Effect of NOP2 knockdown on colon cancer cell proliferation, migration, and invasion

Epitranscriptomic orchestrations: Unveiling the regulatory paradigm of m6A, A-to-I editing, and m5C in breast cancer via long noncoding RNAs and microRNAs

Breast cancer (BC) poses a persistent global health challenge, particularly in countries with elevated human development indices linked to factors such as increased life expectancy, education, and wealth. Despite therapeutic progress, challenges persist, and the role of epitranscriptomic RNA modifications in BC remains inadequately understood. The epitranscriptome, comprising diverse posttranscriptional modifications on RNA molecules, holds the potential to intricately modulate RNA function and regulation, implicating dysregulation in various diseases, including BC. Noncoding RNAs (ncRNAs), acting as posttranscriptional regulators, influence physiological and pathological processes, including cancer. RNA modifications in long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) add an extra layer to gene expression control. This review delves into recent insights into epitranscriptomic RNA modifications, such as N-6-methyladenosine (m6A), adenine-to-inosine (A-to-I) editing, and 5-methylcytosine (m5C), specifically in the context of lncRNA and miRNAs in BC, highlighting their potential implications in BC development and progression. Understanding this intricate regulatory landscape is vital for deciphering the molecular mechanisms underlying BC and identifying potential therapeutic targets.

Nuclear protein NOP2 serves as a poor-prognosis predictor of LUAD and aggravates the malignancy of lung adenocarcinoma cells

Recent studies have shown that NOP2, a nucleolar protein, is up-regulated in various cancers, suggesting a potential link to tumor aggressiveness and unfavorable outcomes. This study examines NOP2's role in lung adenocarcinoma (LUAD), a context where its implications remain unclear. Utilizing bioinformatics, we assessed 513 LUAD and 59 normal tissue samples from The Cancer Genome Atlas (TCGA) to explore NOP2's diagnostic and prognostic significance in LUAD. Additionally, in vitro experiments compared NOP2 expression between Beas-2b and A549 cells. Advanced databases and analytical tools, including LINKEDOMICS, STRING, and TISIDB, were employed to further elucidate NOP2's association with LUAD. Our findings indicate a significantly higher expression of NOP2 mRNA and protein in A549 cells compared to Beas-2b cells (P < 0.001). In LUAD, elevated NOP2 levels were linked to decreased Overall Survival (OS) and advanced clinical stages. Univariate Cox analysis revealed that high NOP2 expression correlated with poorer OS in LUAD (P < 0.01), a finding independently supported by multivariate Cox analysis (P < 0.05). The relationship between NOP2 expression and LUAD risk was presented via a Nomogram. Additionally, Gene Set Enrichment Analysis (GSEA) identified seven NOP2-related signaling pathways. A focal point of our research was the interplay between NOP2 and tumor-immune interactions. Notably, a negative correlation was observed between NOP2 expression and the immune infiltration levels of macrophages, neutrophils, mast cells, Natural Killer (NK) cells, and CD8 + T cells in LUAD. Moreover, the expression of NOP2 was related to the sensitivity of various chemotherapeutic drugs. In vitro, we found that downregulating NOP2 can decrease the proliferation, migration and invasion of A549 cells. Furthermore, NOP2 can regulate Caspase3-mediated apoptosis. Collectively, particularly regarding prognosis, immune infiltration and vitro experiments, these findings suggest NOP2's potential of serving as a poor-prognostic biomarker for LUAD and aggravating the malignancy of lung adenocarcinoma cells.

Function of m5C RNA methyltransferase NOP2 in high-grade serous ovarian cancer

RNA methyltransferase nucleolar protein p120 (NOP2), commonly referred to as NOP2/Sun RNA methyltransferase family member 1 (NSUN1), is involved in cell proliferation and is highly expressed in various cancers. However, its role in high-grade serous ovarian cancer (HGSOC) remains unclear. Our study investigated the expression of NOP2 in HGSOC tissues and normal fimbria tissues, and found that NOP2 was significantly upregulated in HGSOC tissues. Our experiments showed that NOP2 overexpression promoted cell proliferation in vivo and in vitro and increased the migration and invasion ability of HGSOC cells in vitro. Furthermore, we identified Rap guanine nucleotide exchange factor 4 (RAPGEF4) as a potential downstream target of NOP2 in HGSOC. Finally, our findings suggest that the regulation of NOP2 and RAPGEF4 may depend on m5C methylation levels.

