miRPathDB 2.0: a novel release of the miRNA Pathway Dictionary Database

Mesenchymal stem cells and their derivatives as potential longevity-promoting tools

Mesenchymal stem cells (MSCs) and blood plasma/MSC-derived extracellular vesicles (EVs) offer promising tools to promote longevity and treat age-related diseases. MSCs have low immunogenicity and tumorigenicity, and their efficacy is relatively independent of the donor age in humans (but not in rodents). Systemic administration of MSCs and stem cell/blood-derived EVs modified the omic profiles of various organs of aged rodents towards the young ones. The application of EVs appears to be even more beneficial than MSCs. Remarkably, over 70% of microRNAs, which are over-presented in ESC-derived EVs, were found to target longevity-associated genes. Along with MSCs, other types of stem cells were reported to display health- and lifespan-extending effects. Pluripotent Muse cells, a specific subpopulation of MSCs, which possess a number of unique features, could be particularly relevant for promoting healthspan. The rejuvenation potential of MSCs, EVs, and Muse cells warrants further investigation in both animal models and clinical trials, using aging clocks for biological age determination as one of the endpoints.

Extracellular vesicle-derived miRNA-mediated cell-cell communication inference for single-cell transcriptomic data with miRTalk

MicroRNAs are released from cells in extracellular vesicles (EVs), representing an essential mode of cell-cell communication (CCC) via a regulatory effect on gene expression. Single-cell RNA-sequencing technologies have ushered in an era of elucidating CCC at single-cell resolution. Herein, we present miRTalk, a pioneering approach for inferring CCC mediated by EV-derived miRNA-target interactions (MiTIs). The benchmarking against simulated and real-world datasets demonstrates the superior performance of miRTalk, and the application to four disease scenarios reveals the in-depth MiTI-mediated CCC mechanisms. Collectively, miRTalk can infer EV-derived MiTI-mediated CCC with scRNA-seq data, providing new insights into the intercellular dynamics of biological processes.

Dysregulation of GAS5-miRNA-Mediated Signaling Pathways in Cancer Pathobiology: A Comprehensive Exploration of Pathways Influenced by this Axis

The long non-coding RNA Growth Arrest-Specific 5 (GAS5) is pivotal in modulating key signaling pathways by functioning as a molecular sponge for microRNAs (miRNAs). GAS5 is notably recognized for its antitumor properties, primarily through its ability to sequester oncogenic miRNAs, thereby influencing critical pathways such as p53, Wnt/β-catenin, and PI3K/Akt, all of which are integral to cell proliferation, apoptosis, and metastasis. The disruption of GAS5-miRNA interactions has been implicated in various malignancies, reinforcing its potential as both a biomarker and a therapeutic target. This paper delves into the intricate signaling cascades affected by GAS5-miRNA interactions and thoroughly investigates the diagnosis and treatment prospects associated with GAS5. Moreover, it addresses both the challenges and opportunities for translational applicability of these findings in clinical environments. The study emphasizes GAS5's significance within the cancer molecular landscape and posits that precise modulation of GAS5-miRNA interactions could catalyze transformative developments in cancer diagnostics and therapeutic approaches. This comprehensive review not only highlights the critical role of non-coding RNAs in cancer biology but also aims to lay the groundwork for future investigations aimed at harnessing these insights for therapeutic interventions.

Effects of Clinical Covariates on Serum miRNA Expression among Women without Ovarian Cancer

BACKGROUND

Serum miRNAs are potential biomarkers for ovarian cancer; however, many factors may influence miRNA expression. To understand potential confounders in miRNA analysis, we examined how sociodemographic factors and comorbidities, including known ovarian cancer risk factors, influence serum miRNA levels in women without ovarian cancer.

METHODS

Data from 1,576 women from the Mass General Brigham Biobank collected between 2012 and 2019, excluding subjects previously or subsequently diagnosed with ovarian cancer, were examined. Using a focused panel of 179 miRNA probes optimized for serum profiling, miRNA expression was measured by flow cytometry using the Abcam FirePlex assay and correlated with subjects' electronic medical records.

RESULTS

The study population broadly reflected the New England population. The median age of subjects was 49 years, 34% were current or prior smokers, 33% were obese (body mass index > 30 kg/m2), 49% were postmenopausal, and 11% had undergone prior bilateral oophorectomy. Significant differences in miRNA expression were observed among ovarian risk factors such as age, obesity, menopause, BRCA1 or BRCA2 germline mutations, or existence of breast cancer in family history. Additionally, miRNA expression was significantly altered by prior bilateral oophorectomy, hypertension, and hypercholesterolemia. Other variables, such as smoking; parity; age at menarche; hormonal replacement therapy; oral contraception; breast, endometrial, or colon cancer; and diabetes, were not associated with significant changes in the panel when corrected for multiple testing.

CONCLUSIONS

Serum miRNA expression patterns are significantly affected by patient demographics, exposure history, and medical comorbidities.

IMPACT

Understanding confounders in serum miRNA expression is important for refining clinical assays for cancer screening.

Identifying key genes, miRNAs, and pathways in keloid formation: A bioinformatics and experimental study

Keloids represent a challenging clinical problem because of their unpredictable and often refractory nature to treatment. This study aimed to identify the key changes in gene expression in the formation of keloid and provide potential biomarker candidates for clinical treatment and drug target discovery. Keloids and normal skin samples were analyzed for gene expression, and datasets from the Gene Expression Omnibus database were also analyzed. Differentially expressed genes (DEGs) were identified and analyzed using bioinformatics techniques, including gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. A protein-protein interaction network of the DEGs was created using the Search Tool for the Retrieval of Interacting Genes database. The gene set enrichment analysis was performed on keloid and normal skin tissue from clinical samples. The enriched functions and pathways identified included collagen-containing extracellular matrix (ECM), ECM, and external encapsulating structure. Ten hub genes were identified, along with one differentially expressed microRNA, miR-22-5p. miRNA target gene prediction was performed using miRPathDB 2.0 and Targetscan database. Among the hub genes, RUNX2, IGF1, EGF, and PPARGC1A were predicted targets of miR-22-5p. Validation at the tissue level highlighted RUNX2 as a crucial DEG in keloid tissue. These findings shed light on the molecular mechanisms of keloid formation and offer candidate therapeutic targets, suggesting that modulation of the miR-22-5p/RUNX2 axis may be a promising avenue for keloid diagnosis and treatment, thus laying a foundation for improved clinical management of keloid disorders.

