miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology

Integrative analysis of anoikis-related genes prognostic signature with immunotherapy and identification of CDKN3 as a key oncogene in lung adenocarcinoma

Anoikis, a form of programmed cell death induced by loss of cell contact, is closely associated with tumor invasion and metastasis, making it highly significant in lung cancer research. We examined the expression patterns and prognostic relevance of Anoikis-related genes (ARGs) in lung adenocarcinoma (LUAD) using the TCGA-LUAD database. This study identified molecular subtypes associated with Anoikis in LUAD and conducted functional enrichment analyses. We constructed an ARG risk score using univariate least absolute shrinkage and selection operator (LASSO) Cox regression, validated externally with GEO datasets and clinical samples. The clinical applicability of the prognostic model was evaluated using nomograms, calibration curves, decision curve analysis (DCA), and time-dependent AUC assessments. We identified four prognostically significant genes (PLK1, SLC2A1, CDKN3, PHLDA2) and two ARG-related molecular subtypes. ARGs were generally upregulated in LUAD and correlated with multiple pathways including the cell cycle and DNA replication. The prognostic model indicated that the low-risk group had better outcomes and significant correlations with clinicopathological features, tumor microenvironment, immune therapy responses, drug sensitivity, and pan-RNA epigenetic modification-related genes. Patients with low-risk LUAD were potential beneficiaries of immune checkpoint inhibitor (ICI) therapy. Prognostic ARGs' distribution and expression across various immune cell types were further analyzed using single-cell RNA sequencing. The pivotal role of CDKN3 in LUAD was confirmed through qRT-PCR and gene knockout experiments, demonstrating that CDKN3 knockdown inhibits tumor cell proliferation, migration, and invasion. Additionally, we constructed a ceRNA network involving CDKN3/hsa-miR-26a-5p/SNHG6, LINC00665, DUXAP8, and SLC2A1/hsa-miR-218-5p/RNASEH1-AS1, providing new insights for personalized and immune therapy decisions in LUAD patients.

Integration of miRNA expression analysis of purified leukocytes and whole blood reveals blood-borne candidate biomarkers for lung cancer

Changes in leukocyte populations may confound the disease-associated miRNA signals in the blood of cancer patients. We aimed to develop a method to detect differentially expressed miRNAs from lung cancer whole blood samples that are not influenced by variations in leukocyte proportions. The Ref-miREO method identifies differential miRNAs unaffected by changes in leukocyte populations by comparing the within-sample relative expression orderings (REOs) of miRNAs from healthy leukocyte subtypes and those from lung cancer blood samples. Over 77% of the differential miRNAs observed between lung cancer and healthy blood samples overlapped with those between myeloid-derived and lymphoid-derived leukocytes, suggesting the potential impact of changes in leukocyte populations on miRNA profile. Ref-miREO identified 16 differential miRNAs that target 19 lung adenocarcinoma-related genes previously linked to leukocytes. These miRNAs showed enrichment in cancer-related pathways and demonstrated high potential as diagnostic biomarkers, with the LASSO regression models effectively distinguishing between healthy and lung cancer blood or serum samples (all AUC > 0.85). Additionally, 12 of these miRNAs exhibited significant prognostic correlations. The Ref-miREO method offers valuable candidates for circulating biomarker detection in cancer that are not affected by changes in leukocyte populations.

Identification of prostate cancer associated genes for diagnosis and prognosis: a modernized in silico approach

Prostate cancer (PCa) ranks as the second leading cause of cancer-related deaths in men. Diagnosing PCa relies on molecular markers known as diagnostic biomarkers, while prognostic biomarkers are used to identify key proteins involved in PCa treatments. This study aims to gather PCa-associated genes and assess their potential as either diagnostic or prognostic biomarkers for PCa. A corpus of 152,064 PCa-related data from PubMed, spanning from May 1936 to December 2020, was compiled. Additionally, 4199 genes associated with PCa terms were collected from the National Center of Biotechnology Information (NCBI) database. The PubMed corpus data was extracted using pubmed.mineR to identify PCa-associated genes. Network and pathway analyses were conducted using various tools, such as STRING, DAVID, KEGG, MCODE 2.0, cytoHubba app, CluePedia, and ClueGO app. Significant marker genes were identified using Random Forest, Support Vector Machines, Neural Network algorithms, and the Cox Proportional Hazard model. This study reports 3062 unique PCa-associated genes along with 2518 corresponding unique PMIDs. Diagnostic markers such as IL6, MAPK3, JUN, FOS, ACTB, MYC, and TGFB1 were identified, while prognostic markers like ACTB and HDAC1 were highlighted in PubMed. This suggests that the potential target genes provided by PubMed data outweigh those in the NCBI database.

Integrative analysis of FADS3 as a marker for prognosis and immunity in head and neck squamous cell carcinoma

BACKGROUND

Long-chain polyunsaturated fatty acid formation requires fatty acid desaturase (FADS), which is strongly linked to cancer progression. Nevertheless, it's unclear how FADS3 functions in head and neck squamous cell carcinoma (HNSCC).

METHODS

HNSCC cases were retrieved from TCGA and GEO databases, and FADS members with transcriptionally differential expression were identified. Clinical survival, tumor microenvironment (TME), and potential pathogenic mechanism in HNSCC were also investigated. These results were validated using tissue staining, flow cytometry and functional studies in HNSCC cell lines.

RESULTS

When comparing HNSCC to normal epithelial tissues, FADS3 expression was much higher in the former. FADS3 upregulation was correlated with poor clinical outcomes. FADS3 was an independent prognostic factor for poor overall survival in HNSCC patients. KEGG, GO, and GSEA revealed that FADS3 expression correlated with several immune-related pathways and the epithelial-mesenchymal transition (EMT). Knocking down FADS3 restrained HNSCC cell proliferation, migration, invasion, and EMT. Single-cell dataset analysis showed an association between FADS3 and TME features. Further investigation revealed that FADS3high tumor was accompanied with less CD8+ T cells in situ tissue and peripheral blood. FADS3 was positively correlated with immune-related molecules and could predict the adverse efficacy of immunotherapy. Finally, we constructed a CYTOR/hsa-let-7c-5p axis regulating FADS3 expression in HNSCC progression.

CONCLUSIONS

FADS3 may represent a target for treatment in HNSCC, which is linked to prognosis, EMT, immune infiltration, and ceRNA regulatory network of HNSCC.

The role of m5C RNA methylation regulators in the diagnosis and immune microenvironment of osteoarthritis

The 5-methylcytosine (m5C) is a common post-transcriptional RNA methylation modification and is involved in the pathological process of many diseases. However, little is known about the role of m5C in osteoarthritis (OA). OA gene data and the corresponding information were downloaded from the Gene Expression Omnibus database. Based on 36 m5C regulators, we constructed the landscape and diagnostic model for OA. Later, two m5C modification patterns were identified, and functional analyses were performed to evaluate whether these patterns were related to endoplasmic reticulum (ER) stress and mitochondrial autophagy. We further comprehensively analyzed the immune cell infiltration characteristics in different modification patterns in OA. We also established the post-transcriptional regulatory networks and drug-gene networks. Our findings suggested that m5C regulators were differentially expressed between OA and normal samples and could serve as novel biomarkers for the diagnosis of OA. Besides, m5C regulators may be involved in regulating ER stress, mitochondrial autophagy, and immune infiltration in OA. The m5C modification can influence the sensitivity to drugs and the potential post-transcriptional regulatory mechanisms might provide promising targets.

MIMR: Development of a Web-Based System for miRNA and mRNA Integrated Analysis

The human body is a complex network of systems that is harmonized with multiple biological components. To understand these interactions is very challenging. With rapid development of advanced sequencing technologies, massive amounts of data such as mRNA, miRNA are rapidly accumulated. The integrated analysis of mRNA-miRNA has brought an extensive understanding of complex biological systems and pathological mechanisms. MicroRNAs (miRNAs) are small non-coding RNAs that intricately regulate target gene products, resulting in the inhibition of gene expression. While these miRNAs play crucial roles in essential biological processes-ranging from immunity and metabolism to cell death-their specific impacts on diseases remain unknown. Recent studies have been focused on the integration of miRNA and mRNA expression to reveal the underlying biological pathways and mechanisms responsible for disease manifestation. We proposed a novel approach for integrative analysis of miRNA and mRNA expression data and developed MIMR (Integrative Analysis of miRNA and mRNA), a web-based application that leverages the Random Walk with Restart (RWR) algorithm. MIMR incorporates both direct and indirect interactions by utilizing protein-protein interaction (PPI) networks and experimentally validated mRNA-miRNA target interactions. MIMR provides comprehensive results, including novel pathological pathways associated with a specific disease and interactive network diagrams representing the mRNAs and miRNAs. We applied it to Alzheimer and breast cancer data and successfully identified the novel biological pathways related to these diseases. In summary, MIMR will offer a deeper insight into the hidden mechanisms of diseases and identify potential therapeutic strategies through integrated analysis of miRNAs and mRNAs.

