2 (ARL2) were measured by quantitative reverse transcription-polymerase chain reaction or western blot assay. 3-(4,5)-Dimethylthiazole-2-y1)-2,5-biphenyl tetrazolium bromide (MTT) and flow cytometry were used to examine cell viability and apoptosis, respectively. For migration and invasion detection, transwell assay was performed. The interaction between miR-503 and PVT1 or ARL2 was shown by dual luciferase reporter assay. A nude mouse model was constructed to clarify the role of PVT1 in vivo. PVT1 and ARL2 expressions were increased, whereas miR-503 expression was decreased in CC tissues and cells. PVT1 was a sponge of miR-503, and miR-503 targeted ARL2. PVT1 knockdown suppressed proliferation, migration, and invasion of CC cells, which could be largely reverted by miR-503 inhibitor. In addition, upregulated ARL2 could attenuate si-PVT1-mediated anti-proliferation and anti-metastasis effects on CC cells. Silenced PVT1 also inhibited CC tumor growth in vivo. PVT1 knockdown exerted tumor suppressor role in CC progression via the miR-503/ARL2 axis, at least in part.

The microRNA-424/503 cluster: A master regulator of tumorigenesis and tumor progression with paradoxical roles in cancer

MicroRNAs (miRNAs) are a group of non-coding RNAs that play a crucial role in post-transcriptional gene regulation and act as indispensable mediators in several critical biological processes, including tumorigenesis, tissue homeostasis, and regeneration. MiR-424 and miR-503 are intragenic miRNAs that are clustered on human chromosome Xq26.3. Previous studies have reported that both miRNAs are dysregulated and play crucial but paradoxical roles in tumor initiation and progression, involving different target genes and molecular pathways. Moreover, these two miRNAs are concomitantly expressed in several cancer cells, indicating a coordinating function as a cluster. In this review, the roles and regulatory mechanisms of miR-424, miR-503, and miR-424/503 cluster are summarized in different types of cancers.

The Role of Long Non-Coding RNA NNT-AS1 in Neoplastic Disease

Simple Summary

Nicotinamide nucleotide transhydrogenase-antisense 1 (NNT-AS1), which is a newly-discovered long non-coding RNA (lncRNA), has been found to be dysregulated in a variety of neoplastic diseases. With the accumulation of studies on NNT-AS1 in recent years, the mechanism of NNT-AS1 and its significance for tumor occurrence and progression are constantly being updated and improved. Thus, this paper aims to summarize the abnormal expression of NNT-AS1 and its prognostic values in different neoplastic diseases. In addition, the detailed competing endogenous RNA networks and subsequent biology behaviors, as well as the role of NNT-AS1 in mediating cisplatin resistance are revealed in this paper. This review not only summarizes the past research of NNT-AS1, but also provides some ideas for future research in this field.

Abstract

Studies have shown that non-coding RNAs (ncRNAs), especially long non-coding RNAs (lncRNAs), play an important regulatory role in the occurrence and development of human cancer. Nicotinamide nucleotide transhydrogenase-antisense 1 (NNT-AS1) is a newly-discovered cytoplasmic lncRNA. Many studies have shown that it has abnormally-high expression levels in malignant tumors, but there are also a few studies that have reported low expression levels of NNT-AS1 in gastric cancer, breast cancer, and ovarian cancer. At present, the regulatory mechanism of NNT-AS1 as a miRNA sponge, which may be an important reason affecting tumor cell proliferation, invasion, metastasis, and apoptosis is being studied in-depth. In addition, NNT-AS1 has been found to be related to cisplatin resistance. In this review, we summarize the abnormal expression of NNT-AS1 in a variety of neoplastic diseases and its diagnostic and prognostic value, and we explain the mechanism by which NNT-AS1 regulates cancer progression by competing with miRNAs. In addition, we also reveal the correlation between NNT-AS1 and cisplatin resistance and the potential clinical applications of NNT-AS1.

SARS-CoV-2 and the possible connection to ERs, ACE2, and RAGE: Focus on susceptibility factors

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has provoked major stresses on the health-care systems of several countries, and caused the death of more than a quarter of a million people globally, mainly in the elderly population with preexisting pathologies. Previous studies with coronavirus (SARS-CoV) point to gender differences in infection and disease progression with increased susceptibility in male patients, indicating that estrogens may be associated with physiological protection against the coronavirus. Therefore, the objectives of this work are threefold. First, we aim to summarize the SARS-CoV-2 infection pathway and the roles both the virus and patient play in COVID-19 (Coronavirus disease 2019) progression, clinical symptomatology, and mortality. Second, we detail the effect estrogen has on viral infection and host infection response, including its role in both the regulation of key viral receptor expression and the mediation of inflammatory activity. Finally, we describe how ERs (estrogen receptors) and RAGE (receptor for advanced glycation end-products) play a critical role in metabolic pathways, which we envisage could maintain a close interplay with SARS-CoV and COVID-19 mortality rates, despite a current lack of research directly determining how. Taken together, we present the current state of the field regarding SARS-CoV-2 research and illuminate where research is needed to better define the role both estrogen and metabolic comorbidities have in the COVID-19 disease state, which can be key in screening potential therapeutic options as the search for effective treatments continue.