Integrated Pharmacogenetic Signature for the Prediction of Prostatic Neoplasms in Men With Metabolic Disorders

BACKGROUND/AIM

Oncogenic processes are delineated by metabolic dysregulation. Drug likeness is pharmacokinetically tested through the CYP450 enzymatic system, whose genetic aberrations under epigenetic stress could shift male organisms into prostate cancer pathways. Our objective was to predict the susceptibility to prostate neoplasia, focused on benign prostatic hyperplasia (BPH) and prostate cancer (PCa), based on the pharmacoepigenetic and the metabolic profile of Caucasians.

MATERIALS AND METHODS

Two independent cohorts of 47,389 individuals in total were assessed to find risk associations of CYP450 genes with prostatic neoplasia. The metabolic profile of the first cohort was statistically evaluated and frequencies of absorption-distribution-metabolism-excretion-toxicity (ADMET) properties were calculated. Prediction of miRNA pharmacoepigenetic targeting was performed.

RESULTS

We found that prostate cancer and benign prostatic hyperplasia patients of the first cohort shared common cardiometabolic trends. Drug classes C08CA, C09AA, C09CA, C10AA, C10AX of the cardiovascular, and G04CA, G04CB of the genitourinary systems, were associated with increased prostate cancer risk, while C03CA and N06AB of the cardiovascular and nervous systems were associated with low-risk for PCa. CYP3A4*1B was the most related pharmacogenetic polymorphism associated with prostate cancer susceptibility. miRNA-200c-3p and miRNA-27b-3p seem to be associated with CYP3A4 targeting and prostate cancer predisposition. Metabolomic analysis indicated that 11β-OHT, 2β-OHT, 15β-OHT, 2α-OHT and 6β-OHT had a high risk, and 16α-OHT, and 16β-OHT had an intermediate disease-risk.

CONCLUSION

These findings constitute a novel integrated signature for prostate cancer susceptibility. Further studies are required to assess their predictive value more fully.

Profiling the cell-specific small non-coding RNA transcriptome of the human placenta

The human placenta is the composite of multiple cell types, each which contributes uniquely to placental function. Small non-coding RNAs (sncRNAs) are regulators of gene expression and can be cell-specific. The sncRNA transcriptome of individual placental cell types has not yet been investigated due to difficulties in their procurement and isolation. Using a custom sequencing method, we explored the expression of seven sncRNA species (miRNA, piRNA, rRNA, scaRNA, snRNA, snoRNA, tRNA) from whole chorionic villi and four major sample-matched FACS-sorted cell type (cytotrophoblast, stromal, endothelial, Hofbauer) samples from 9 first trimester and 17 term placentas. After normalization for technical variables, samples clustered primarily by cell type lineage. No sncRNAs were uniquely expressed by cell type, however, mean expression differed by cell type for 115 sncRNAs. Known placentally-expressed sncRNAs showed differing expression by cell type and trimester. Expression of few sncRNAs varied by sex. Lastly, sample-matched sncRNA expression and DNA methylation correlation was not significant, although high correlation (> R2 ± 0.6) was observed for some sncRNA-CpG pairs. This study represents the first exploration of the sncRNA transcriptome of bulk placental villi and placental cell types, informing about the expression and regulatory patterns underlying human placental development.

Circulating microRNA panels for multi-cancer detection and gastric cancer screening: leveraging a network biology approach

BACKGROUND

Screening tests, particularly liquid biopsy with circulating miRNAs, hold significant potential for non-invasive cancer detection before symptoms manifest.

METHODS

This study aimed to identify biomarkers with high sensitivity and specificity for multiple and specific cancer screening. 972 Serum miRNA profiles were compared across thirteen cancer types and healthy individuals using weighted miRNA co-expression network analysis. To prioritize miRNAs, module membership measure and miRNA trait significance were employed. Subsequently, for specific cancer screening, gastric cancer was focused on, using a similar strategy and a further step of preservation analysis. Machine learning techniques were then applied to evaluate two distinct miRNA panels: one for multi-cancer screening and another for gastric cancer classification.

RESULTS

The first panel (hsa-miR-8073, hsa-miR-614, hsa-miR-548ah-5p, hsa-miR-1258) achieved 96.1% accuracy, 96% specificity, and 98.6% sensitivity in multi-cancer screening. The second panel (hsa-miR-1228-5p, hsa-miR-1343-3p, hsa-miR-6765-5p, hsa-miR-6787-5p) showed promise in detecting gastric cancer with 87% accuracy, 90% specificity, and 89% sensitivity.

CONCLUSIONS

Both panels exhibit potential for patient classification in diagnostic and prognostic applications, highlighting the significance of liquid biopsy in advancing cancer screening methodologies.