MBNL splicing factors regulate the microtranscriptome of skeletal muscles

Muscleblind like splicing regulators (MBNLs) govern various RNA-processing steps, including alternative splicing, polyadenylation, RNA stability and mRNA intracellular localization. In myotonic dystrophy type 1 (DM1), the most common muscular dystrophy in adults, MBNLs are sequestered on toxic RNA containing expanded CUG repeats, which leads to disruption of MBNL-regulated processes and disease features of DM1. Herein, we show the significance of MBNLs in regulating microtranscriptome dynamics during the postnatal development of skeletal muscles and in microRNA (miRNA) misregulation observed in mouse models and patients with DM1. We identify multiple miRNAs sensitive to MBNL proteins insufficiency and reveal that many of them were postnatally regulated, which correlates with increases in the activity of these proteins during this process. In adult Mbnl1-knockout mice, miRNA expression exhibited an adult-to-newborn shift. We hypothesize that Mbnl1 deficiency influences miRNA levels through a combination of mechanisms. First, the absence of Mbnl1 protein results in alterations to the levels of pri-miRNAs. Second, MBNLs affect miRNA biogenesis by regulating the alternative splicing of miRNA primary transcripts. We propose that the expression of miR-23b, miR-27b and miR-24-1, produced from the same cluster, depends on the MBNL-sensitive inclusion of alternative exons containing miRNA sequences. Our findings suggest that MBNL sequestration in DM1 is partially responsible for altered miRNA activity. This study provides new insights into the biological roles and functions of MBNL proteins as regulators of miRNA expression in skeletal muscles.

miRNA biomarkers to predict risk of primary non-function of fatty allografts and drug induced acute liver failures

Primary non-function (PNF) of an allograft defines an irreversible graft failure and although rare, constitutes a life-threatening condition that requires high-urgency re-transplantation. Equally, drug induced acute liver failures (ALF) are seldom but the rapid loss of hepatic function may require orthotropic liver transplantation (OLT). Recently, we reported the development of a rodent PNF-disease model of fatty allografts and showed that a dysfunctional Cori and Krebs cycle and inhibition of lactate transporters constitute a mechanism of PNF. Based on findings from the rat PNF-disease model, we selected 15 miRNA-biomarker candidates for clinical validation and performed RT-qPCRs in well-documented PNF cases following OLT of fatty allografts. To assess specificity and selectivity, we compared their regulation in pre- and intraoperative liver biopsies and pre- and post-operative blood samples of patients undergoing elective hepatobiliary surgery. Additionally, we assessed their regulation in drug induced ALF. We confirmed clinical relevance for 11 PNF-associated miRNAs and found expression of miRNA-27b-3p, miRNA-122-3p, miRNA-125a-5p, miRNA-125b-5p and miRNA-192-5p to correlate with the hepatic steatosis grades. Furthermore, we demonstrate selectivity and specificity for the biomarker candidates with opposite regulation of let-7b-5p, miRNA-122-5p, miRNA-125b-5p and miRNA-194-5p in blood samples of patients following successful OLTs and/or liver resection. Moreover, by considering findings from 21 independent ALF-studies, we observed nine PNF-associated miRNAs regulated in common. We report miRNAs highly regulated in PNF and ALF, and their common regulation in different diseases broadens the perspective as biomarker candidates. Our study warrants independent confirmation in randomized clinical trials.

Impact of the near-physiological temperature on the in vitro maturation of bovine oocytes: A comparative proteomic approach

In vivo, the temperature inside preovulatory follicles of cows is approximately 1 °C lower than rectal temperature. However, standard bovine oocyte in vitro maturation (IVM) protocols use 38.5 °C based on rectal temperature. This study evaluated the effect of reducing IVM temperature to 37.5 °C on the proteomic profile of oocytes compared to the routine 38.5 °C. Nuclear maturation rate and cumulus cell (CC) expansion (30 COCs per group, 21 replicates) were assessed by observing the first polar body and using a subjective scoring method (0-4). Total nitrite concentrations in the culture medium were measured using the Griess method. Differential proteomics was performed using LC-MS/MS on pooled oocyte samples (500 matured oocytes per group, three replicates), followed by gene ontology enrichment, protein-protein interaction, and putative miRNA target analyses. No significant differences were observed between the groups in nuclear maturation, CC expansion, or nitrite concentration (P > 0.05). A total of 806 proteins were identified, with 7 up-regulated and 12 down-regulated in the treatment group compared to the control. Additionally, 12 proteins were unique to the control group, and 8 were unique to the treatment group. IVM at 37.5 °C resulted in the upregulation of proteins involved in protein folding and GTP binding, and the downregulation of enzymes with oxidoreductase activity and proteins involved in cytoskeletal fiber formation. Furthermore, 43 bovine miRNAs potentially regulating these genes (DES, HMOX2, KRT75, FARSA, IDH2, CARHSP1) were identified. We conclude that IVM of bovine oocytes at 37.5 °C induces significant proteomic changes without impacting nuclear maturation, cumulus cell expansion, or nitrite concentration in the IVM medium.

Integration of ubiquitination-related genes in predictive signatures for prognosis and immunotherapy response in sarcoma

Background

Ubiquitination is one of the most prevalent and complex post-translational modifications of proteins in eukaryotes, playing a critical role in regulating various physiological and pathological processes. Targeting ubiquitination pathways, either through inhibition or activation, holds promise as a novel therapeutic approach for cancer treatment. However, the expression patterns, prognostic significance, and underlying mechanisms of ubiquitination-related genes (URGs) in sarcoma (SARC) remain unclear.

Methods

We analyzed URG expression patterns and prognostic implications in TCGA-SARC using public databases, identifying DEGs related to ubiquitination among SARC molecular subtypes. Functional enrichment analysis elucidated their biological significance. Prognostic signatures were developed using LASSO-Cox regression, and a predictive nomogram was constructed. External validation was performed using GEO datasets and clinical tissue samples. The association between URG risk scores and various clinical parameters, immune response, drug sensitivity, and RNA modification regulators was investigated. Integration of data from multiple sources and RT-qPCR confirmed upregulated expression of prognostic URGs in SARC. Single-cell RNA sequencing data analyzed URG distribution across immune cell types. Prediction analysis identified potential target genes of microRNAs and long non-coding RNAs.

Results

We identified five valuable genes (CALR, CASP3, BCL10, PSMD7, PSMD10) and constructed a prognostic model, simultaneously identifying two URG-related subtypes in SARC. The UEGs between subtypes in SARC are mainly enriched in pathways such as Cell cycle, focal adhesion, and ECM-receptor interaction. Analysis of URG risk scores reveals that patients with a low-risk score have better prognoses compared to those with high-risk scores. There is a significant correlation between DRG riskscore and clinical features, immune therapy response, drug sensitivity, and genes related to pan-RNA epigenetic modifications. High-risk SARC patients were identified as potential beneficiaries of immune checkpoint inhibitor therapy. We established regulatory axes in SARC, including CALR/hsa-miR-29c-3p/LINC00943, CASP3/hsa-miR-143-3p/LINC00944, and MIR503HG. RT-qPCR data further confirmed the upregulation of prognostic URGs in SARC. Finally, we validated the prognostic model's excellent predictive performance in predicting outcomes for SARC patients.

Conclusion

We discovered a significant correlation between aberrant expression of URGs and prognosis in SARC patients, identifying a prognostic model related to ubiquitination. This model provides a basis for individualized treatment and immunotherapy decisions for SARC patients.

Integrated analysis of gene expressions and targeted mirnas for explaining crosstalk between oral and esophageal squamous cell carcinomas through an interpretable machine learning approach

This study explores the bidirectional relation of esophageal squamous cell carcinoma (ESCC) and oral squamous cell carcinoma (OSCC), examining shared risk factors and underlying molecular mechanisms. By employing random forest (RF) classifier, enhanced with interpretable machine learning (IML) through SHapley Additive exPlanations (SHAP), we analyzed gene expression from two GEO datasets (GSE30784 and GSE44021). The GSE30784 dataset comprises 167 OSCC samples and 45 control group, whereas the GSE44021 dataset encompasses 113 ESCC samples and 113 control group. Our analysis led to identification of 20 key genes, such as XBP1, VGLL1, and RAD1, which are significantly associated with development of ESCC and OSCC. Further investigations were conducted using tools like NetworkAnalyst 3.0, Single Cell Portal, and miRNET 2.0, which highlighted complex interactions between these genes and specific miRNA targets including hsa-mir-124-3p and hsa-mir-1-3p. Our model achieved high precision in identifying genes linked to crucial processes like programmed cell death and cancer pathways, suggesting new avenues for diagnosis and treatment. This study confirms the bidirectional relationship between OSCC and ESCC, laying groundwork for targeted therapeutic approaches. This study helps to identify shared biological pathways and genetic factors of these conditions for designing personalized medicine strategies and to improve disease management.

The Identification of New Pharmacological Targets for the Treatment of Glaucoma: A Network Pharmacology Approach

Background: Glaucoma is a progressive optic neuropathy characterized by the neurodegeneration and death of retinal ganglion cells (RGCs), leading to blindness. Current glaucoma interventions reduce intraocular pressure but do not address retinal neurodegeneration. In this effort, to identify new pharmacological targets for glaucoma management, we employed a network pharmacology approach. Methods: We first retrieved transcriptomic data from GEO, an NCBI database, and carried out GEO2R (an interactive web tool aimed at comparing two or more groups of samples in a GEO dataset). The GEO2R statistical analysis aimed at identifying the top differentially expressed genes (DEGs) and used these as input of STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) app within Cytoscape software, which builds networks of proteins starting from input DEGs. Analyses of centrality metrics using Cytoscape were carried out to identify nodes (genes or proteins) involved in network stability. We also employed the web-server software MIRNET 2.0 to build miRNA-target interaction networks for a re-analysis of the GSE105269 dataset, which reports analyses of microRNA expressions. Results: The pharmacological targets, identified in silico through analyses of the centrality metrics carried out with Cytoscape, were rescored based on correlations with entries in the PubMed and clinicaltrials.gov databases. When there was no match (82 out of 135 identified central nodes, in 8 analyzed networks), targets were considered "potential innovative" targets for the treatment of glaucoma, after further validation studies. Conclusions: Several druggable targets, such as GPCRs (e.g., 5-hydroxytryptamine 5A (5-HT5A) and adenosine A2B receptors) and enzymes (e.g., lactate dehydrogenase A or monoamine oxidase B), were found to be rescored as "potential innovative" pharmacological targets for glaucoma treatment.

Modulation of the Oncogenic LINE-1 Regulatory Network in Non-Small Cell Lung Cancer by Exosomal miRNAs

Several microRNAs (miRNAs), including miR-221-5p, Let-7b-5p, miR-21-5p, miR-9-5p, miR-126-3p, and miR-222-3p, were recently found to be enriched in circulating exosomes of patients with non-small cell lung cancers (NSCLCs). These miRNAs distinguished cancer cases from controls with high precision and were predicted to modulate the expression of genes within the oncogenic LINE-1 regulatory network. To test this hypothesis, plasma exosomes from controls, early, and late-stage NSCLC patients were co-cultured with non-tumorigenic lung epithelial cells for 72 h and processed for measurements of gene expression. Exosomes from late-stage NSCLC patients markedly increased the mRNA levels of LINE-1 ORF1 and ORF2, as well as the levels of target miRNAs in naïve recipient cells compared to saline or control exosomes. Late-stage exosomes also modulated the expression of oncogenic targets within the LINE-1 regulatory network, namely, ICAM1, AGL, RGS3, RGS13, VCAM1, and TGFβ1. In sharp contrast, exosomes from controls or early-stage NSCLC patients inhibited LINE-1 expression, along with many of the genetic targets within the LINE-1 regulatory network. Thus, late-stage NSCLC exosomes activate LINE-1 and miRNA-regulated oncogenic signaling in non-tumorigenic, recipient lung bronchial epithelial cells. These findings raise important questions regarding lung cancer progression and metastasis and open the door for the exploration of new therapeutic interventions.