RatDEGdb: a knowledge base of differentially expressed genes in the rat as a model object in biomedical research

The animal models used in biomedical research cover virtually every human disease. RatDEGdb, a knowledge base of the differentially expressed genes (DEGs) of the rat as a model object in biomedical research is a collection of published data on gene expression in rat strains simulating arterial hypertension, age-related diseases, psychopathological conditions and other human afflictions. The current release contains information on 25,101 DEGs representing 14,320 unique rat genes that change transcription levels in 21 tissues of 10 genetic rat strains used as models of 11 human diseases based on 45 original scientific papers. RatDEGdb is novel in that, unlike any other biomedical database, it offers the manually curated annotations of DEGs in model rats with the use of independent clinical data on equal changes in the expression of homologous genes revealed in people with pathologies. The rat DEGs put in RatDEGdb were annotated with equal changes in the expression of their human homologs in affected people. In its current release, RatDEGdb contains 94,873 such annotations for 321 human genes in 836 diseases based on 959 original scientific papers found in the current PubMed. RatDEGdb may be interesting first of all to human geneticists, molecular biologists, clinical physicians, genetic advisors as well as experts in biopharmaceutics, bioinformatics and personalized genomics. RatDEGdb is publicly available at https://www.sysbio.ru/RatDEGdb.

Combining Bulk RNA-seq and scRNA-seq data to identify RNA m5C methyltransferases NSUN1: a rising star as a biomarker for cancer diagnosis, prognosis and therapy

Background

RNA 5-methylcytosine (m5C) methyltransferases NSUN1 is a member of the NOP2/SUN (NSUN) RNA methyltransferase family. Studies have found that the expression of NSUN1 is elevated in breast and colon cancer and can predict poor prognosis. However, the NSUN1 gene has only been studied in a few tumors.

Methods

Single-cell RNA sequencing (scRNA-seq) and Bulk RNA-seq data were used for comprehensive analysis of NSUN1 in cancers. The Human Protein Atlas (HPA) database was used to identify the gene location. Immunofluorescence staining was used to detect NSUN1 subcellular distribution within the nucleus, endoplasmic reticulum (ER), and microtubules of A-431, U-2, U-251 cells. The cBioPortal tool was used to analyze the alteration frequency and mutation type. The epigenetic profile of NSUN1 also was analyzed by using the University of Alabama at Birmingham CANcer data analysis Portal (UCLCAN). Tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoint expression in cancers were analyzed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to perform enrichment and visualization. The study was based on online resources and public databases.

Results

Elevated NSUN1 expression had been observed in most human cancers. Analysis of scRNA-seq data showed that NSUN1 was highly expressed in immune cells such as T cells, B cells, and dendritic (DC) cells. High NSUN1 expression indicated poor overall survival (OS) and disease-free survival (DFS). The characteristics of genetic alteration, methylation and phosphorylation of NSUN1 were analyzed and higher levels of phosphorylation in tumor tissues were found. In addition, the expression of NSUN1 was closely related to tumor-infiltrating immune cells. At the same time, the expression of NSUN1 was positively correlated with the expression of multiple immune checkpoints.

Conclusions

The gene expression profile, survival status, genetic alteration, methylation, phosphorylation and infiltrating immune cells of NSUN1 in human cancers were comprehensively analyzed. The results herein implied that NSUN1 may be an effective biomarker for early cancer diagnosis, prognosis and therapy.

Identification of ZMYND19 as a novel biomarker of colorectal cancer: RNA-sequencing and machine learning analysis

Colorectal cancer (CRC) is the third most common cause of cancer-related deaths. The five-year relative survival rate for CRC is estimated to be approximately 90% for patients diagnosed with early stages and 14% for those diagnosed at an advanced stages of disease, respectively. Hence, the development of accurate prognostic markers is required. Bioinformatics enables the identification of dysregulated pathways and novel biomarkers. RNA expression profiling was performed in CRC patients from the TCGA database using a Machine Learning approach to identify differential expression genes (DEGs). Survival curves were assessed using Kaplan-Meier analysis to identify prognostic biomarkers. Furthermore, the molecular pathways, protein-protein interaction, the co-expression of DEGs, and the correlation between DEGs and clinical data have been evaluated. The diagnostic markers were then determined based on machine learning analysis. The results indicated that key upregulated genes are associated with the RNA processing and heterocycle metabolic process, including C10orf2, NOP2, DKC1, BYSL, RRP12, PUS7, MTHFD1L, and PPAT. Furthermore, the survival analysis identified NOP58, OSBPL3, DNAJC2, and ZMYND19 as prognostic markers. The combineROC curve analysis indicated that the combination of C10orf2 -PPAT- ZMYND19 can be considered as diagnostic markers with sensitivity, specificity, and AUC values of 0.98, 1.00, and 0.99, respectively. Eventually, ZMYND19 gene was validated in CRC patients. In conclusion, novel biomarkers of CRC have been identified that may be a promising strategy for early diagnosis, potential treatment, and better prognosis.