Multiomic profiling reveals timing of menopause predicts prefrontal cortex aging and cognitive function

A new case of dementia is diagnosed every 3 s. Beyond age, risk prediction of dementia is challenging. There is growing evidence of underlying processes that connect aging across organ systems and may provide insight for early detection, and there is a need to identify early biomarkers at an age when action can be taken to mitigate cognitive decline. We hypothesized that timing of menopause, a marker of ovarian aging, predicts brain age decades later. We used 2086 subjects with multiple "omics" measurements from post-mortem brain samples. Age at menopause (AAM) is positively correlated with cognitive function and negatively correlated with pre-frontal cortex aging acceleration (calculated as estimated biological age from DNA methylation minus chronological age). Genetic correlations showed that at least part of these associations is derived from shared heritability. To dissect the mechanism linking AAM to cognitive decline, we turned to transcriptomic data which confirmed that later AAM was associated with gene expression in pre-frontal cortex consistent with better cognition, and among those who reached menopause naturally, decreased gene expression of pathways implicated in aging. Those with surgical menopause displayed different molecular changes, including perturbed nicotinamide adenine dinucleotide (NAD+) activity, validated by metabolomics. Bile acid metabolism was perturbed in both groups, although different bile acid ratios were associated with AAM in each. Together, our data suggest that AAM is predictive of brain aging and cognition, with potential mediation by the gut, although through different mechanisms depending on the type of menopause.

miR-449a/miR-340 reprogram cell identity and metabolism in fusion-negative rhabdomyosarcoma

Rhabdomyosarcoma (RMS), the most common pediatric soft tissue sarcoma, arises in skeletal muscle and remains in an undifferentiated state due to transcriptional and post-transcriptional regulators. Among its subtypes, fusion-negative RMS (FN-RMS) accounts for the majority of diagnoses in the pediatric population. MicroRNAs (miRNAs) are non-coding RNAs that modulate cell identity via post-transcriptional regulation of messenger RNAs (mRNAs). In this study, we identify miRNAs impacting FN-RMS cell identity, revealing miR-449a and miR-340 as major regulators of the cell cycle and p53 signaling. Through miR-eCLIP technology, we demonstrate that miR-449a and miR-340 directly target transcripts involved in glycolysis and mitochondrial pyruvate transport, inhibiting the mitochondrial pyruvate carrier (MPC) complex. Pharmacological MPC inhibition induces a similar metabolic shift, reducing metastatic potential and leading to cell cycle exit. Overall, miR-449 and miR-340 orchestrate FN-RMS cell identity, positioning MPC inhibition as a strategy to shift FN-RMS cells toward a non-tumorigenic, quiescent state.

Integrated Analysis of microRNA Targets Reveals New Insights into Transcriptional-Post-Transcriptional Regulatory Cross-Talk

It is becoming increasingly clear that microRNAs are key players in gene regulatory networks, modulating gene expression at post-transcriptional level. Their involvement in almost all cellular processes predicts their role in diseases, and several microRNA-based therapeutics are currently undergoing clinical testing. Despite their undeniable relevance and the substantial body of literature demonstrating their role in cancer and other pathologies, the identification of functional interactions is still challenging. To address this issue, several resources have been developed to collect information from the literature, according to different criteria and reliability scores. In the present study, we have constructed a network of verified microRNA-mRNA interactions by integrating strong-evidence couples from different resources. Our analysis of the resulting network reveals that only one-fifth of the human genes exhibits experimental validated regulation by microRNAs. A very small subset of them is controlled by more than 20 microRNAs, and these hubs are highly enriched of pivotal transcription factors and regulatory proteins, strongly suggesting a complex interplay and a combinatorial effect between transcriptional and post-transcriptional gene control. Data analysis also reveals that several microRNAs control multiple targets involved in the same pathway or biological process, likely contributing to the coordinated control of the protein levels.

Graph Convolutional Network with Neural Collaborative Filtering for Predicting miRNA-Disease Association

Background: Over the past few decades, micro ribonucleic acids (miRNAs) have been shown to play significant roles in various biological processes, including disease incidence. Therefore, much effort has been devoted to discovering the pivotal roles of miRNAs in disease incidence to understand the underlying pathogenesis of human diseases. However, identifying miRNA-disease associations using biological experiments is inefficient in terms of cost and time. Methods: Here, we discuss a novel machine-learning model that effectively predicts disease-related miRNAs using a graph convolutional neural network with neural collaborative filtering (GCNCF). By applying the graph convolutional neural network, we could effectively capture important miRNAs and disease feature vectors present in the network while preserving the network structure. By exploiting neural collaborative filtering, miRNAs and disease feature vectors were effectively learned through matrix factorization and deep learning, and disease-related miRNAs were identified. Results: Extensive experimental results based on area under the curve (AUC) scores (0.9216 and 0.9018) demonstrated the superiority of our model over previous models. Conclusions: We anticipate that our model could not only serve as an effective tool for predicting disease-related miRNAs but could be employed as a universal computational framework for inferring relationships across biological entities.

miRTarBase 2025: updates to the collection of experimentally validated microRNA-target interactions

MicroRNAs (miRNAs) are small non-coding RNAs (18-26 nucleotides) that regulate gene expression by interacting with target mRNAs, affecting various physiological and pathological processes. miRTarBase, a database of experimentally validated miRNA-target interactions (MTIs), now features over 3 817 550 validated MTIs from 13 690 articles, significantly expanding its previous version. The updated database includes miRNA interactions with therapeutic agents, revealing roles in drug resistance and therapeutic strategies. It also highlights miRNAs as predictive, safety and monitoring biomarkers for toxicity assessment, clinical treatment guidance and therapeutic optimization. The expansion of miRNA-mRNA and miRNA-miRNA networks allows the identification of key regulatory genes and co-regulatory miRNAs, providing deeper insights into miRNA functions and critical target genes. Information on oxidized miRNA sequences has been added, shedding light on how oxidative modifications influence miRNA targeting and regulation. The integration of the LLAMA3 model into the NLP pipeline, alongside prompt engineering, enables the efficient identification of MTIs and miRNA-disease associations without large training datasets. An updated data integration and a redesigned user interface enhance accessibility, reinforcing miRTarBase as an essential resource for molecular oncology, drug development and related fields. The updated miRTarBase is available at https://mirtarbase.cuhk.edu.cn/∼miRTarBase/miRTarBase_2025.