Systems Biology and Machine Learning Identify Genetic Overlaps Between Lung Cancer and Gastroesophageal Reflux Disease

One Health and planetary health place emphasis on the common molecular mechanisms that connect several complex human diseases as well as human and planetary ecosystem health. For example, not only lung cancer (LC) and gastroesophageal reflux disease (GERD) pose a significant burden on planetary health, but also the coexistence of GERD in patients with LC is often associated with a poor prognosis. This study reports on the genetic overlaps between these two conditions using systems biology-driven bioinformatics and machine learning-based algorithms. A total of nine hub genes including IGHV1-3, COL3A1, ITGA11, COL1A1, MS4A1, SPP1, MMP9, MMP7, and LOC102723407 were found to be significantly altered in both LC and GERD as compared with controls and with pathway analyses suggesting a significant association with the matrix remodeling pathway. The expression of these genes was validated in two additional datasets. Random forest and K-nearest neighbor, two machine learning-based algorithms, achieved accuracies of 89% and 85% for distinguishing LC and GERD, respectively, from controls using these hub genes. Additionally, potential drug targets were identified, with molecular docking confirming the binding affinity of doxycycline to matrix metalloproteinase 7 (binding affinity: -6.8 kcal/mol). The present study is the first of its kind that combines in silico and machine learning algorithms to identify the gene signatures that relate to both LC and GERD and promising drug candidates that warrant further research in relation to therapeutic innovation in LC and GERD. Finally, this study also suggests upstream regulators, including microRNAs and transcription factors, that can inform future mechanistic research on LC and GERD.

Gene Coexpression and miRNA Regulation: A Path to Early Intervention in Colorectal Cancer

Early diagnosis and intervention are pivotal in reducing colorectal cancer (CRC) incidence and enhancing patient outcomes. In this study, we focused on three genes, AQP8, GUCA2B, and SPIB, which exhibit high coexpression and play crucial roles in suppressing early-stage CRC. Our objective was to identify key miRNAs that can mitigate CRC tumorigenesis and modulate the coexpression network involving these genes. We conducted a comprehensive analysis using large-scale tissue mRNA data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus to validate the coexpression of AQP8, GUCA2B, and SPIB, and to assess their diagnostic and prognostic significance in CRC. The mRNA-miRNA interactions were examined using MiRNet and the Encyclopedia of RNA Interactomes. Furthermore, using various molecular techniques, we conducted miRNA inhibitor transfection experiments in HCT116 cells to evaluate their effects on cell growth, migration, and gene/protein expression. Our findings revealed that, compared with normal tissues, AQP8, GUCA2B, and SPIB exhibited high coexpression and were downregulated in CRC, particularly during tumorigenesis. OncoMirs, hsa-miR-182-5p, and hsa-miR-27a-3p, were predicted to regulate these genes. MiRNA inhibition experiments in HCT116 cells demonstrated the inhibitory effects of miR-27a-3p and miR-182-5p on GUCA2B mRNA and protein expression. These miRNAs promoted the proliferation of CRC cells, possibly through their involvement in the GUCA2B-GUCY2C axis, which is known to promote tumor growth. While the expressions of AQP8 and SPIB were barely detectable, their regulatory relationship with hsa-miR-182-5p remained inconclusive. Our study confirms that hsa-miR-27a-3p and hsa-miR-182-5p are oncomiRs in CRC. These miRNAs may contribute to GUCY2C dysregulation by downregulating GUCA2B, which encodes uroguanylin. Consequently, hsa-miR-182-5p and hsa-miR-27a-3p show promise as potential targets for early intervention and treatment in the early stages of CRC.

Machine learning and experimental analyses identified miRNA expression models associated with metastatic osteosarcoma

Osteosarcoma (OS), as the most common primary bone cancer, has a high invasiveness and metastatic potential, therefore, it has a poor prognosis. This study identified early diagnostic biomarkers using miRNA expression profiles associated with osteosarcoma metastasis. In the first step, we used RNA-seq and online microarray data from osteosarcoma tissues and cell lines to identify differentially expressed miRNAs. Then, using seven feature selection algorithms for ranking, the first-ranked miRNAs were selected as input for five machine learning systems. Using network analysis and machine learning algorithms, we developed new diagnostic models that successfully differentiated metastatic osteosarcoma from non-metastatic samples based on newly discovered miRNA signatures. The results showed that miR-34c-3p and miR-154-3p act as the most promising models in the diagnosis of metastatic osteosarcoma. Validation for this model by RT-qPCR in benign tissue and osteosarcoma biopsies confirmed the lower expression of miR-34c-3p and miR-154-3p in OS samples. In addition, a direct correlation between miR-34c-3p expression, miR-154-3p expression and tumor grade was discovered. The combined values of miR-34c-3p and miR-154-3p showed 90 % diagnostic power (AUC = 0.90) for osteosarcoma samples and 85 % (AUC = 0.85) for metastatic osteosarcoma. Adhesion junction and focal adhesion pathways, as well as epithelial-to-mesenchymal transition (EMT) GO terms, were identified as the most significant KEGG and GO terms for the top miRNAs. The findings of this study highlight the potential use of novel miRNA expression signatures for early detection of metastatic osteosarcoma. These findings may help in determining therapeutic approaches with a quantitative and faster method of metastasis detection and also be used in the development of targeted molecular therapy for this aggressive cancer. Further research is needed to confirm the clinical utility of miR-34c-3p and miR-154-3p as diagnostic biomarkers for metastatic osteosarcoma.

Host genetics and microbiota data analysis in colorectal cancer research

Colorectal cancer (CRC) is a heterogeneous disease with a complex aetiology influenced by a myriad of genetic and environmental factors. Despite advances in CRC research, it is a major burden of disease, with the second highest incidence and third leading cause of cancer deaths worldwide. To individualise diagnosis, prognosis, and treatment of CRC, developing new strategies combining precision medicine and bioinformatic procedures is promising. Precision medicine is based on omics technologies and aims to individualise the management of CRC based on patient host genetic characteristics and microbiota. Bioinformatics is central to the application of personalised medicine because it enables the analysis of large datasets generated by these technologies. At the level of host genetics, bioinformatics allows the identification of mutations, genes, molecular pathways, biomarkers and drugs relevant to colorectal carcinogenesis. At the microbiota level, bioinformatics is fundamental to analysing microbial communities' composition and functionality and developing biomarkers and personalised microbiota-based therapies. This paper explores the host and microbiota genetic data analysis in CRC research.

Reference gene panel for urinary exosome-based molecular diagnostics in patients with kidney disease

BACKGROUND

Kidney disease is a severe complication of diabetes that often leads to end-stage renal disease. Early diagnosis is crucial for prevention or delay. However, the current diagnostic methods, with their limitations in detecting the disease in its early stages, underscore the urgency and importance of finding new solutions. miRNAs encapsulated inside urinary exosomes (UEs) have potential as early biomarkers for kidney diseases. The need for reference miRNAs for accurate interpretation currently limits their translational potential.

AIM

To identify consistently expressing reference miRNAs from UEs of controls and patients with type 2 diabetesmellitus (T2DM) and biopsy-confirmed kidney diseases.

METHODS

miRNA profiling was performed on UEs from 31 human urine samples using a rigorous and unbiased method. The UEs were isolated from urine samples collected from healthy individuals (n = 6), patients with T2DM (n = 13), and T2DM patients who also had kidney diseases (including diabetic nephropathy, n = 5; membranous nephropathy, n = 5; and IgA nephropathy, n = 2) through differential ultracentrifugation. After characterizing the UEs, miRNA expression profiling using microarray technology was conducted.

RESULTS

Microarray data analysis identified 14 miRNAs that were consistently expressed in UEs from 31 human samples, representing various kidney conditions: diabetic controls, diabetic nephropathy, membrane nephropathy, IgA nephropathy, and healthy controls. Through in silico analysis, we determined that 10 of these miRNAs had significant potential to serve as reference genes in UEs.

CONCLUSION

We identified uniformly expressing UE miRNAs that could serve as reference genes kidney disease biomarkers.

Circulating Exosomal miRNA Profiles in Non-Small Cell Lung Cancers

A growing number of studies have shown that microRNAs (miRNAs) can exert oncogenic or tumor suppressor activities in a variety of cancers, including lung cancer. Given their presence in exosome preparations, microRNA molecules may in fact participate in exosomal intercellular transfers and signaling. In the present study, we examined the profile of 25 circulating exosomal microRNAs in ostensibly healthy controls compared to patients with squamous cell lung cancers (SQCLC) or lung adenocarcinomas (LUAD). Eight miRNAs, namely, miR-21-5p, miR-126-3p, miR-210-3p, miR-221-3p, Let-7b-5p, miR-146a-5p, miR-222-3p, and miR-9-5p, were highly enriched in the cohort and selected for further analyses. All miRNAs were readily detected in non-small cell lung cancer (NSCLC) patients of both sexes at all cancer stages, and their levels in exosomes correlated with the clinicopathological characteristics of tumors. Thus, the presence of these miRNAs in circulating exosomes may contribute to the regulation of oncogenic activity in patients with NSCLC.

Multiomics integrated analysis and experimental validation identify TLR4 and ALOX5 as oxidative stress-related biomarkers in intracranial aneurysms

BACKGROUND

Intracranial aneurysm (IA) is a severe cerebrovascular disease, and effective gene therapy and drug interventions for its treatment are still lacking. Oxidative stress (OS) is closely associated with the IA, but the key regulatory genes involved are still unclear. Through multiomics analysis and experimental validation, we identified two diagnostic markers for IA associated with OS.