Metabolic labeling of RNA using multiple ribonucleoside analogs enables the simultaneous evaluation of RNA synthesis and degradation rates

Gene expression is determined by a balance between RNA synthesis and RNA degradation. To elucidate the underlying regulatory mechanisms and principles of this, simultaneous measurements of RNA synthesis and degradation are required. Here, we report the development of “Dyrec-seq,” which uses 4-thiouridine and 5-bromouridine to simultaneously quantify RNA synthesis and degradation rates. Dyrec-seq enabled the quantification of RNA synthesis and degradation rates of 4702 genes in HeLa cells. Functional enrichment analysis showed that the RNA synthesis and degradation rates of genes are actually determined by the genes’ biological functions. A comparison of theoretical and experimental analyses revealed that the amount of RNA is determined by the ratio of RNA synthesis to degradation rates, whereas the rapidity of responses to external stimuli is determined only by the degradation rate. This study emphasizes that not only RNA synthesis but also RNA degradation is important in shaping gene expression patterns.

Ligand dependent gene regulation by transient ERα clustered enhancers

Unliganded Estrogen receptor alpha (ERα) has been implicated in ligand-dependent gene regulation. Upon ligand exposure, ERα binds to several EREs relatively proximal to the pre-marked, unliganded ERα-bound sites and affects transient but robust gene expression. However, the underlying mechanisms are not fully understood. Here we demonstrate that upon ligand stimulation, persistent sites interact extensively, via chromatin looping, with the proximal transiently ERα-bound sites, forming Ligand Dependent ERα Enhancer Cluster in 3D (LDEC). The E2-target genes are regulated by these clustered enhancers but not by the H3K27Ac super-enhancers. Further, CRISPR-based deletion of TFF1 persistent site disrupts the formation of its LDEC resulting in the loss of E2-dependent expression of TFF1 and its neighboring genes within the same TAD. The LDEC overlap with nuclear ERα condensates that coalesce in a ligand and persistent site dependent manner. Furthermore, formation of clustered enhancers, as well as condensates, coincide with the active phase of signaling and their later disappearance results in the loss of gene expression even though persistent sites remain bound by ERα. Our results establish, at TFF1 and NRIP1 locus, a direct link between ERα condensates, ERα enhancer clusters, and transient, but robust, gene expression in a ligand-dependent fashion.

A rank-based algorithm of differential expression analysis for small cell line data with statistical control

To detect differentially expressed genes (DEGs) in small-scale cell line experiments, usually with only two or three technical replicates for each state, the commonly used statistical methods such as significance analysis of microarrays (SAM), limma and RankProd (RP) lack statistical power, while the fold change method lacks any statistical control. In this study, we demonstrated that the within-sample relative expression orderings (REOs) of gene pairs were highly stable among technical replicates of a cell line but often widely disrupted after certain treatments such like gene knockdown, gene transfection and drug treatment. Based on this finding, we customized the RankComp algorithm, previously designed for individualized differential expression analysis through REO comparison, to identify DEGs with certain statistical control for small-scale cell line data. In both simulated and real data, the new algorithm, named CellComp, exhibited high precision with much higher sensitivity than the original RankComp, SAM, limma and RP methods. Therefore, CellComp provides an efficient tool for analyzing small-scale cell line data.

Biotransformation of the Mycotoxin Zearalenone to its Metabolites Hydrolyzed Zearalenone (HZEN) and Decarboxylated Hydrolyzed Zearalenone (DHZEN) Diminishes its Estrogenicity In Vitro and In Vivo