Selective diagnostics of Amyotrophic Lateral Sclerosis, Alzheimer's and Parkinson's Diseases with machine learning and miRNA

The diagnosis of neurological diseases can be expensive, invasive, and inaccurate, as it is often difficult to distinguish between different types of diseases with similar motor symptoms. However, the dysregulation of miRNAs can be used to create a robust machine-learning model for a reliable diagnosis of neurological diseases. We used miRNA sequence descriptors and gene target data to create machine-learning models that can be used as diagnostic tools. The top-performing machine-learning models, trained on filtered miRNA datasets for Amyotrophic Lateral Sclerosis, Alzheimer's and Parkinson's Diseases of this research yielded 94, 97, and 96, percent accuracies, respectively. Analysis of dysregulated miRNA in neurological diseases elucidated novel biomarkers that could be used to diagnose and distinguish between the diseases. Machine-learning models developed using sequence and gene target descriptors of miRNA biomarkers can achieve favorable accuracies for disease classification and attain a robust discerning capability of neurological diseases.

Identification of the EBF1/ETS2/KLF2-miR-126-Gene Feed-Forward Loop in Breast Carcinogenesis and Stemness

MicroRNA (miR)-126 is frequently downregulated in malignancies, including breast cancer (BC). Despite its tumor-suppressive role, the mechanisms underlying miR-126 deregulation in BC remain elusive. Through silencing experiments, we identified Early B Cell Factor 1 (EBF1), ETS Proto-Oncogene 2 (ETS2), and Krüppel-Like Factor 2 (KLF2) as pivotal regulators of miR-126 expression. These transcription factors were found to be downregulated in BC due to epigenetic silencing or a "poised but not transcribed" promoter state, impairing miR-126 expression. Gene Ontology analysis of differentially expressed miR-126 target genes in the Cancer Genome Atlas: Breast Invasive Carcinoma (TCGA-BRCA) cohort revealed their involvement in cancer-related pathways, primarily signal transduction, chromatin remodeling/transcription, and differentiation/development. Furthermore, we defined interconnections among transcription factors, miR-126, and target genes, identifying a potential feed-forward loop (FFL) crucial in maintaining cellular identity and preventing the acquisition of stemness properties associated with cancer progression. Our findings propose that the dysregulation of the EBF1/ETS2/KLF2/miR-126 axis disrupts this FFL, promoting oncogenic transformation and progression in BC. This study provides new insights into the molecular mechanisms of miR-126 downregulation in BC and highlights potential targets for therapeutic intervention. Further research is warranted to clarify the role of this FFL in BC, and to identify novel therapeutic strategies aimed at modulating this network as a whole, rather than targeting individual signals, for cancer management.

Mitigating off-target effects of small RNAs: conventional approaches, network theory and artificial intelligence

Three types of highly promising small RNA therapeutics, namely, small interfering RNAs (siRNAs), microRNAs (miRNAs) and the RNA subtype of antisense oligonucleotides (ASOs), offer advantages over small-molecule drugs. These small RNAs can target any gene product, opening up new avenues of effective and safe therapeutic approaches for a wide range of diseases. In preclinical research, synthetic small RNAs play an essential role in the investigation of physiological and pathological pathways as silencers of specific genes, facilitating discovery and validation of drug targets in different conditions. Off-target effects of small RNAs, however, could make it difficult to interpret experimental results in the preclinical phase and may contribute to adverse events of small RNA therapeutics. Out of the two major types of off-target effects we focused on the hybridization-dependent, especially on the miRNA-like off-target effects. Our main aim was to discuss several approaches, including sequence design, chemical modifications and target prediction, to reduce hybridization-dependent off-target effects that should be considered even at the early development phase of small RNA therapy. Because there is no standard way of predicting hybridization-dependent off-target effects, this review provides an overview of all major state-of-the-art computational methods and proposes new approaches, such as the possible inclusion of network theory and artificial intelligence (AI) in the prediction workflows. Case studies and a concise survey of experimental methods for validating in silico predictions are also presented. These methods could contribute to interpret experimental results, to minimize off-target effects and hopefully to avoid off-target-related adverse events of small RNA therapeutics. LINKED ARTICLES: This article is part of a themed issue Non-coding RNA Therapeutics. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v182.2/issuetoc.

Prediction of miRNA-disease associations based on PCA and cascade forest

BACKGROUND

As a key non-coding RNA molecule, miRNA profoundly affects gene expression regulation and connects to the pathological processes of several kinds of human diseases. However, conventional experimental methods for validating miRNA-disease associations are laborious. Consequently, the development of efficient and reliable computational prediction models is crucial for the identification and validation of these associations.

RESULTS

In this research, we developed the PCACFMDA method to predict the potential associations between miRNAs and diseases. To construct a multidimensional feature matrix, we consider the fusion similarities of miRNA and disease and miRNA-disease pairs. We then use principal component analysis(PCA) to reduce data complexity and extract low-dimensional features. Subsequently, a tuned cascade forest is used to mine the features and output prediction scores deeply. The results of the 5-fold cross-validation using the HMDD v2.0 database indicate that the PCACFMDA algorithm achieved an AUC of 98.56%. Additionally, we perform case studies on breast, esophageal and lung neoplasms. The findings revealed that the top 50 miRNAs most strongly linked to each disease have been validated.

CONCLUSIONS

Based on PCA and optimized cascade forests, we propose the PCACFMDA model for predicting undiscovered miRNA-disease associations. The experimental results demonstrate superior prediction performance and commendable stability. Consequently, the PCACFMDA is a potent instrument for in-depth exploration of miRNA-disease associations.

Molecular Profiling of A549 Cell-Derived Exosomes: Proteomic, miRNA, and Interactome Analysis for Identifying Potential Key Regulators in Lung Cancer

BACKGROUND/OBJECTIVES

Exosomes, nano-sized extracellular vesicles released by all cells, play a key role in intercellular communication and carry tumorigenic properties that impact surrounding or distant cells. The complexity of the exosomal molecular interactome and its effects on recipient cells still remain unclear. This study aims to decipher the molecular profile and interactome of lung adenocarcinoma A549 cell-derived exosomes using multi-omics and bioinformatics approaches.