METHODS

In this study, we first analyzed the IA dataset GSE75436 and conducted a joint analysis of oxidative stress-related genes (ORGs). Differential analysis, functional enrichment analysis, immune infiltration, WGCNA, PPI, LASSO, and other methods were used to identify IA diagnostic markers related to OS. Next, the functions of TLR4 and ALOX5 expression in IA and their potential targeted therapeutic drugs were analyzed. We also performed single-cell sequencing of patient IA and control (superficial temporal artery, STA) tissues. 23,342 cells were captured from 2 IA and 3 STA samples obtained from our center. Cell clustering and annotation were conducted using R software to observe the distribution of TLR4 and ALOX5 expression in IAs. Finally, the expression of TLR4 and ALOX5 were validated in IA patients and in an elastase-induced mouse IA model using experiments such as WB and immunofluorescence.

RESULTS

Through bioinformatics analysis, we identified 16 key ORGs associated with IA pathogenesis. Further screening revealed that ALOX5 and TLR4 were highly expressed to activate a series of inflammatory responses and reduce the production of myocytes. Methotrexate (MTX) may be a potential targeted drug. Single-cell analysis revealed a notable increase in immune cells in the IA group, with ALOX5 and TLR4 primarily localized to monocytes/macrophages. Validation through patient samples and mouse models confirmed high expression of ALOX5 and TLR4 in IAs.

CONCLUSIONS

Bioinformatics analysis indicated that ALOX5 and TLR4 are the most significant ORGs associated with the pathogenesis of IA. Single-cell sequencing and experiments revealed that the high expression of ALOX5 and TLR4 are closely related to IA. These two genes are promising new targets for IA therapy.

Integrative study of chicken lung transcriptome to understand the host immune response during Newcastle disease virus challenge

Introduction

Newcastle disease is one of the significant issues in the poultry industry, having catastrophic effects worldwide. The lung is one of the essential organs which harbours Bronchus-associated lymphoid tissue and plays a vital role in the immune response. Leghorn and Fayoumi breeds are known to have differences in resistance to Newcastle disease. Along with genes and long non-coding RNAs (lncRNAs) are also known to regulate various biological pathways through gene regulation.

Methods

This study analysed the lung transcriptome data and identified the role of genes and long non-coding RNAs in differential immune resistance. The computational pipeline, FHSpipe, as used in our previous studies on analysis of harderian gland and trachea transcriptome was used to identify genes and lncRNAs. This was followed by differential expression analysis, functional annotation of genes and lncRNAs, identification of transcription factors, microRNAs and finally validation using qRT-PCR.

Results and discussion

A total of 8219 novel lncRNAs were identified. Of them, 1263 lncRNAs and 281 genes were differentially expressed. About 66 genes were annotated with either an immune-related GO term or pathway, and 12 were annotated with both. In challenge and breed-based analysis, most of these genes were upregulated in Fayoumi compared to Leghorn, and in timepoint-based analysis, Leghorn challenge chicken showed downregulation between time points. A similar trend was observed in the expression of lncRNAs. Co-expression analysis has revealed several lncRNAs co-expressing with immune genes with a positive correlation. Several genes annotated with non-immune pathways, including metabolism, signal transduction, transport of small molecules, extracellular matrix organization, developmental biology and cellular processes, were also impacted. With this, we can understand that Fayoumi chicken showed upregulated immune genes and positive cis-lncRNAs during both the non-challenged and NDV-challenge conditions, even without viral transcripts in the tissue. This finding shows that these immune-annotated genes and coexpressing cis-lncRNAs play a significant role in Fayoumi being comparatively resistant to NDV compared to Leghorn. Our study affirms and expands upon the outcomes of previous studies and highlights the crucial role of lncRNAs during the immune response to NDV.

Conclusion

This analysis clearly shows the differences in the gene expression patterns and lncRNA co-expression with the genes between Leghorn and Fayoumi, indicating that the lncRNAs and co-expressing genes might potentially have a role in differentiating these breeds. We hypothesise that these genes and lncRNAs play a vital role in the higher resistance of Fayoumi to NDV than Leghorn. This study can pave the way for future studies to unravel the biological mechanism behind the regulation of immune-related genes.

Maternal Plasma miRNAs as Early Biomarkers of Moderate-to-Late-Preterm Birth

Globally, preterm birth (PTB) is a primary cause of mortality and morbidity in infants, with PTB rates increasing worldwide over the last two decades. Biomarkers for accurate early prediction of PTB before the clinical event do not currently exist. Given their roles in the development and progression of many disease states, there has been increasing interest in the utility of microRNAs (miRNAs) as early biomarkers for pregnancy-related disorders, including PTB. The present study was designed to examine potential differences in miRNA abundances in maternal plasma from mothers with infants born following a moderate to late (28-36 weeks' gestation, n = 54) spontaneous PTB (SPTB) compared to mothers with matched term infants (n = 54). Maternal plasma collected at 15 weeks' gestation were utilised from the Auckland and Adelaide cohorts from the Screening for Pregnancy Endpoints (SCOPE) study. miRNAs in plasma were quantified using the NanoString nCounter expression panel (800 miRNAs). The top four most abundant miRNAs were significantly decreased in the plasma of mothers in the SPTB group with results consistent across both cohorts and pathway analysis was undertaken to examine the biological processes linked to the dysregulated miRNAs. The top candidate miRNAs (miRs-451a, -223-3p, let-7a-5p, and -126-3p) were linked to gene pathways associated with inflammation, apoptosis, and mitochondrial biogenesis. Moreover, miRNAs were consistently less abundant in the plasma of mothers of preterm infants across both sites, suggesting potential global dysregulation in miRNA biogenesis. This was supported by a significant downregulation in expression of key genes that are involved in miRNA biogenesis (DROSHA, DICER, and AGO2) across both sites in the SPTB group. In summary, the present study has identified miRNAs in maternal plasma that may provide predictive utility as early biomarkers for the risk of later SPTB. Importantly, these observations were conserved across two independent cohorts. Further, our data provide evidence for a persistent decrease in miRNA abundance in mothers who later experienced an SPTB, which is likely to have widespread consequences for gene regulation and epigenetic processes.

Identification of critical genes and metabolic pathways in rheumatoid arthritis and osteoporosis toward drug repurposing

BACKGROUND

Rheumatoid arthritis (RA) and osteoporosis (OP) are considered to be complex diseases. In recent studies, a positive association between RA and OP has been reported triggering growing research interest. This study aims to investigate the drugs related to critical genes in RA and OP, using bioinformatics approaches, toward drug repurposing.

METHOD

RA and OP genes were identified. The RA-OP PPI network was constructed and analyzed using the STRING and Cytoscape, respectively. Hub genes and modules were extracted and enriched Gene Ontology, through the WebGestalt and g:Profiler. The identification of the drugs related to critical genes using the DGIDB, and extracted the miRNAs using miRWalk and miRNet.

RESULTS

By network clustering, five significant modules were obtained that have important roles in the immune system. IL6, TNF, IL1B, STAT3, TGFB1, TP53, HIF1A, CCL2, IL10, and MMP9 were found as the top 10 hub genes in the RA-OP network. Hub genes were shown to have implications in inflammatory response, significant functions in cytokine receptor binding, and localized mostly in extracellular space. By investigating the drugs related to hub genes, 16 drugs were identified as repurposing candidate drugs. The 10 drugs included Hydroxychloroquine, Infliximab, Adalimumab, Etanercept, Certolizumab, Cyclosporine, Diacerein, Gevokizumab, Canakinumab, and Olokizumab proposed for OP. Also, six drugs including Pirfenidone, Pentoxifylline, Vadimezan, Rilonacept, Metelimumab, and Siltuximab have important roles in inflammatory control and were proposed for both RA and OP.

CONCLUSIONS

The results of the present study can provide novel insights into the pathogenesis and treatment of RA and OP.

Integrative in silico approaches to analyse microRNA-mediated responses in human diseases

Advancements in sequencing technologies have facilitated omics level information generation for various diseases in human. High-throughput technologies have become a powerful tool to understand differential expression studies and transcriptional network analysis. An understanding of complex transcriptional networks in human diseases requires integration of datasets representing different RNA species including microRNA (miRNA) and messenger RNA (mRNA). This review emphasises on conceptual explanation of generalized workflow and methodologies to the miRNA mediated responses in human diseases by using different in silico analysis. Although, there have been many prior explorations in miRNA-mediated responses in human diseases, the advantages, limitations and overcoming the limitation through different statistical techniques have not yet been discussed. This review focuses on miRNAs as important gene regulators in human diseases, methodologies for miRNA-target gene prediction and data driven methods for enrichment and network analysis for miRnome-targetome interactions. Additionally, it proposes an integrative workflow to analyse structural components of networks obtained from high-throughput data. This review explains how to apply the existing methods to analyse miRNA-mediated responses in human diseases. It addresses unique characteristics of different analysis, its limitations and its statistical solutions influencing the choice of methods for the analysis through a workflow. Moreover, it provides an overview of promising common integrative approaches to comprehend miRNA-mediated gene regulatory events in biological processes in humans. The proposed methodologies and workflow shall help in the analysis of multi-source data to identify molecular signatures of various human diseases.

Effects of pesticide exposure on the expression of selected genes in normal and cancer samples: Identification of predictive biomarkers for risk assessment

Pesticides pivotal in controlling pests, can represent a threat for human health. Regulatory agencies constantly monitor their harmful effects, regulating their use. Several studies support a positive association between long-term exposure to pesticides and chronic pathologies, such as cancer. Geno-toxicological biomonitoring has proven to be valuable to assess genetic risks associated with exposure to pesticides, representing a promising tool to improve preventive measures and identify workers at higher risk. In this study, a differential gene expression analysis of 70 candidate genes deregulated upon pesticide exposure, was performed in 10 GEO human gene expression DataSets. It was found that six genes (PMAIP1, GCLM, CD36, SQSTM1, ABCC3, NR4A2) had significant AUC predictive values. Also, CD36 was upregulated in non-transformed cell samples and healthy workers, but downregulated in cancer cells. Further validation in larger groups of workers will corroborate the importance of the identified candidates as biomarkers of exposure/effect.

