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Abstract Background Specific biomarkers of pyelonephritis (PN) in cats are lacking. MicroRNAs (miRNAs) have diagnostic potential in human nephropathies. Objectives To investigate the presence/stability of miRNAs in whole urine of cats and the discriminatory potential of selected urinary miRNAs for PN in cats. Animals Twelve healthy cats, 5 cats with PN, and 13 cats with chronic kidney disease (n = 5), subclinical bacteriuria (n = 3), and ureteral obstructions (n = 5) recruited from 2 companion animal hospitals. Methods Prospective case-control study. Expression profiles of 24 miRNAs were performed by quantitative PCR (qPCR). Effect of storage temperature (4°C [24 hours], −20°C, and −80°C) was determined for a subset of miRNAs in healthy cats. Results Urinary miR-4286, miR-30c, miR-204, miR4454, miR-21, miR-16, miR-191, and miR-30a were detected. For the majority of miRNAs tested, storage at 4°C and −20°C resulted in significantly lower miRNA yield compared to storage at −80°C (mean log2fold changes across miRNAs from −0.5  ± 0.4 SD to −1.20 ± 0.4 SD (4°C versus −80°C) and from −0.7 ± 0.2 SD to −1.20 ± 0.3 SD (−20°C versus −80°C)). Cats with PN had significantly upregulated miR-16 with a mean log2fold change of 1.0 ± 0.4 SD, compared with controls (−0.1 ± 0.2, P = .01) and other urological conditions (0.6 ± 0.3, P = .04). Conclusions Upregulation of miR16 might be PN-specific, pathogen-specific (Escherichia coli), or both.

Glioblastoma multiforme is the most common primary brain tumor and is highly lethal. This study aims to figure out signatures for predicting the survival time of patients with glioblastoma multiforme. Clinical information, messenger RNA expression, microRNA expression, and single-nucleotide polymorphism array data of patients with glioblastoma multiforme were retrieved from The Cancer Genome Atlas. Patients were separated into two groups by using 1 year as a cutoff, and a logistic regression model was used to figure out any variables that can predict whether the patient was able to live longer than 1 year. Furthermore, Cox’s model was used to find out features that were correlated with the survival time. Finally, a Cox model integrated the significant clinical variables, messenger RNA expression, microRNA expression, and single-nucleotide polymorphism was built. Although the classification method failed, signatures of clinical features, messenger RNA expression levels, and microRNA expression levels were figured out by using Cox’s model. However, no single-nucleotide polymorphisms related to prognosis were found. The selected clinical features were age at initial diagnosis, Karnofsky score, and race, all of which had been suggested to correlate with survival time. Both of the two significant microRNAs, microRNA-221 and microRNA-222, were targeted to p27Kip1 protein, which implied the important role of p27Kip1 on the prognosis of glioblastoma multiforme patients. Our results suggested that survival modeling was more suitable than classification to figure out prognostic biomarkers for patients with glioblastoma multiforme. An integrated model containing clinical features, messenger RNA levels, and microRNA expression levels was built, which has the potential to be used in clinics and thus to improve the survival status of glioblastoma multiforme patients.