Zearalenone (ZEN)-degrading enzymes are a promising strategy to counteract the negative effects of this mycotoxin in livestock. The reaction products of such enzymes need to be thoroughly characterized before technological application as a feed additive can be envisaged. Here, we evaluated the estrogenic activity of the metabolites hydrolyzed zearalenone (HZEN) and decarboxylated hydrolyzed zearalenone (DHZEN) formed by hydrolysis of ZEN by the zearalenone-lactonase Zhd101p. ZEN, HZEN, and DHZEN were tested in two in vitro models, the MCF-7 cell proliferation assay (0.01–500 nM) and an estrogen-sensitive yeast bioassay (1–10,000 nM). In addition, we compared the impact of dietary ZEN (4.58 mg/kg) and equimolar dietary concentrations of HZEN and DHZEN on reproductive tract morphology as well as uterine mRNA and microRNA expression in female piglets (n = 6, four weeks exposure). While ZEN increased cell proliferation and reporter gene transcription, neither HZEN nor DHZEN elicited an estrogenic response, suggesting that these metabolites are at least 50–10,000 times less estrogenic than ZEN in vitro. In piglets, HZEN and DHZEN did not increase vulva size or uterus weight. Moreover, RNA transcripts altered upon ZEN treatment (EBAG9, miR-135a-5p, miR-187-3p and miR-204-5p) were unaffected by HZEN and DHZEN. Our study shows that both metabolites exhibit markedly reduced estrogenicity in vitro and in vivo, and thus provides an important basis for further evaluation of ZEN-degrading enzymes.

Impulse model-based differential expression analysis of time course sequencing data

Temporal changes to the concentration of molecular species such as mRNA, which take place in response to various environmental cues, can often be modeled as simple continuous functions such as a single pulse (impulse) model. The simplicity of such functional representations can provide an improved performance on fundamental tasks such as noise reduction, imputation and differential expression analysis. However, temporal gene expression profiles are often studied with models that treat time as a categorical variable, neglecting the dependence between time points. Here, we present ImpulseDE2, a framework for differential expression analysis that combines the power of the impulse model as a continuous representation of temporal responses along with a noise model tailored specifically to sequencing data. We compare the simple categorical models to ImpulseDE2 and to other continuous models based on natural cubic splines and demonstrate the utility of the continuous approach for studying differential expression in time course sequencing experiments. A unique feature of ImpulseDE2 is the ability to distinguish permanently from transiently up- or down-regulated genes. Using an in vitro differentiation dataset, we demonstrate that this gene classification scheme can be used to highlight distinct transcriptional programs that are associated with different phases of the differentiation process.

MicroRNAs in porcine uterus and serum are affected by zearalenone and represent a new target for mycotoxin biomarker discovery

The mycotoxin zearalenone (ZEN) poses a risk to animal health because of its estrogenic effects. Diagnosis of ZEN-induced disorders remains challenging due to the lack of appropriate biomarkers. In this regard, circulating microRNAs (small non-coding RNAs) have remarkable potential, as they can serve as indicators for pathological processes in tissue. Thus, we combined untargeted and targeted transcriptomics approaches to investigate the effects of ZEN on the microRNA expression in porcine uterus, jejunum and serum, respectively. To this end, twenty-four piglets received uncontaminated feed (Control) or feed containing 0.17 mg/kg ZEN (ZEN low), 1.46 mg/kg ZEN (ZEN medium) and 4.58 mg/kg ZEN (ZEN high). After 28 days, the microRNA expression in the jejunum remained unaffected, while significant changes in the uterine microRNA profile were observed. Importantly, 14 microRNAs were commonly and dose-dependently affected in both the ZEN medium and ZEN high group, including microRNAs from the miR-503 cluster (i.e. ssc-miR-424-5p, ssc-miR-450a, ssc-miR-450b-5p, ssc-miR-450c-5p, ssc-miR-503 and ssc-miR-542-3p). Predicted target genes for those microRNAs are associated with regulation of gene expression and signal transduction (e.g. cell cycle). Although the effects in serum were less pronounced, receiver operating characteristic analysis revealed that several microRNA ratios were able to discriminate properly between non-exposed and ZEN-exposed pigs (e.g. ssc-miR-135a-5p/ssc-miR-432-5p, ssc-miR-542-3p/ssc-miR-493-3p). This work sheds new light on the molecular mechanisms of ZEN, and fosters biomarker discovery.

mirTime: identifying condition-specific targets of microRNA in time-series transcript data using Gaussian process model and spherical vector clustering

Background

MicroRNAs, small noncoding RNAs, are conserved in many species, and they are key regulators that mediate post-transcriptional gene silencing. Since biologists cannot perform experiments for each of target genes of thousands of microRNAs in numerous specific conditions, prediction on microRNA target genes has been extensively investigated. A general framework is a two-step process of selecting target candidates based on sequence and binding energy features and then predicting targets based on negative correlation of microRNAs and their targets. However, there are few methods that are designed for target predictions using time-series gene expression data.

Results

In this article, we propose a new pipeline, mirTime, that predicts microRNA targets by integrating sequence features and time-series expression profiles in a specific experimental condition. The most important feature of mirTime is that it uses the Gaussian process regression model to measure data at unobserved or unpaired time points. In experiments with two datasets in different experimental conditions and cell types, condition-specific target modules reported in the original papers were successfully predicted with our pipeline. The context specificity of target modules was assessed with three (correlation-based, target gene-based and network-based) evaluation criteria. mirTime showed better performance than existing expression-based microRNA target prediction methods in all three criteria.