High Serum miR-361-3p Predicts Early Postdischarge Infections after Autologous Stem Cell Transplantation

BACKGROUND

Autologous hematopoietic stem cell transplantation (AHSCT) is currently the backbone of the treatment of multiple myeloma (MM) and relapsed and refractory lymphomas. Notably, infections contribute to over 25% of fatalities among AHSCT recipients within the initial 100 days following the procedure. In this study, we aimed to evaluate three selected miRNAs: hsa-miR-155-5p, hsa-miR-320c, and hsa-miR-361-3p, in identifying AHSCT recipients at high risk of infectious events up to 100 days post-transplantation after discharge.

MATERIALS AND METHODS

The study group consisted of 58 patients (43 with MM, 15 with lymphoma) treated with AHSCT. Blood samples were collected from all patients at the same time point: on day +14 after transplantation.

RESULTS

Fifteen patients (25.9%) experienced infectious complications after post-transplant discharge within the initial +100 days post-transplantation. The median time to infection onset was 44 days (interquartile range, 25-78). Four patients required hospitalization due to severe infection. High expression of hsa-miR-361-3p (fold change [FC], 1.79; P=0.0139) in the patients experiencing infectious complications and overexpression of hsa-miR-320c (FC, 2.14; P<0.0001) in patients requiring hospitalization were observed. In the multivariate model, both lymphoma diagnosis (odds ratio [OR], 6.88; 95% confidence interval [CI], 1.55-30.56; P=0.0112) and high expression of hsa-miR-361-3p (OR, 3.00; 95% CI, 1.40-6.41; P=0.0047) were independent factors associated with post-discharge infectious complications occurrence. Our model in 10-fold cross-validation preserved its diagnostic potential with an area under the receiver operating characteristic curve of 0.78 (95% CI, 0.64-0.92).

CONCLUSION

Elevated serum hsa-miR-361-3p emerges as a promising biomarker for identifying patients at risk of infection during the early post-discharge period, potentially offering optimization of the prophylactic use of antimicrobial agents tailored to the specific risk profile of each AHSCT recipient.

Differential levels of circulating RNAs prior to endometrial cancer diagnosis

Endometrial cancer (EC) is one of the most common female cancers and there is currently no routine screening strategy for early detection. An altered abundance of circulating microRNAs (miRNAs) and other RNA classes have the potential as early cancer biomarkers. We analyzed circulating RNA levels using small RNA sequencing, targeting RNAs in the size range of 17-47 nucleotides, in EC patients with samples collected prior to diagnosis compared to cancer-free controls. The analysis included 316 cases with samples collected 1-11 years prior to EC diagnosis, and 316 matched controls, both from the Janus Serum Bank cohort in Norway. We identified differentially abundant (DA) miRNAs, isomiRs, and small nuclear RNAs between EC cases and controls. The top EC DA miRNAs were miR-155-5p, miR-200b-3p, miR-589-5p, miR-151a-5p, miR-543, miR-485-5p, miR-625-p, and miR-671-3p. miR-200b-3p was previously reported to be among one of the top miRNAs with higher abundance in EC cases. We observed 47, 41, and 32 DA miRNAs for EC interacting with BMI, smoking status, and physical activity, respectively, including two miRNAs (miR-223-3p and miR-29b-3p) interacting with all three factors. The circulating RNAs are altered and show temporal dynamics prior to EC diagnosis. Notably, DA miRNAs for EC had the lowest q-value 4.39-6.66 years before diagnosis. Enrichment analysis of miRNAs showed that signaling pathways Fc epsilon RI, prolactin, toll-like receptor, and VEGF had the strongest associations.

In-silico identification and functional characterization of common genes associated with type 2 diabetes and hypertension

Type 2 diabetes (T2D) and hypertension are global public health concerns and major metabolic disorders in humans. Experimental evidence indicates considerable hereditary influences on the etiology of T2D and hypertension, but the molecular basis of these diseases is still limited. Thus, the current study analyzed 185 (132 T2D and 53 hypertension) GWAS catalog datasets and identified 83 common genes linked to T2D and hypertension pathogenesis. These genes were further examined using various bioinformatics approaches to elucidate their molecular mechanisms underlying the pathophysiology of T2D and hypertension. Gene ontology (GO) analysis revealed the biological, cellular, and molecular functions of these genes, which were also linked to different T2D and hypertension pathways. Specifically, seven genes were found to be crucial for T2D, and nine were directly associated with hypertension. Protein-protein interaction (PPI) analysis identified 28 candidate genes and seven hub genes through 11 topological methods. Among 231 miRNAs, seven were significant in interacting with the hub genes, and nine transcription factors (TFs) out of 36 were linked to these hub genes. Additionally, two of the seven hub genes were downregulated by 43 FDA-approved drugs. These findings elucidate the molecular processes underlying T2D and hypertension, suggesting that targeting these genes could lead to future drug development and therapeutic strategies to treat T2D and hypertension.

Global microRNA profiling of bone marrow-MSC derived extracellular vesicles identifies miRNAs associated with hematopoietic dysfunction in aplastic anemia

Recently, we have reported that extracellular vesicles (EVs) from the bone marrow mesenchymal stromal cells (BM-MSC) of aplastic anemia (AA) patients inhibit hematopoietic stem and progenitor cell (HSPC) proliferative and colony-forming ability and promote apoptosis. One mechanism by which AA BM-MSC EVs might contribute to these altered HSPC functions is through microRNAs (miRNAs) encapsulated in EVs. However, little is known about the role of BM-MSC EVs derived miRNAs in regulating HSPC functions in AA. Therefore, we performed miRNA profiling of EVs from BM-MSC of AA (n = 6) and normal controls (NC) (n = 6) to identify differentially expressed miRNAs. The Integrated DEseq2 analysis revealed 34 significantly altered mature miRNAs, targeting 235 differentially expressed HSPC genes in AA. Hub gene analysis revealed 10 HSPC genes such as IGF-1R, IGF2R, PAK1, PTPN1, etc., which are targeted by EV miRNAs and had an enrichment of chemokine, MAPK, NK cell-mediated cytotoxicity, Rap1, PI3k-Akt, mTOR signalling pathways which are associated with hematopoietic homeostasis. We further showed that miR-139-5p and its target, IGF-1R (hub-gene), might regulate HSPC proliferation and apoptosis, which may serve as potential therapeutic targets in AA. Overall, the study highlights that AA BM-MSC EV miRNAs could contribute to impaired HSPC functions in AA.

Circulating cell-free and extracellular vesicles-derived microRNA as prognostic biomarkers in patients with early-stage NSCLC: results from RESTING study

BACKGROUND

Factors to accurately stratify patients with early-stage non-small cell lung cancer (NSCLC) in different prognostic groups are still needed. This study aims to investigate 1) the prognostic potential of circulating cell-free (CF) and extracellular vesicles (EVs)-derived microRNA (miRNAs), and 2) their added value with respect to known prognostic factors (PFs).

METHODS

The RESTING study is a multicentre prospective observational cohort study on resected stage IA-IIIA patients with NSCLC. The primary end-point was disease-free survival (DFS), and the main analyses were carried out separately for CF- and EV-miRNAs. CF- and EV-miRNAs were isolated from plasma, and miRNA-specific libraries were prepared and sequenced. To reach the study aims, three statistical models were specified: one using the miRNA data only (Model 1); one using both miRNAs and known PFs (age, gender, and pathological stage) (Model 2), and one using the PFs alone (Model 3). Five-fold cross-validation (CV) was used to assess the predictive performance of each. Standard Cox regression and elastic net regularized Cox regression were used.

RESULTS

A total of 222 patients were enrolled. The median follow-up time was 26.3 (95% CI 25.4-27.6) months. From Model 1, three CF-miRNAs and 21 EV-miRNAs were associated with DFS. In Model 2, two CF-miRNAs (miR-29c-3p and miR-877-3p) and five EV-miRNAs (miR-181a-2-3p, miR-182-5p, miR-192-5p, miR-532-3p and miR-589-5p) remained associated with DFS. From pathway enrichment analysis, TGF-beta and NOTCH were the most involved pathways.

CONCLUSION

This study identified promising prognostic CF- and EV-miRNAs that could be used as a non-invasive, cost-effective tool to aid clinical decision-making. However, further evaluation of the obtained miRNAs in an external cohort of patients is warranted.

MicroRNA dysregulation in ataxia telangiectasia

Introduction

Ataxia telangiectasia (AT) is a rare disorder characterized by neurodegeneration, combined immunodeficiency, a predisposition to malignancies, and high clinical variability. Profiling of microRNAs (miRNAs) may offer insights into the underlying mechanisms of complex rare human diseases, as miRNAs play a role in various biological functions including proliferation, differentiation, and DNA repair. In this study, we investigate the differential expression of miRNAs in samples from AT patients to identify miRNA patterns and analyze how these patterns are related to the disease.

Methods

We enrolled 20 AT patients (mean age 17.7 ± 9.6 years old) and collected clinical and genetic data. We performed short non-coding RNA-seq analysis on peripheral blood mononuclear cells (PBMCs) and fibroblasts to compare the miRNA expression profile between AT patients and controls.

Results

We observed 42 differentially expressed (DE)-miRNAs in blood samples and 26 in fibroblast samples. Among these, three DE-miRNAs, miR-342-3p, miR-30a-5p, and miR-195-5p, were further validated in additional AT samples, confirming their dysregulation.

Discussion

We identified an AT-related miRNA signature in blood cells and fibroblast samples collected from a group of AT patients. We also predicted several dysregulated pathways, primarily related to cancer, immune system control, or inflammatory processes. The findings suggest that miRNAs may provide insights into the pathophysiology and tumorigenesis of AT and have the potential to serve as useful biomarkers in cancer research.