METHODS

We performed comprehensive morphological and physicochemical characterization of exosomes isolated from cell culture supernatant of A549 cells in vitro, using DLS, cryo-TEM, Western blot, and flow cytometry. Proteomic and miRNA high-throughput profiling, coupled with bioinformatics network analysis, were applied to elucidate the exosome molecular cargo. A comparative miRNA analysis was also conducted with exosomes derived from normal lung fibroblast MRC-5 cells.

RESULTS

Exosomes exhibited an average size of ~40 nm and disk-shaped lipid bilayer structures, with tetraspanins CD9 and CD63 validated as exosomal markers. Proteomic analysis identified 68 proteins, primarily linked to the extracellular matrix organization and metabolic processes. miRNA sequencing revealed 72 miRNAs, notably hsa-miR-619-5p, hsa-miR-122-5p, hsa-miR-9901, hsa-miR-7704, and hsa-miR-151a-3p, which are involved in regulating metabolic processes, gene expression, and tumorigenic pathways. Th integration of proteomic and miRNA data through a proteogenomics approach identified dually affected genes including ERBB2, CD44, and APOE, impacted by both exosomal miRNA targeting and protein interactions through synergistic or antagonistic interactions. Differential analysis revealed a distinct miRNA profile in A549 exosomes, associated with cancer-related biological processes, compared to MRC-5 exosomes; notably, hsa-miR-619-5p emerged as a promising candidate for future clinical biomarker studies. The network analysis also revealed genes targeted by multiple upregulated tumor-associated miRNAs in potential exosome-recipient cells.

CONCLUSIONS

This integrative study provides insights into the molecular interactome of lung adenocarcinoma A549 cell-derived exosomes, providing a foundation for future research on exosomal cargo and its role in tumor cell communication, growth, and progression.

System biology analysis of miRNA-gene interaction network reveals novel drug targets in breast cancer

Breast cancer is a heterogeneous disease that is ranked as one of the most common cancers worldwide. Currently, although there are existing molecules such as progesterone receptor and estrogen receptor for breast cancer treatment, discovering more effective drug targets is still in urgent need. In this study, we have obtained six sequencing datasets of breast cancer from GEO database and identified a set of differentially expressed molecules, including 67 miRNAs and 133 genes. Function enrichment analysis by miRPathDB database indicated that targets of 11 miRNAs could be enriched in breast cancer pathway with a p-value ≤ .05. A special miRNA-gene interaction network was constructed for analysis of the progression of breast cancer. We then ranked the importance of each molecule (i.e. miRNA and gene) by their node centrality indexes in the network and selected the top 10% of molecules. The statistical analysis of these molecules showed three miRNAs (hsa-miR-1275, hsa-miR-2392, hsa-miR-3141) have significant effects on the prognosis and survival of patients. By searching for potential drugs in Drugbank database, we have identified four candidates (phenethyl isothiocyanate, amuvatinib, theophylline, trifluridine) for targeting these genes. In conclusion, we believe that these drugs and their analogs could be used in the targeted therapy of breast cancer in the future.

A novel microRNA promotes coxsackievirus B4 infection of pancreatic β cells

The epidemiological association of coxsackievirus B infection with type 1 diabetes suggests that therapeutic strategies that reduce viral load could delay or prevent disease onset. Moreover, recent studies suggest that treatment with antiviral agents against coxsackievirus B may help preserve insulin levels in type 1 diabetic patients. In the current study, we performed small RNA-sequencing to show that infection of immortalized trophoblast cells with coxsackievirus caused differential regulation of several miRNAs. One of these, hsa-miR-AMC1, was similarly upregulated in human pancreatic β cells infected with coxsackievirus B4. Moreover, treatment of β cells with non-cytotoxic concentrations of an antagomir that targets hsa-miR-AMC1 led to decreased CVB4 infection, suggesting a positive feedback loop wherein this microRNA further promotes viral infection. Interestingly, some predicted target genes of hsa-miR-AMC1 are shared with hsa-miR-184, a microRNA that is known to suppress genes that regulate insulin production in pancreatic β cells. Consistently, treatment of coxsackievirus B4-infected β cells with the hsa-miR-AMC1 antagomir was associated with a trend toward increased insulin production. Taken together, our findings implicate novel hsa-miR-AMC1 as a potential early biomarker of coxsackievirus B4-induced type 1 diabetes and suggest that inhibiting hsa-miR-AMC1 may provide therapeutic benefit to type 1 diabetes patients. Our findings also support the use of trophoblast cells as a model for identifying microRNAs that might be useful diagnostic markers or therapeutic targets for coxsackievirus B-induced type 1 diabetes.

Multiomics profiling of DNA methylation, microRNA, and mRNA in skeletal muscle from monozygotic twin pairs discordant for type 2 diabetes identifies dysregulated genes controlling metabolism

BACKGROUND

A large proportion of skeletal muscle insulin resistance in type 2 diabetes (T2D) is caused by environmental factors.

METHODS

By applying multiomics mRNA, microRNA (miRNA), and DNA methylation platforms in biopsies from 20 monozygotic twin pairs discordant for T2D, we aimed to delineate the epigenetic and transcriptional machinery underlying non-genetic muscle insulin resistance in T2D.

RESULTS

Using gene set enrichment analysis (GSEA), we found decreased mRNA expression of genes involved in extracellular matrix organization, branched-chain amino acid catabolism, metabolism of vitamins and cofactors, lipid metabolism, muscle contraction, signaling by receptor tyrosine kinases pathways, and translocation of glucose transporter 4 (GLUT4) to the plasma membrane in muscle from twins with T2D. Differential expression levels of one or more predicted target relevant miRNA(s) were identified for approximately 35% of the dysregulated GSEA pathways. These include miRNAs with a significant overrepresentation of targets involved in GLUT4 translocation (miR-4643 and miR-548z), signaling by receptor tyrosine kinases pathways (miR-607), and muscle contraction (miR-4658). Acquired DNA methylation changes in skeletal muscle were quantitatively small in twins with T2D compared with the co-twins without T2D. Key methylation and expression results were validated in muscle, myotubes, and/or myoblasts from unrelated subjects with T2D and controls. Finally, mimicking T2D-associated changes by overexpressing miR-548 and miR-607 in cultured myotubes decreased expression of target genes, GLUT4 and FGFR4, respectively, and impaired insulin-stimulated phosphorylation of Akt (Ser473) and TBC1D4.