Background and objectiveGastric cancer (GC) remains a prevalent and preventable disease, yet accurate early diagnostic methods are lacking. Exosome non-coding RNAs (ncRNAs), a type of liquid biopsy, have emerged as promising diagnostic biomarkers for various tumours. This study aimed to identify a serum exosome ncRNA feature for enhancing GC diagnosis.DesignsSerum exosomes from patients with GC (n=37) and healthy donors (n=20) were characterised using RNA sequencing, and potential biomarkers for GC were validated through quantitative reverse transcription PCR (qRT-PCR) in both serum exosomes and tissues. A combined diagnostic model was developed using LASSO-logistic regression based on a cohort of 518 GC patients and 460 healthy donors, and its diagnostic performance was evaluated via receiver operating characteristic curves.ResultsRNA sequencing identified 182 candidate biomarkers for GC, of which 31 were validated as potential biomarkers by qRT-PCR. The combined diagnostic score (cd-score), derived from the expression levels of four long ncRNAs (RP11.443C10.1, CTD-2339L15.3, LINC00567 and DiGeorge syndrome critical region gene (DGCR9)), was found to surpass commonly used biomarkers, such as carcinoembryonic antigen, carbohydrate antigen 19-9 (CA19-9) and CA72-4, in distinguishing GC patients from healthy donors across training, testing and external validation cohorts, with AUC values of 0.959, 0.942 and 0.949, respectively. Additionally, the cd-score could effectively identify GC patients with negative gastrointestinal tumour biomarkers and those in early-stage. Furthermore, molecular biological assays revealed that knockdown of DGCR9 inhibited GC tumour growth.ConclusionsOur proposed serum exosome ncRNA feature provides a promising liquid biopsy approach for enhancing the early diagnosis of GC.

Background Neuropathic pain (NP) lacks clear biomarkers and effective treatment methods. We aimed to identify important genes and microRNA (miRNA)–messenger RNA (mRNA) regulatory network in NP to elucidate the underlying mechanism of NP using bioinformatics analysis combined with an animal model. Methods Two NP‐related gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between NP and controls were identified using the limma package. Protein–protein interaction (PPI) and miRNA–mRNA‐disease networks were constructed to investigate the interactions among genes and miRNAs. Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed to investigate the biological functions of DEGs in NP. Additionally, to further confirm the expression and the functions of hub genes, a chronic constriction injury (CCI) NP rat model was established, and C1qb knockdown treatment was performed by transfection of sh‐C1qb. Results A total of 108 common DEGs (94 upregulated and 14 downregulated) were identified related to the pathogenesis of NP. Five hub genes (Ptprc, C1qb, Aif1, Fcgr2b, and Ccl2) were selected in the PPI network. KEGG analyses unveiled that the five hub genes were primarily involved in immune regulation and neuroinflammation especially NF‐κB signaling pathway. miRNA–mRNA‐disease network analysis revealed 160 miRNAs associated with the five hub genes, and 25 miRNAs (including miR‐124‐3p, miR‐128‐3p, and miR‐369‐3p) were regulated to Ptprc, C1qb, Fcgr2b, and Ccl2 in NP. Moreover, the expressions of Aif1, Ptprc, C1qb, Fcgr2b, and Ccl2 were increased in blood, spinal cord, dorsal root ganglia, and prefrontal cortex in NP rats compared to sham rats. C1qb knockdown alleviated the rat NP and inhibited the NF‐κB signaling pathway. Conclusion Four hub genes (Ptprc, C1qb, Fcgr2b, and Ccl2) may be potential biomarkers in NP pathogenesis, offering insights into its molecular mechanisms and suggesting therapeutic targets. C1qb knockdown is demonstrated to alleviate the NP progression through the NF‐κB signaling pathway. The differentially expressed genes (DEGs) in neuropathic pain (NP) and their potential regulation by miRNAs were investigated by differential expressionanalysis and protein‐protein interaction network. Fianlly, Aif1, Ptprc, C1qb, Fcgr2b, and Ccl2 emerged as potential biomarkers for NP; miR‐124‐3p, miR‐128‐3p, and miR‐369‐3p may target Ccl2 and Ptprc to regulate NP.

MicroRNAs (miRs, miRNAs) are small molecules of 18–22 nucleotides that serve as important regulators of gene expression at the post-transcriptional level. One of the mechanisms through which miRNAs regulate gene expression involves the interaction of their “seed” sequences primarily with 3′-end and more rarely with 5′-end, of mRNA transcribed from target genes. Numerous studies over the past decade have been devoted to quantitative and qualitative assessment of miRNAs expression and have shown remarkable changes in miRNA expression profiles in various diseases. Thus, profiling of miRNA expression can be an important tool for diagnostics and treatment of disease. However, less attention has been paid towards understanding the underlying reasons for changes in miRNA expression, especially in cancer cells. The purpose of this review is to analyze and systematize current data that explains reasons for changes in the expression of miRNAs. The review will cover both transcriptional (changes in gene expression and promoter hypermethylation) and post-transcriptional (changes in miRNA processing) mechanisms of regulation of miRNA expression, as well as effects of endogenous (hormones, cytokines) and exogenous (xenobiotics) compounds on the miRNA expression. The review will summarize the complex multilevel regulation of miRNA expression, in relation to cell type, physiological state of the body and various external factors.