Circulating microRNAs as biomarkers for stratifying different phases of liver cancer progression and response to therapy

Hepatocellular carcinoma (HCC) is the most common liver cancer and is among the leading causes of cancer-related death worldwide. There is no reliable biomarker for the early diagnosis of HCC. Circulating microRNAs (miRNAs) have attracted attention as potential biomarkers of disease. By small-RNA next-generation sequencing, the analysis of serum miRNAs led to the identification of molecular signatures able to discriminate advanced HCC from early HCC (n = 246); advanced HCC from CIRRHOSIS (n = 299); advanced HCC from HEALTHY (n = 320); HEALTHY from early HCC (n = 343); and HEALTHY from CIRRHOSIS (n = 414). Cirrhotic patients and early HCC patients exhibited similar serum miRNA profiles, yet a small number of miRNAs (n = 57) were able to distinguish these two classes of patients. A second objective of the study was to identify serum miRNAs capable of predicting the response to therapy in patients with advanced HCC. All patients were treated with sorafenib as first-line therapy: 24 were nonresponsive and 24 responsive. Analysis of circulating miRNAs revealed a 54 miRNAs signature able to separate the two subgroups. This study suggested that circulating miRNAs could be useful biomarkers for monitoring patients with liver diseases ranging from cirrhosis to advanced HCC and possibly predicting susceptibility to first-line treatment based on sorafenib.

Computational Analyses Reveal Deregulated Clock Genes Associated with Breast Cancer Development in Night Shift Workers

Breast cancer (BC) is the leading cause of cancer death among women worldwide. Women employed in shift jobs face heightened BC risk due to prolonged exposure to night shift work (NSW), classified as potentially carcinogenic by the International Agency for Research on Cancer (IARC). This risk is linked to disruptions in circadian rhythms governed by clock genes at the cellular level. However, the molecular mechanisms are unclear. This study aimed to assess clock genes as potential BC biomarkers among women exposed to long-term NSW. Clock gene expression was analysed in paired BC and normal breast tissues within Nurses' Health Studies I and II GEO datasets. Validation was performed on additional gene expression datasets from healthy night shift workers and women with varying BC susceptibility, as well as single-cell sequencing datasets. Post-transcriptional regulators of clock genes were identified through miRNA analyses. Significant alterations in clock gene expression in BC compared to normal tissues were found. BHLHE40, CIART, CLOCK, PDPK1, and TIMELESS were over-expressed, while HLF, NFIL3, NPAS3, PER1, PER3, SIM1, and TEF were under-expressed. The downregulation of PER1 and TEF and upregulation of CLOCK correlated with increased BC risk in healthy women. Also, twenty-six miRNAs, including miR-10a, miR-21, miR-107, and miR-34, were identified as potential post-transcriptional regulators influenced by NSW. In conclusion, a panel of clock genes and circadian miRNAs are suggested as BC susceptibility biomarkers among night shift workers, supporting implications for risk stratification and early detection strategies.

Divergent Processing of Cell Stress Signals as the Basis of Cancer Progression: Licensing NFκB on Chromatin

Inflammation is activated by diverse triggers that induce the expression of cytokines and adhesion molecules, which permit a succession of molecules and cells to deliver stimuli and functions that help the immune system clear the primary cause of tissue damage, whether this is an infection, a tumor, or a trauma. During inflammation, short-term changes in the expression and secretion of strong mediators of inflammation occur, while long-term changes occur to specific groups of cells. Long-term changes include cellular transdifferentiation for some types of cells that need to regenerate damaged tissue, as well as death for specific immune cells that can be detrimental to tissue integrity if they remain active beyond the boundaries of essential function. The transcriptional regulator NFκB enables some of the fundamental gene expression changes during inflammation, as well as during tissue development. During recurrence of malignant disease, cell stress-induced alterations enable the growth of cancer cell clones that are substantially resistant to therapeutic intervention and to the immune system. A number of those alterations occur due to significant defects in feedback signal cascades that control the activity of NFκB. Specifically, cell stress contributes to feedback defects as it overrides modules that otherwise control inflammation to protect host tissue. NFκB is involved in both the suppression and promotion of cancer, and the key distinctive feature that determines its net effect remains unclear. This paper aims to provide a clear answer to at least one aspect of this question, namely the mechanism that enables a divergent response of cancer cells to critical inflammatory stimuli and to cell stress in general.

Analysis of miR-497/195 cluster identifies new therapeutic targets in cervical cancer

OBJECTIVE

miR-497/195, located at 17p13.1, is a highly conserved miRNA cluster whose abnormal expression is a key regulator of carcinogenesis. We performed a comprehensive analysis of the miR-497/195 cluster to determine its prognostic utility and role in cervical cancer (CC) using publicly available datasets.

RESULTS

In silico analysis and validation revealed that this cluster is downregulated in CC. A total of 60 target genes of miR-497/195 cluster were identified as differentially expressed between normal and CC samples. ShinyGO, STRING, CytoHubba, Timer 2.0, HPA, and HCMBD were used for functional enrichment, PPIN network construction, hub gene identification, immune infiltration correlation, histopathological expression, and determination of the metastatic potential of miR-497/195 cluster and their target genes. PPIN analysis identified CCNE1, CCNE2, ANLN, RACGAP1, KIF23, CHEK1, CDC25A, E2F7, CDK1, and CEP55 as the top 10 hub genes (HGs). Furthermore, the upregulation of RECK, ATD5, and BCL2, downregulation of OSBPL3, RCAN3, and HIST1H3H effected overall survival of CC patients. We identified 6 targets (TFAP2A, CLSPN, RASEF, HIST1H3H, AKT3, and ITPR1) of miR-497/195 cluster to influence metastasis. In addition, 8 druggable genes and 38 potential drugs were also identified. Our study identified miR-497/195 cluster target genes and pathways that could be used for prognostic and therapeutic applications in CC.

Explicate molecular landscape of combined pulmonary fibrosis and emphysema through explainable artificial intelligence: a comprehensive analysis of ILD and COPD interactions using RNA from whole lung homogenates

Combined pulmonary fibrosis and emphysema (CPFE) presents a unique challenge in respiratory disorders, merging features of interstitial lung disease (ILD) and chronic obstructive pulmonary disease (COPD). Using the random forest algorithm, our study thoroughly examines the molecular details of CPFE. Analyzing gene expression datasets from GSE47460 (ILD: 254, COPD: 220, control: 108), we identify key genes namely ADRB2, CDH3, IRS2, MATN3, CD38, PDIA4, VEGFC, and among twenty others, crucial in airway regulation, lung function, and apoptosis, shaping the complex pathogenesis of CPFE. Additionally, miRNAs (hsa-mir-101-3p, hsa-mir-1343-3p, hsa-mir-27a-3p, and miR-16-5p) showcase regulatory impacts on CPFE-related molecular pathways. Our machine learning model unveils these intricate interactions, offering a comprehensive insight into CPFE's molecular mechanisms. This research not only pinpoints potential therapeutic targets and biomarkers but also opens avenues for innovative approaches in managing CPFE, linking ILD and COPD within this complex respiratory condition.

Identification of circulating miRNA biomarkers in leptospirosis for early detection: A promising diagnostic approach

Leptospirosis is a zoonotic disease of global significance, contributing to morbidity and mortality worldwide. It is endemic to tropical regions, with outbreaks during monsoons. The disease manifestations are similar to that of other febrile illness such as dengue, malaria hence often misdiagnosed and underreported. The zoonoses if undetected, progresses to cause severe life-threatening complications also known as Weil's disease. Routine diagnostic tests are based on the detection of antibodies in patient serum and are not accurate during the initial phase of the infection. Therefore, it is necessary to detect novel biomarkers that can be used in early detection of leptospirosis. Circulating miRNAs are known to be promising biomarkers for various diseases including cancer, tuberculosis, influenza; hence in this study the potential of miRNAs as biomarkers for leptospirosis was evaluated. A total of 30 leptospirosis cases were screened for the differential expression of 10 miRNA by RT-qPCR assay. The differential expression was calculated by relative quantification using healthy individuals as controls. Among the 10 miRNA,3 miRNA, miR-28-5p, miR-302c-3p and miR-302a-3p were reported to exhibit a significant trend of upregulation. Further their role in immune pathways and biological processes was investigated by KEGG analysis and Gene Ontology. The 3 miRNAs were observed to target various immune response pathways, thus confirming their role in host immune response. Based on the results obtained in this study, miR-28-5p, miR-302c-3p and miR-302a-3p can be considered as potential biomarkers for the detection of leptospirosis.

Induction of let-7d-5p miRNA modulates aortic smooth muscle inflammatory signaling and phenotypic switching

BACKGROUND AND AIMS

Activation of vascular smooth muscle cell inflammation is recognised as an important early driver of vascular disease. We have previously identified the let-7 miRNA family as important regulators of inflammation in in vitro and in vivo models of atherosclerosis. Here we investigated a dual statin/let-7d-5p miRNA combination therapy approach to target human aortic SMC (HAoSMC) activation and inflammation.

METHODS

In vitro studies using primary HAoSMCs were performed to investigate the effects of let-7d-5p miRNA overexpression and inhibition. HAoSMCs were treated with combinations of the inflammatory cytokine tumor necrosis factor-α (TNF-α), and atorvastatin or lovastatin. HAoSMC Bulk RNA-seq transcriptomics of HAoSMCs revealed downstream regulatory networks modulated by let-7d-5p miRNA overexpression and statins. Proteome profiler cytokine array, Western blotting and quantitative PCR analyses were performed on HAoSMCs to validate key findings.

RESULTS

Let-7d-5p overexpression significantly attenuated TNF-α-induced upregulation of IL-6, ICAM1, VCAM1, CCL2, CD68, MYOCD gene expression in HAoSMCs (p<0.05). Statins (atorvastatin, lovastatin) significantly attenuated inflammatory gene expression and upregulated Let-7d levels in HAoSMCs (p<0.05). Bulk RNA-seq analysis of a dual Let-7d-5p overexpression/statin therapy in HAoSMCs revealed that let-7d-5p activation and statins converge on key inflammatory pathways (IL-6, IL-1β, TNF-α, IFN-γ). Let-7d-5p overexpression led to reduced expression of the ox-LDL receptor OLR1, and this was associated with lower ox-LDL uptake in HAoSMCs. In silico analysis of smooth muscle cell phenotypic switching shows that overexpression of let-7d-5p in HAoSMCs maintains a contractile phenotype.

CONCLUSIONS

Targeting the Let-7 network alongside statins can modulate HAoSMC activation and attenuate key inflammatory pathway signals.