CONCLUSIONS

Together, we show that T2D is associated with non- and epigenetically determined differential transcriptional regulation of pathways regulating skeletal muscle metabolism and contraction.

Profiling Plasma Extracellular Vesicle Metabotypes and miRNAs: An Unobserved Clue for Predicting Relapse in Patients with Early-Stage NSCLC

BACKGROUND AND OBJECTIVE

Lung cancer, the second most prevalent cancer globally, poses significant challenges in early detection and prognostic assessment. Despite advancements in targeted therapies and immunotherapy, the timely identification of relapse remains elusive. Blood-based liquid biopsy biomarkers, including circulating tumor cells (CTCs), cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), circulating-free RNAs (cfRNAs), and extracellular vesicles (EVs)/exosomes, offer promise for non-invasive monitoring.

METHODS

We employ a comprehensive approach integrating miRNA/lncRNA/metabolomic datasets, following a mixed-methods content analysis, to identify candidate biomarkers in NSCLC. NSCLC-associated miRNA/gene/lncRNA associations were linked to in silico-derived molecular pathways.

RESULTS

For data validation, mass spectrometry-based untargeted metabolomics of plasma EVs highlighted miRNA/lncRNA/metabotypes, linking "glycerophospholipid metabolism" to lncRNA H19 and "alanine, aspartate and glutamate metabolism" to miR-29a-3p. Prognostic significance was established for miR-29a-3p, showing lower expression in NSCLC patients with disease progression compared to stable disease (p = 0.004). Kaplan-Meier survival analysis indicated that patients with miR-29a-3p under-expression had significantly shorter overall survival (OS) (p = 0.038). Despite the expression of lncRNA H19 in plasma EVs being undetected, its expression in plasma cfRNAs correlated significantly with disease progression (p = 0.035).

CONCLUSIONS

Herein, we showcase the potential of plasma EV-derived miR-29a-3p as a prognostic biomarker and underscore the intricate interplay of miRNAs, lncRNAs, and metabolites in NSCLC biology. Our findings offer new insights and avenues for further exploration, contributing to the ongoing quest for effective biomarkers in early-stage NSCLC.

Extracellular vesicles from neural stem cells safeguard neurons in intracerebral hemorrhage by suppressing reactive astrocyte neurotoxicity

Extracellular vesicles (EVs) derived from stem cells have shown therapeutic potential in various diseases, but their use in treating neurological disorders remains limited. In this study, we observed neurotoxic activation of reactive astrocytes and lipoapoptosis pathways in both mice and patients with intracerebral hemorrhage (ICH) and found that EVs derived from neural stem cells (EVs-NSC) could suppress this activation. Using loss- and gain-of-function approaches, we identified interferon-β (IFNβ) as a key regulator in neurotoxic activation of astrocytes. In addition, we demonstrated that the microRNA (miRNA) miR-124-3p within EVs-NSC degrades IFNβ mRNA and inhibits ELOVL1 expression via miRNA-coding sequence (CDS) and miRNA-3' UTR binding mechanisms, respectively. This dual action likely reduces astrocyte neurotoxicity by lowering saturated lipid secretion. These mechanisms enable EVs-NSC or miR-124-3p overexpression to inhibit astrocyte neurotoxicity, reduce neural damage, and promote recovery in ICH models, offering strategies for treating neurological disorders by targeting neurotoxic reactive astrocytes.

Ionizing radiation effects on blood-derived extracellular vesicles: insights into miR-34a-5p-mediated cellular responses and biomarker potential

Adverse effects of ionizing radiation on normal tissues limit the radiation dose in cancer treatment, thereby compromising treatment efficiency. Among the consistently affected non-cancer cells, peripheral blood mononuclear cells (PBMCs) exhibit high radiosensitivity and have the potential to induce systemic effects. PBMC-released extracellular vesicles (EVs), contribute to the communication of such systemic effects. This study aimed to investigate the effects of ionizing radiation on EVs as part of the systemic response of PBMCs in terms of microRNA cargo and biological functions.Therefore, whole blood samples from healthy donors were irradiated ex-vivo (0 Gy, 1 Gy, 2 Gy, 4 Gy) and EVs from PBMCs were isolated after 96 h by PEG precipitation or ultracentrifugation. Candidate microRNAs were examined in PBMC-derived EVs from individual donors. The uptake of membrane-stained fluorescent EVs by different recipient cells was quantified by fluorescence-activated cell sorting analysis. The biological effects of increased miR-34a-5p and of total EVs on recipient cells were assessed.Irradiation of PBMCs induced a dose-dependent upregulation of miR-34a-5p within EVs and PBMCs. However, interindividual differences between donors were noticed in the extent of upregulation, and small EVs displayed more pronounced changes in microRNA levels in comparison to large EVs. Irradiation in presence of the small molecule inhibitor KU-60019 demonstrated that this upregulation is dependent on ATM (Ataxia telangiectasia mutated) activation. Moreover, fibroblasts and keratinocytes were identified as preferred EV recipients. Increased miR-34a-5p levels led to a significant reduction in viability and induction of senescence in keratinocytes but not in fibroblasts, indicating a cell type-specific response.In conclusion, this study further elucidated the complex cellular response of normal tissue after radiation exposure. It confirmed radiation-induced modifications of microRNA expression levels in EVs from PBMCs and identified a robust upregulation of miR-34a-5p in the small EV subfraction, suggesting this microRNA as a potential novel candidate for the development of biomarkers for radiation exposure. Moreover, the different uptake efficiencies observed among specific cell types suggested that EVs induce cell type-specific responses in the intercellular communication of systemic radiation effects.