Background DNA 5-methylcytosine (5mC) and RNA N6-methyladenosine (m6A) methylation are prevalent modifications in eukaryotes, both playing crucial roles in gene regulation. Recent studies have explored their crosstalk and impact on transcription. However, the intricate relationships among 5mC, m6A, and gene expression remain incompletely elucidated. Results We collect data on 5mC, m6A, and gene expression from samples from three tissues from each of four pregnant cattle and sheep. We construct a comprehensive genome-wide self-interaction (same gene) and across-interaction (across genes) network of 5mC and m6A within gene-bodies or promoters and gene expression in both species. Qualitative analysis identifies uniquely expressed genes with specific m6A methylation in each tissue from both species. A quantitative comparison of gene expression ratio between methylated and unmethylated genes for m6A within gene body and promoter, and 5mC within gene body and promoter confirms the positive effect of RNA methylation on gene expression. Importantly, the influence of RNA methylation on gene expression is stronger than that of DNA methylation. The predominant self- and across-interactions are between RNA methylation within gene bodies and gene expression, as well as between RNA methylation within promoters and gene expression in both species. Conclusions RNA methylation has a stronger effect on gene expression than does DNA methylation within gene bodies and promoters. DNA and RNA methylation in gene-bodies has a greater impact on gene expression than those in promoters. These findings deepen comprehension of the dynamics and complex relationships among the epigenome, epitranscriptome, and transcriptome, offering fresh insights for advancing epigenetics research.

BackgroundPancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer with a 5-year survival rate of 12%. It has two major molecular subtypes: classical and basal, regulated by the master transcription factors (MTFs) GATA6 and ΔNp63, respectively.ObjectiveThis study sought to uncover the transcriptional regulatory mechanisms controlling PDAC subtype identity.DesignWe integrated primary tumour single-cell RNA-seq, patient-derived xenograft RNA-seq and multispectral imaging to identify MTF-dependent, subtype-specific markers. We created subtype-specific fluorescent reporter systems and conducted drug screenings to find actionable targets. We analysed chromatin accessibility (ATAC-seq), genome-wide occupancy (ChIP-seq) for epigenetic status (H3K27ac), MTFs (GATA6, ΔNp63), RNA polymerase II (Pol II), H3K4me3-anchored chromatin topology (HiChIP) and nascent RNA capture sequencing (PRO-seq). Additionally, we used nuclease-dead Cas9 (dCas9) to manipulate transcriptional regulatory mechanisms.ResultsOur approach identified glucocorticoid receptor (GR) agonists as agents that suppress the classical transcriptional programme by interacting with GATA6. GATA6 regulates classical-specific transcription through promoter-proximal pause release. Depletion of GATA6 increased Pol II occupancy at GATA6-bound enhancers and transcriptional start sites, stabilising enhancer–promoter interactions. Artificially inducing pausing at GATA6-bound enhancers with dCas9 abrogated target gene expression and induced pausing at both the enhancer and target gene promoter. Conversely, in basal PDAC ΔNp63 promotes Pol II recruitment and stabilises enhancer–promoter interactions.ConclusionThis study provides new insights into the transcriptional control and role of GR agonists in controlling PDAC molecular subtype identity.