Differential Regulation of Genes by the Glucogenic Hormone Asprosin in Ovarian Cancer

Background: Ovarian cancer (OvCa) is one of the most lethal forms of gynaecological malignancy. Altered energy metabolism and increased aerobic glycolysis in OvCa are hallmarks that demand attention. The glucogenic hormone asprosin is often dysregulated in metabolic disorders such as insulin resistance, diabetes (type 2 and gestational), and preeclampsia. Despite association with metabolic disorders, its role in energy metabolism within the tumour microenvironment is yet to be explored. Here, we study the role of asprosin in OvCa using transcriptomics and expand on functional studies with clinical samples. Methods: RNA sequencing, functional gene enrichment analysis, Western blotting and ImageStream. Results: Following treatment with 100 nM of asprosin, the serous OvCa cell line, SKOV-3, displayed 160 and 173 gene regulatory changes, at 4 and 12 h respectively, when compared with control samples (p < 0.05 and Log2FC > 1). In addition to energy metabolism and glucose-related pathways, asprosin was shown to alter pathways associated with cell communication, TGF-β signalling, and cell proliferation. Moreover, asprosin was shown to induce phosphorylation of ERK1/2 in the same in vitro model. Using liquid biopsies, we also report for novel expression of asprosin’s predicted receptors OR4M1 and TLR4 in cancer-associated circulating cells; with significant reduction seen between pre-chemotherapy and end of first line chemotherapy, in addition to patients under maintenance with bevacizumab +/− olaparib for OR4M1. Conclusions: In relation to OvCa, asprosin appears to regulate numerous signalling pathways in-vitro. The prognostic potential of OR4M1 in liquid biopsies should also be explored further.

Human NOP2/NSUN1 regulates ribosome biogenesis through non-catalytic complex formation with box C/D snoRNPs

5-Methylcytosine (m⁵C) is a base modification broadly found on various RNAs in the human transcriptome. In eukaryotes, m⁵C is catalyzed by enzymes of the NSUN family composed of seven human members (NSUN1-7). NOP2/NSUN1 has been primarily characterized in budding yeast as an essential ribosome biogenesis factor required for the deposition of m⁵C on the 25S ribosomal RNA (rRNA). Although human NOP2/NSUN1 has been known to be an oncogene overexpressed in several types of cancer, its functions and substrates remain poorly characterized. Here, we used a miCLIP-seq approach to identify human NOP2/NSUN1 RNA substrates. Our analysis revealed that NOP2/NSUN1 catalyzes the deposition of m⁵C at position 4447 on the 28S rRNA. We also find that NOP2/NSUN1 binds to the 5′ETS region of the pre-rRNA transcript and regulates pre-rRNA processing through non-catalytic complex formation with box C/D snoRNAs. We provide evidence that NOP2/NSUN1 facilitates the recruitment of U3 and U8 snoRNAs to pre-90S ribosomal particles and their stable assembly into snoRNP complexes. Remarkably, expression of both WT and catalytically inactive NOP2/NSUN1 in knockdown background rescues the rRNA processing defects and the stable assembly of box C/D snoRNP complexes, suggesting that NOP2/NSUN1-mediated deposition of m⁵C on rRNA is not required for ribosome synthesis.

Mammalian Neuraminidases in Immune-Mediated Diseases: Mucins and Beyond

Mammalian neuraminidases (NEUs), also known as sialidases, are enzymes that cleave off the terminal neuraminic, or sialic, acid resides from the carbohydrate moieties of glycolipids and glycoproteins. A rapidly growing body of literature indicates that in addition to their metabolic functions, NEUs also regulate the activity of their glycoprotein targets. The simple post-translational modification of NEU protein targets-removal of the highly electronegative sialic acid-affects protein folding, alters protein interactions with their ligands, and exposes or covers proteolytic sites. Through such effects, NEUs regulate the downstream processes in which their glycoprotein targets participate. A major target of desialylation by NEUs are mucins (MUCs), and such post-translational modification contributes to regulation of disease processes. In this review, we focus on the regulatory roles of NEU-modified MUCs as coordinators of disease pathogenesis in fibrotic, inflammatory, infectious, and autoimmune diseases. Special attention is placed on the most abundant and best studied NEU1, and its recently discovered important target, mucin-1 (MUC1). The role of the NEU1 - MUC1 axis in disease pathogenesis is discussed, along with regulatory contributions from other MUCs and other pathophysiologically important NEU targets.

Epitranscriptomics: A New Layer of microRNA Regulation in Cancer

MicroRNAs are pervasive regulators of gene expression at the post-transcriptional level in metazoan, playing key roles in several physiological and pathological processes. Accordingly, these small non-coding RNAs are also involved in cancer development and progression. Furthermore, miRNAs represent valuable diagnostic and prognostic biomarkers in malignancies. In the last twenty years, the role of RNA modifications in fine-tuning gene expressions at several levels has been unraveled. All RNA species may undergo post-transcriptional modifications, collectively referred to as epitranscriptomic modifications, which, in many instances, affect RNA molecule properties. miRNAs are not an exception, in this respect, and they have been shown to undergo several post-transcriptional modifications. In this review, we will summarize the recent findings concerning miRNA epitranscriptomic modifications, focusing on their potential role in cancer development and progression.