COPS: A novel platform for multi-omic disease subtype discovery via robust multi-objective evaluation of clustering algorithms

Recent research on multi-view clustering algorithms for complex disease subtyping often overlooks aspects like clustering stability and critical assessment of prognostic relevance. Furthermore, current frameworks do not allow for a comparison between data-driven and pathway-driven clustering, highlighting a significant gap in the methodology. We present the COPS R-package, tailored for robust evaluation of single and multi-omics clustering results. COPS features advanced methods, including similarity networks, kernel-based approaches, dimensionality reduction, and pathway knowledge integration. Some of these methods are not accessible through R, and some correspond to new approaches proposed with COPS. Our framework was rigorously applied to multi-omics data across seven cancer types, including breast, prostate, and lung, utilizing mRNA, CNV, miRNA, and DNA methylation data. Unlike previous studies, our approach contrasts data- and knowledge-driven multi-view clustering methods and incorporates cross-fold validation for robustness. Clustering outcomes were assessed using the ARI score, survival analysis via Cox regression models including relevant covariates, and the stability of the results. While survival analysis and gold-standard agreement are standard metrics, they vary considerably across methods and datasets. Therefore, it is essential to assess multi-view clustering methods using multiple criteria, from cluster stability to prognostic relevance, and to provide ways of comparing these metrics simultaneously to select the optimal approach for disease subtype discovery in novel datasets. Emphasizing multi-objective evaluation, we applied the Pareto efficiency concept to gauge the equilibrium of evaluation metrics in each cancer case-study. Affinity Network Fusion, Integrative Non-negative Matrix Factorization, and Multiple Kernel K-Means with linear or Pathway Induced Kernels were the most stable and effective in discerning groups with significantly different survival outcomes in several case studies.

Integrated Bioinformatics-Based Identification and Validation of Neuroinflammation-Related Hub Genes in Primary Open-Angle Glaucoma

Glaucoma is a leading cause of permanent blindness, affecting 80 million people worldwide. Recent studies have emphasized the importance of neuroinflammation in the early stages of glaucoma, involving immune and glial cells. To investigate this further, we used the GSE27276 dataset from the GEO (Gene Expression Omnibus) database and neuroinflammation genes from the GeneCards database to identify differentially expressed neuroinflammation-related genes associated with primary open-angle glaucoma (POAG). Subsequently, these genes were submitted to Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes for pathway enrichment analyses. Hub genes were picked out through protein-protein interaction networks and further validated using the external datasets (GSE13534 and GSE9944) and real-time PCR analysis. The gene-miRNA regulatory network, receiver operating characteristic (ROC) curve, genome-wide association study (GWAS), and regional expression analysis were performed to further validate the involvement of hub genes in glaucoma. A total of 179 differentially expressed genes were identified, comprising 60 upregulated and 119 downregulated genes. Among them, 18 differentially expressed neuroinflammation-related genes were found to overlap between the differentially expressed genes and neuroinflammation-related genes, with six genes (SERPINA3, LCN2, MMP3, S100A9, IL1RN, and HP) identified as potential hub genes. These genes were related to the IL-17 signaling pathway and tyrosine metabolism. The gene-miRNA regulatory network showed that these hub genes were regulated by 118 miRNAs. Notably, GWAS data analysis successfully identified significant single nucleotide polymorphisms (SNPs) corresponding to these six hub genes. ROC curve analysis indicated that our genes showed significant accuracy in POAG. The expression of these genes was further confirmed in microglia, Müller cells, astrocytes, and retinal ganglion cells in the Spectacle database. Moreover, three hub genes, SERPINA3, IL1R1, and LCN2, were validated as potential diagnostic biomarkers for high-risk glaucoma patients, showing increased expression in the OGD/R-induced glaucoma model. This study suggests that the identified hub genes may influence the development of POAG by regulation of neuroinflammation, and it may offer novel insights into the management of POAG.

Plasma and Myocardial miRNomes Similarities and Differences during Cardiac Remodelling and Reverse Remodelling in a Murine Model of Heart Failure with Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome characterised by multiple risk factors touching various organs outside the heart. Using a murine HFpEF model, we studied cardiac reverse remodelling (RR) after stopping the causing metabolic-hypertensive stress (MHS; Angiotensin II [AngII] and a high-fat diet [HFD]) after 28 days and introducing voluntary exercise (VE) for four more weeks. We measured the effects of MHS and RR on the plasma and myocardial microRNA (miR) profile (miRNome) to characterise better cardiac and non-cardiac responses to HFpEF-inducing risk factors and their reversibility. AngII alone, the HFD or the MHS caused cardiac hypertrophy (CH), left ventricular (LV) concentric remodelling and left atrial enlargement in females. Only AngII and the MHS, but not HFD, did in males. After RR, CH, LV concentric remodelling and atrial enlargement were normalised. Among the 25 most abundant circulating miRs, 10 were modulated by MHS. Plasma miRNomes from AngII, HFD or MHS mice shared 31 common significantly modulated miRs (24 upregulated and 7 downregulated), suggesting that the response of organs producing the bulk of those circulating miRs was similar even for seemingly different stress. In the LV, 19 out of 25 most expressed miRs were modulated. RR restored normality for the plasma miRNome but not for the LV miRNome, which remained mostly unchanged. Our results suggest that abnormalities persist in the myocardium of the HFpEF mice and that the normalisation of circulatory markers may be falsely reassuring after recovery.

Transcriptomic analyses of differentially expressed human genes, micro RNAs and long-non-coding RNAs in severe, symptomatic and asymptomatic malaria infection

Malaria transmission and endemicity in Africa remains hugely disproportionate compared to the rest of the world. The complex life cycle of P. falciparum (Pf) between the vertebrate human host and the anopheline vector results in differential expression of genes within and between hosts. An in-depth understanding of Pf interaction with various human genes through regulatory elements will pave way for identification of newer tools in the arsenal for malaria control. Therefore, the regulatory elements (REs) involved in the over- or under-expression of various host immune genes hold the key to elucidating alternative control measures that can be applied for disease surveillance, prompt diagnosis and treatment. We carried out an RNAseq analysis to identify differentially expressed genes and network elucidation of non-coding RNAs and target genes associated with immune response in individuals with different clinical outcomes. Raw RNAseq datasets, retrieved for analyses include individuals with severe (Gambia-20), symptomatic (Burkina Faso-15), asymptomatic (Mali-16) malaria as well as uninfected controls (Tanzania-20; Mali-36). Of the total 107 datasets retrieved, we identified 5534 differentially expressed genes (DEGs) among disease and control groups. A peculiar pattern of DEGs was observed, with individuals presenting with severe/symptomatic malaria having the highest and most diverse upregulated genes, while a reverse phenomenon was recorded among asymptomatic and uninfected individuals. In addition, we identified 141 differentially expressed micro RNA (miRNA), of which 78 and 63 were upregulated and downregulated respectively. Interactome analysis revealed a moderate interaction between DEGs and miRNAs. Of all identified miRNA, five were unique (hsa-mir-32, hsa-mir-25, hsa-mir-221, hsa-mir-29 and hsa-mir-148) because of their connectivity to several genes, including hsa-mir-221 connected to 16 genes. Six-hundred and eight differentially expressed long non coding RNA (lncRNA) were also identified, including SLC7A11, LINC01524 among the upregulated ones. Our study provides important insight into host immune genes undergoing differential expression under different malaria conditions. It also identified unique miRNAs and lncRNAs that modify and/or regulate the expression of various immune genes. These regulatory elements we surmise, have the potential to serve a diagnostic purpose in discriminating between individuals with severe/symptomatic malaria and those with asymptomatic infection or uninfected, following further clinical validation from field isolates.

In-silico analysis of cattle blood transcriptome to identify lncRNAs and their role during bovine tuberculosis

Long noncoding RNAs (lncRNAs) are RNA molecules with a length greater than 200 nucleotides that do not code for functional proteins. Although, genes play a vital role in immune response against a disease, it is less known that lncRNAs also contribute through gene regulation. Bovine tuberculosis is a significant zoonotic disease caused by Mycobacterium bovis (M. bovis) in cattle. Here, we report the in-silico analysis of the publicly available transcriptomic data of calves infected with M. bovis. A total of 51,812 lncRNAs were extracted across all the samples. A total of 216 genes and 260 lncRNAs were found to be differentially expressed across all the 4 conditions-infected vs uninfected at 8- and 20-week post-infection (WPI), 8 vs 20-WPI of both infected and uninfected. Gene Ontology and Functional annotation showed that 8 DEGs were annotated with immune system GOs and 2 DEGs with REACTOME immune system pathways. Co-expression analysis of DElncRNAs with DEGs revealed the involvement of lncRNAs with the genes annotated with Immune related GOs and pathways. Overall, our study sheds light on the dynamic transcriptomic changes in response to M. bovis infection, particularly highlighting the involvement of lncRNAs with immune-related genes. The identified immune pathways and gene-lncRNA interactions offer valuable insights for further research in understanding host-pathogen interactions and potential avenues for genetic improvement strategies in cattle.

Octadecaneuropeptide, ODN, Promotes Cell Survival against 6-OHDA-Induced Oxidative Stress and Apoptosis by Modulating the Expression of miR-34b, miR-29a, and miR-21in Cultured Astrocytes

Astrocytes specifically synthesize and release endozepines, a family of regulatory peptides including octadecaneuropeptide (ODN). We have previously reported that ODN rescues neurons and astrocytes from 6-OHDA-induced oxidative stress and cell death. The purpose of this study was to examine the potential implication of miR-34b, miR-29a, and miR-21 in the protective activity of ODN on 6-OHDA-induced oxidative stress and cell death in cultured rat astrocytes. Flow cytometry analysis showed that 6-OHDA increased the number of early apoptotic and apoptotic dead cells while treatment with the subnanomolar dose of ODN significantly reduced the number of apoptotic cells induced by 6-OHDA. 6-OHDA-treated astrocytes exhibited the over-expression of miR-21 (+118%) associated with a knockdown of miR-34b (-61%) and miR-29a (-49%). Co-treatment of astrocytes with ODN blocked the 6-OHDA-stimulated production of ROS and NO and stimulation of Bax and caspase-3 gene transcription. Concomitantly, ODN down-regulated the expression of miR-34b and miR-29a and rescued the 6-OHDA-associated reduced expression of miR21, indicating that ODN regulates their expression during cell death. Transfection with miR-21-3p inhibitor prevented the effect of 6-OHDA against cell death. In conclusion, our study indicated that (i) the expression of miRNAs miR-34b, miR-29a, and miR-21 is modified in astrocytes under 6-OHDA injury and (ii) that ODN prevents this deregulation to induce its neuroprotective action. The present study identified miR-21 as an emerging candidate and as a promising pharmacological target that opens new neuroprotective therapeutic strategies in neurodegenerative diseases, especially in Parkinson's disease.