Small non-coding RNAs and pancreatic ductal adenocarcinoma: Linking diagnosis, pathogenesis, drug resistance, and therapeutic potential

This review comprehensively investigates the intricate interplay between small non-coding RNAs (sncRNAs) and pancreatic ductal adenocarcinoma (PDAC), a devastating malignancy with limited therapeutic options. Our analysis reveals the pivotal roles of sncRNAs in various facets of PDAC biology, spanning diagnosis, pathogenesis, drug resistance, and therapeutic strategies. sncRNAs have emerged as promising biomarkers for PDAC, demonstrating distinct expression profiles in diseased tissues. sncRNA differential expression patterns, often detectable in bodily fluids, hold potential for early and minimally invasive diagnostic approaches. Furthermore, sncRNAs exhibit intricate involvement in PDAC pathogenesis, regulating critical cellular processes such as proliferation, apoptosis, and metastasis. Additionally, mechanistic insights into sncRNA-mediated pathogenic pathways illuminate novel therapeutic targets and interventions. A significant focus of this review is dedicated to unraveling sncRNA mechanisms underlying drug resistance in PDAC. Understanding these mechanisms at the molecular level is imperative for devising strategies to overcome drug resistance. Exploring the therapeutic landscape, we discuss the potential of sncRNAs as therapeutic agents themselves as their ability to modulate gene expression with high specificity renders them attractive candidates for targeted therapy. In summary, this review integrates current knowledge on sncRNAs in PDAC, offering a holistic perspective on their diagnostic, pathogenic, and therapeutic relevance. By elucidating the roles of sncRNAs in PDAC biology, this review provides valuable insights for the development of novel diagnostic tools and targeted therapeutic approaches, crucial for improving the prognosis of PDAC patients.

Reduced ovarian cholesterol and steroid biosynthesis along with increased inflammation are associated with high DEHP metabolite levels in human ovarian follicular fluids

The plasticizer di(2-ethylhexyl) phthalate (DEHP) is known to have endocrine-disrupting properties mediated by its many metabolites that form upon exposure in biological systems. In a previous study, we reported an inverse association between DEHP metabolites in the human ovarian follicular fluid (FF) and the responsiveness of the follicles to controlled ovarian stimulation during in vitro fertilization (IVF) treatments. Here, we explored this association further through molecular analysis of the ovarian FF samples. Ninety-six IVF patients from Swedish (N = 48) and Estonian (N = 48) infertility clinics were selected from the previous cohort (N = 333) based on the molar sum of DEHP metabolites in their FF samples to arrive at "high" (mean 7.7 ± SD 2.3 nM, N = 48) and "low" (0.8 ± 0.4 nM, N = 48) exposure groups. Extracellular miRNA levels and concentrations of 15 steroid hormones were measured across FF samples. In addition, FF somatic cells, available for the Estonian patients, were used for RNA sequencing. Differential expression (DE) and interactions between miRNA and mRNA networks revealed that the expression levels of genes in the cholesterol biosynthesis and steroidogenesis pathways were significantly decreased in the high compared to the low DEHP group. In addition, the DE miRNAs were predicted to target key enzymes within these pathways (FDR < 0.05). A decreased 17-OH-progesterone to progesterone ratio was observed in the FF of the high DEHP group (p < 0.05). Additionally, the expression levels of genes associated with inflammatory processes were elevated in the FF somatic cells, and a computational cell-type deconvolution analysis suggested an increased immune cell infiltration into the high DEHP follicles (p < 0.05). In conclusion, elevated DEHP levels in FF were associated with a significantly altered follicular milieu within human ovaries, involving a pro-inflammatory environment and reduced cholesterol metabolism, including steroid synthesis. These results contribute to our understanding of the molecular mechanisms of female reprotoxic effects of DEHP.

Early life interventions metformin and trodusquemine metabolically reprogram the developing mouse liver through transcriptomic alterations

Recent studies have demonstrated the remarkable potential of early life intervention strategies at influencing the course of postnatal development, thereby offering exciting possibilities for enhancing longevity and improving overall health. Metformin (MF), an FDA-approved medication for type II diabetes mellitus, has recently gained attention for its promising anti-aging properties, acting as a calorie restriction mimetic, and delaying precocious puberty. Additionally, trodusquemine (MSI-1436), an investigational drug, has been shown to combat obesity and metabolic disorders by inhibiting the enzyme protein tyrosine phosphatase 1b (Ptp1b), consequently reducing hepatic lipogenesis and counteracting insulin and leptin resistance. In this study, we aimed to further explore the effects of these compounds on young, developing mice to uncover biomolecular signatures that are central to liver metabolic processes. We found that MSI-1436 more potently alters mRNA and miRNA expression in the liver compared with MF, with bioinformatic analysis suggesting that cohorts of differentially expressed miRNAs inhibit the action of phosphoinositide 3-kinase (Pi3k), protein kinase B (Akt), and mammalian target of rapamycin (Mtor) to regulate the downstream processes of de novo lipogenesis, fatty acid oxidation, very-low-density lipoprotein transport, and cholesterol biosynthesis and efflux. In summary, our study demonstrates that administering these compounds during the postnatal window metabolically reprograms the liver through induction of potent epigenetic changes in the transcriptome, potentially forestalling the onset of age-related diseases and enhancing longevity. Future studies are necessary to determine the impacts on lifespan and overall quality of life.

An ontology-based knowledge graph for representing interactions involving RNA molecules

The "RNA world" represents a novel frontier for the study of fundamental biological processes and human diseases and is paving the way for the development of new drugs tailored to each patient's biomolecular characteristics. Although scientific data about coding and non-coding RNA molecules are constantly produced and available from public repositories, they are scattered across different databases and a centralized, uniform, and semantically consistent representation of the "RNA world" is still lacking. We propose RNA-KG, a knowledge graph (KG) encompassing biological knowledge about RNAs gathered from more than 60 public databases, integrating functional relationships with genes, proteins, and chemicals and ontologically grounded biomedical concepts. To develop RNA-KG, we first identified, pre-processed, and characterized each data source; next, we built a meta-graph that provides an ontological description of the KG by representing all the bio-molecular entities and medical concepts of interest in this domain, as well as the types of interactions connecting them. Finally, we leveraged an instance-based semantically abstracted knowledge model to specify the ontological alignment according to which RNA-KG was generated. RNA-KG can be downloaded in different formats and also queried by a SPARQL endpoint. A thorough topological analysis of the resulting heterogeneous graph provides further insights into the characteristics of the "RNA world". RNA-KG can be both directly explored and visualized, and/or analyzed by applying computational methods to infer bio-medical knowledge from its heterogeneous nodes and edges. The resource can be easily updated with new experimental data, and specific views of the overall KG can be extracted according to the bio-medical problem to be studied.