Availability and implementation

mirTime is available at https://github.com/mirTime/mirtime.

Supplementary information

Supplementary data are available at Bioinformatics online.

H19X-encoded miR-424(322)/-503 cluster: emerging roles in cell differentiation, proliferation, plasticity and metabolism

miR-424(322)/-503 are mammal-specific members of the extended miR-15/107 microRNA family. They form a co-expression network with the imprinted lncRNA H19 in tetrapods. miR-424(322)/-503 regulate fundamental cellular processes including cell cycle, epithelial-to-mesenchymal transition, hypoxia and other stress response. They control tissue differentiation (cardiomyocyte, skeletal muscle, monocyte) and remodeling (mammary gland involution), and paradoxically participate in tumor initiation and progression. Expression of miR-424(322)/-503 is governed by unique mechanisms involving sex hormones. Here, we summarize current literature and provide a primer for future endeavors.

Identifying a miRNA signature for predicting the stage of breast cancer

Breast cancer is a heterogeneous disease and one of the most common cancers among women. Recently, microRNAs (miRNAs) have been used as biomarkers due to their effective role in cancer diagnosis. This study proposes a support vector machine (SVM)-based classifier SVM-BRC to categorize patients with breast cancer into early and advanced stages. SVM-BRC uses an optimal feature selection method, inheritable bi-objective combinatorial genetic algorithm, to identify a miRNA signature which is a small set of informative miRNAs while maximizing prediction accuracy. MiRNA expression profiles of a 386-patient cohort of breast cancer were retrieved from The Cancer Genome Atlas. SVM-BRC identified 34 of 503 miRNAs as a signature and achieved a 10-fold cross-validation mean accuracy, sensitivity, specificity, and Matthews correlation coefficient of 80.38%, 0.79, 0.81, and 0.60, respectively. Functional enrichment of the 10 highest ranked miRNAs was analysed in terms of Kyoto Encyclopedia of Genes and Genomes and Gene Ontology annotations. Kaplan-Meier survival analysis of the highest ranked miRNAs revealed that four miRNAs, hsa-miR-503, hsa-miR-1307, hsa-miR-212 and hsa-miR-592, were significantly associated with the prognosis of patients with breast cancer.

microRNA Regulation in Estrogen Receptor-Positive Breast Cancer and Endocrine Therapy

As de novo and acquired resistance to standard first line endocrine therapies is a growing clinical challenge for estrogen receptor-positive (ER⁺) breast cancer patients, understanding the mechanisms of resistance is critical to develop novel therapeutic strategies to prevent therapeutic resistance and improve patient outcomes. The widespread post-transcriptional regulatory role that microRNAs (miRNAs) can have on various oncogenic pathways has been well-documented. In particular, several miRNAs are reported to suppress ERα expression via direct binding with the 3’ UTR of ESR1 mRNA, which can confer resistance to estrogen/ERα-targeted therapies. In turn, estrogen/ERα activation can modulate miRNA expression, which may contribute to ER⁺ breast carcinogenesis. Given the reported oncogenic and tumor suppressor functions of miRNAs in ER⁺ breast cancer, the targeted regulation of specific miRNAs is emerging as a promising strategy to treat ER⁺ breast cancer and significantly improve patient responsiveness to endocrine therapies. In this review, we highlight the major miRNA-ER regulatory mechanisms in context with ER⁺ breast carcinogenesis, as well as the critical miRNAs that contribute to endocrine therapy resistance or sensitivity. Collectively, this comprehensive review of the current literature sheds light on the clinical applications and challenges associated with miRNA regulatory mechanisms and novel miRNA targets that may have translational value as potential therapeutics for the treatment of ER⁺ breast cancer.

CpG island composition differences are a source of gene expression noise indicative of promoter responsiveness

BACKGROUND

Population phenotypic variation can arise from genetic differences between individuals, or from cellular heterogeneity in an isogenic group of cells or organisms. The emergence of gene expression differences between genetically identical cells is referred to as gene expression noise, the sources of which are not well understood.

RESULTS

In this work, by studying gene expression noise between multiple cell lineages and mammalian species, we find consistent evidence of a role for CpG islands as sources of gene expression noise. Variation in noise among CpG island promoters can be partially attributed to differences in island size, in which short islands have noisier gene expression. Building on these findings, we investigate the potential for short CpG islands to act as fast response elements to environmental stimuli. Specifically, we find that these islands are enriched amongst primary response genes in SWI/SNF-independent stimuli, suggesting that expression noise is an indicator of promoter responsiveness.

CONCLUSIONS

Thus, through the integration of single-cell RNA expression profiling, chromatin landscape and temporal gene expression dynamics, we have uncovered a role for short CpG island promoters as fast response elements.