Novel Diagnostic Biomarkers Related to Necroptosis and Immune Infiltration in Coronary Heart Disease

Purpose

Necroptosis, a monitored form of inflammatory cell death, contributes to coronary heart disease (CHD) progression. This study examined the potential of using necroptosis genes as diagnostic markers for CHD and sought to elucidate the underlying roles.

Methods

Through bioinformatic analysis of GSE20680 and GSE20681, we first identified the differentially expressed genes (DEGs) related to necroptosis in CHD. Hub genes were identified using least absolute shrinkage and selection operator (LASSO) regression and random forest analysis after studying immune infiltration and transcription factor-miRNA interaction networks according to the DEGs. Quantitative polymerase chain reaction and immunohistochemistry were used to further investigate hub gene expression in vivo, for which a diagnostic model was constructed and the predictive efficacy was validated. Finally, the CHD group was categorized into high- and low-score groups in accordance with the single-sample gene set enrichment analysis (ssGSEA) score of the necroptosis genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, GSEA, and further immune infiltration analyses were performed on the two groups to explore the possible roles of hub genes.

Results

Based on the results of the LASSO regression and random forest analyses, four genes were used to construct a diagnostic model to establish a nomogram. Additionally, an extensive analysis of all seventeen necroptosis genes revealed notable distinctions in expression between high-risk and low-risk groups. Evaluation of immune infiltration revealed that neutrophils, monocytes, B cells, and activated dendritic cells were highly distributed in the peripheral blood of patients with CHD. Specifically, the high CHD score group exhibited greater neutrophil and monocyte infiltration. Conversely, the high-score group showed lower infiltration of M0 and M2 macrophages, CD8+ T, plasma, and resting mast cells.

Conclusion

TLR3, MLKL, HMGB1, and NDRG2 may be prospective biomarkers for CHD diagnosis. These findings offer plausible explanations for the role of necroptosis in CHD progression through immune infiltration and inflammatory response.

Identification of miRNAs Present in Cell- and Plasma-Derived Extracellular Vesicles-Possible Biomarkers of Colorectal Cancer

Globally, an increasing prevalence of colorectal cancer (CRC) prompts a need for the development of new methods for early tumor detection. MicroRNAs (also referred to as miRNAs) are short non-coding RNA molecules that play a pivotal role in the regulation of gene expression. MiRNAs are effectively transferred to extracellular vesicle (EVs) membrane sacs commonly released by cells. Our study aimed to examine the expression of miRNAs in four CRC cell lines and EVs derived from them (tumor EVs) in comparison to the normal colon epithelium cell line and its EVs. EVs were isolated by ultracentrifugation from the culture supernatant of SW480, SW620, SW1116, HCT116 and normal CCD841CoN cell lines and characterized according to the MISEV2023 guidelines. MiRNAs were analyzed by small RNA sequencing and validated by quantitative PCR. The performed analysis revealed 22 common miRNAs highly expressed in CRC cell lines and effectively transferred to tumor EVs, including miR-9-5p, miR-182-5p, miR-196b-5p, miR-200b-5p, miR-200c-3p, miR-425-5p and miR-429, which are associated with development, proliferation, invasion and migration of colorectal cancer cells, as well as in vesicle maturation and transport-associated pathways. In parallel, normal cells expressed miRNAs, such as miR-369 and miR-143, which play a role in proinflammatory response and tumor suppression. The analysis of selected miRNAs in plasma-derived EVs and tumor samples from CRC patients showed the similarity of miRNA expression profile between the patients' samples and CRC cell lines. Moreover, miR-182-5p, miR-196-5p, miR-425-5p and miR-429 were detected in several EV samples isolated from patients' plasma. Our results suggest that miR-182-5p, miR-196b-5p and miR-429 are differentially expressed between EVs from CRC patients and healthy donors, which might have clinical implications.

Expression and Functional Analysis of Immuno-Micro-RNAs mir-146a and mir-326 in Colorectal Cancer

Micro-RNAs (miRNAs) are non-coding RNAs with importance in the development of cancer. They are involved in both tumor development and immune processes in tumors. The present study aims to characterize the behavior of two miRNAs, the proinflammatory miR-326-5p and the anti-inflammatory miR-146a-5p, in colorectal cancer (CRC), to decipher the mechanisms that regulate their expression, and to study potential applications. Tissue levels of miR-326-5p and miR-146a-5p were determined by qrt-PCR (real-time quantitative reverse transcription polymerase chain reaction) in 45 patients with colorectal cancer in tumoral and normal adjacent tissue. Subsequent bioinformatic analysis was performed to characterize the transcriptional networks that control the expression of the two miRNAs. The biomarker potential of miRNAs was assessed. The expression of miR-325-5p and miR-146a-5p was decreased in tumors compared to normal tissue. The two miRNAs are regulated through a transcriptional network, which originates in the inflammatory and proliferative pathways and regulates a set of cellular functions related to immunity, proliferation, and differentiation. The miRNAs coordinate distinct modules in the network. There is good biomarker potential of miR-326 with an AUC (Area under the curve) of 0.827, 0.911 sensitivity (Sn), and 0.689 specificity (Sp), and of the combination miR-326-miR-146a, with an AUC of 0.845, Sn of 0.75, and Sp of 0.89. The miRNAs are downregulated in the tumor tissue. They are regulated by a transcriptional network in which they coordinate distinct modules. The structure of the network highlights possible therapeutic approaches. MiR-326 and the combination of the two miRNAs may serve as biomarkers in CRC.

A prospective study of the proteome of equine pre-implantation embryo

The present study was conducted to investigate the global proteome of 8-day-old equine blastocysts. Follicular dynamics of eight adult mares were monitored by ultrasonography and inseminated 24 h after the detection of a preovulatory follicle. Four expanded blastocysts were recovered, pooled, and subjected to protein extraction and mass spectrometry. Protein identification was conducted based on four database searches (PEAKS, Proteome Discoverer software, SearchGUI software, and PepExplorer). Enrichment analysis was performed using g:Profiler, Panther, and String platforms. After the elimination of identification redundancies among search tools (at three levels, based on identifiers, peptides, and cross-database mapping), 1977 proteins were reliably identified in the samples of equine embryos. Proteomic analysis unveiled robust metabolic activity in the 8-day equine embryo, highlighted by an abundance of proteins engaged in key metabolic pathways like the TCA cycle, ATP biosynthesis, and glycolysis. The prevalence of chaperones among highly abundant proteins suggests that regulation of protein folding, and degradation is a key process during embryo development. These findings pave the way for developing new strategies to improve equine embryo media and optimize in vitro fertilization techniques.

Profiling several key milk miRNAs and analysing their signalling pathways in dairy sheep breeds during peak and late lactation

BACKGROUND

The comprehensive understanding of microRNAs (miRNAs) in sheep milk during various lactation periods and their impact on milk yield and composition remains limited.

OBJECTIVES

This study aimed to investigate the expression patterns of four highly expressed miRNAs in sheep milk and their association with milk composition and yield parameters during peak and late lactation stages.

METHODS

A total of 40 healthy 4-year-old Akkaraman (n = 20) and Awassi (n = 20) ewes registered with the Ministry of Agriculture and Forestry of the Republic of Türkiye were used in the present study. For miRNA isolation from milk, the Qiagen miRNeasy Serum/Plasma Advanced Kit was utilised following the manufacturer's instructions. The expression levels of miRNAs were assessed using Qiagen miRNA PCR Assays.

RESULTS

The significant fold changes in the expression levels of oar-miR-30a-5p, oar-miR-148a and oar-miR-181a were observed between peak and late lactation periods in the Awassi sheep breed. Conversely, only oar-miR-30a-5p and oar-miR-148a exhibited statistically significant changes in the Akkaraman sheep breed during the same lactation periods. Furthermore, oar-miR-21-5p demonstrated a significant fold change exclusively in peak lactation compared to Akkaraman and Awassi ewes.

CONCLUSIONS

The findings suggest that the expression of the analysed miRNAs is influenced by both the lactation stage and different sheep breeds. This study offers valuable insights into the relationship between key miRNA expressions in sheep milk and milk composition and yield parameters during peak and late lactation, contributing to the existing knowledge in this field.

Thinking Beyond Disease Silos: Dysregulated Genes Common in Tuberculosis and Lung Cancer as Identified by Systems Biology and Machine Learning

The traditional way of thinking about human diseases across clinical and narrow phenomics silos often masks the underlying shared molecular substrates across human diseases. One Health and planetary health fields particularly address such complexities and invite us to think across the conventional disease nosologies. For example, tuberculosis (TB) and lung cancer (LC) are major pulmonary diseases with significant planetary health implications. Despite distinct etiologies, they can coexist in a given community or patient. This is both a challenge and an opportunity for preventive medicine, diagnostics, and therapeutics innovation. This study reports a bioinformatics analysis of publicly available gene expression data, identifying overlapping dysregulated genes, downstream regulators, and pathways in TB and LC. Analysis of NCBI-GEO datasets (GSE83456 and GSE103888) unveiled differential expression of CEACAM6, MUC1, ADM, DYSF, PLOD2, and GAS6 genes in both diseases, with pathway analysis indicating association with lysine degradation pathway. Random forest, a machine-learning-based classification, achieved accuracies of 84% for distinguishing TB from controls and 83% for discriminating LC from controls using these specific genes. Additionally, potential drug targets were identified, with molecular docking confirming the binding affinity of warfarin to GAS6. Taken together, the present study speaks of the pressing need to rethink clinical diagnostic categories of human diseases and that TB and LC might potentially share molecular substrates. Going forward, planetary health and One Health scholarship are poised to cultivate new ways of thinking about diseases not only across medicine and ecology but also across traditional diagnostic conventions.