ObjectivePancreatic ductal adenocarcinoma (PDA) is a highly metastatic disease with limited therapeutic options. Genome and transcriptome analyses have identified signalling pathways and cancer driver genes with implications in patient stratification and targeted therapy. However, these analyses were performed in bulk samples and focused on coding genes, which represent a small fraction of the genome.DesignWe developed a computational framework to reconstruct the non-coding transcriptome from cross-sectional RNA-Seq, integrating somatic copy number alterations (SCNA), common germline variants associated to PDA risk and clinical outcome. We validated the results in an independent cohort of paired epithelial and stromal RNA-Seq derived from laser capture microdissected human pancreatic tumours, allowing us to annotate the compartment specificity of their expression. We employed systems and experimental biology approaches to interrogate the function of epithelial long non-coding RNAs (lncRNAs) associated with genetic traits and clinical outcome in PDA.ResultsWe generated a catalogue of PDA-associated lncRNAs. We showed that lncRNAs define molecular subtypes with biological and clinical significance. We identified lncRNAs in genomic regions with SCNA and single nucleotide polymorphisms associated with lifetime risk of PDA and associated with clinical outcome using genomic and clinical data in PDA. Systems biology and experimental functional analysis of two epithelial lncRNAs (LINC00673 and FAM83H-AS1) suggest they regulate the transcriptional profile of pancreatic tumour samples and PDA cell lines.ConclusionsOur findings indicate that lncRNAs are associated with genetic marks of pancreatic cancer risk, contribute to the transcriptional regulation of neoplastic cells and provide an important resource to design functional studies of lncRNAs in PDA.

GenMineTOP, the first dual DNA–RNA comprehensive genomic profiling (CGP) test in Japan, was approved for reimbursement in 2023. To evaluate its clinical utility, we analyzed 1356 cases from the Center for Cancer Genomics and Advanced Therapeutics (C‐CAT) database. Oncogenic genomic alterations were identified in 91.5% of cases. Somatic mutations were the most prevalent, followed by amplifications and fusion/exon skipping events. The DNA panel, covering 737 genes, detected not only alterations relevant to therapeutic decisions but also those providing insights into tumor biology. Among the latter, frequently observed examples included mutations in KMT2C (n = 28) and ARID1B (n = 24), and amplifications in GLI1 (n = 14) and YAP1 (n = 10), which are not included in other CGP tests approved in Japan. The RNA panel identified 105 fusion events, including 11 NTRK fusions (0.8%), of which five were NTRK3 fusions: two with the well‐known ETV6‐NTRK3 fusion and three with non‐ETV6 partners. Forty‐nine of these fusions were diagnostically significant, highlighting the utility of the RNA panel. Amplification‐RNA expression analyses revealed strong correlations for MDM2, CDK4, EGFR, and ERBB2. In contrast, weaker correlations observed for MYC and FGFR1 highlighted the need for careful interpretation of amplification in these genes. Cancer type significantly influenced RNA expression, with KIT and TERT mutations linked to increased expression and significant overexpression observed in ALK, FGFR3, NTRK1, NTRK3, and RET fusions. In summary, this study demonstrated the real‐world clinical utility of the dual DNA–RNA CGP test and provided a valuable resource for interpreting RNA expressions. This study analyzed 1356 cases using GenMineTOP, Japan's first dual DNA–RNA CGP test, and identified oncogenic alterations in 91.5% of cases. The RNA panel detected 105 fusion events, including 11 NTRK fusions. Furthermore, the analysis clarified the independent effects of genomic abnormalities and cancer type on RNA expression, providing valuable insights for precise and reliable diagnostics.

Perturbation of mRNA splicing is commonly observed in human cancers and plays a role in various aspects of cancer hallmarks. Understanding the mechanisms and functions of alternative splicing (AS) not only enables us to explore the complex regulatory network involved in tumour initiation and progression but also reveals potential for RNA-based cancer treatment strategies. This review provides a comprehensive summary of the significance of AS in liver cancer, covering the regulatory mechanisms, cancer-related AS events, abnormal splicing regulators, as well as the interplay between AS and post-transcriptional and post-translational regulations. We present the current bioinformatic approaches and databases to detect and analyse AS in cancer, and discuss the implications and perspectives of AS in the treatment of liver cancer.