Large Language Models and Genomics for Summarizing the Role of microRNA in Regulating mRNA Expression

microRNA (miRNA)-messenger RNA (mRNA or gene) interactions are pivotal in various biological processes, including the regulation of gene expression, cellular differentiation, proliferation, apoptosis, and development, as well as the maintenance of cellular homeostasis and pathogenesis of numerous diseases, such as cancer, cardiovascular diseases, neurological disorders, and metabolic conditions. Understanding the mechanisms of miRNA-mRNA interactions can provide insights into disease mechanisms and potential therapeutic targets. However, extracting these interactions efficiently from a huge collection of published articles in PubMed is challenging. In the current study, we annotated a miRNA-mRNA Interaction Corpus (MMIC) and used it for evaluating the performance of a variety of machine learning (ML) models, deep learning-based transformer (DLT) models, and large language models (LLMs) in extracting the miRNA-mRNA interactions mentioned in PubMed. We used the genomics approaches for validating the extracted miRNA-mRNA interactions. Among the ML, DLT, and LLM models, PubMedBERT showed the highest precision, recall, and F-score, with all equal to 0.783. Among the LLM models, the performance of Llama-2 is better when compared to others. Llama 2 achieved 0.56 precision, 0.86 recall, and 0.68 F-score in a zero-shot experiment and 0.56 precision, 0.87 recall, and 0.68 F-score in a three-shot experiment. Our study shows that Llama 2 achieves better recall than ML and DLT models and leaves space for further improvement in terms of precision and F-score.

Validation of Selected MicroRNA Transcriptome Data in the Bovine Corpus Luteum during Early Pregnancy by RT-qPCR

In cattle, the corpus luteum (CL) is pivotal in maintaining early pregnancy by secreting progesterone. To establish pregnancy, the conceptus produces interferon-τ, preventing luteolysis and initiating the transformation of the CL spurium into a CL verum. Although this transformation is tightly regulated, limited data are available on the expression of microRNAs (miRNAs) during and after this process. To address this gap, we re-analyzed previously published RNA-Seq data of CL from pregnant cows and regressed CL from non-pregnant cows. This analysis identified 44 differentially expressed miRNAs. From this pool, three miRNAs-bta-miR-222-3p, bta-miR-29c, and bta-miR-2411-3p-were randomly selected for relative quantification. Using bovine ovaries (n = 14) obtained from an abattoir, total RNA (including miRNAs) was extracted and converted to cDNA for RT-qPCR. The results revealed that bta-miR-222-3p was downregulated (p = 0.016) in pregnant females compared to non-pregnant cows with regressed CL. However, no differences in miRNA expression were observed between CL of pregnant and non-pregnant cows for bta-miR-29c (p > 0.32) or bta-miR-2411-3p (p > 0.60). In silico prediction approaches indicated that these miRNAs are involved in pathways regulating pregnancy maintenance, such as the VEGF- and FoxO-signaling pathways. Additionally, their biogenesis is regulated by GABPA and E2F4 transcription factors. The validation of selected miRNA expression in the CL during pregnancy by RT-qPCR provides novel insights that could potentially lead to the identification of biomarkers related to CL physiology and pregnancy outcome.

miRNAs mediate the impact of smoking on dental pulp stem cells via the p53 pathway

Cigarette smoke changes the genomic and epigenomic imprint of cells. In this study, we investigated the biological consequences of extended cigarette smoke exposure on dental pulp stem cells (DPSCs) and the potential roles of miRNAs. DPSCs were treated with various doses of cigarette smoke condensate (CSC) for up to 6 weeks. Cell proliferation, survival, migration, and differentiation were evaluated. Cytokine and miRNA expression were profiled. The results showed that extended exposure to CSC significantly impaired the regenerative capacity of the DPSCs. Bioinformatic analysis showed that the cell cycle pathway, cancer pathways (small cell lung cancer, pancreatic, colorectal, and prostate cancer), and pathways for TNF, TGF-β, p53, PI3K-Akt, mTOR, and ErbB signal transduction, were associated with altered miRNA profiles. In particular, 3 miRNAs has-miR-26a-5p, has-miR-26b-5p, and has-miR-29b-3p fine-tune the p53 and cell cycle signaling pathways to regulate DPSC cellular activities. The work indicated that miRNAs are promising targets to modulate stem cell regeneration and understanding miRNA-targeted genes and their associated pathways in smoking individuals have significant implications for disease control and prevention.

The TGFβ Induced MicroRNAome of the Trabecular Meshwork

Primary open-angle glaucoma (POAG) is a progressive optic neuropathy with a complex, multifactorial aetiology. Raised intraocular pressure (IOP) is the most important clinically modifiable risk factor for POAG. All current pharmacological agents target aqueous humour dynamics to lower IOP. Newer therapeutic agents are required as some patients with POAG show a limited therapeutic response or develop ocular and systemic side effects to topical medication. Elevated IOP in POAG results from cellular and molecular changes in the trabecular meshwork driven by increased levels of transforming growth factor β (TGFβ) in the anterior segment of the eye. Understanding how TGFβ affects both the structural and functional changes in the outflow pathway and IOP is required to develop new glaucoma therapies that target the molecular pathology in the trabecular meshwork. In this study, we evaluated the effects of TGF-β1 and -β2 treatment on miRNA expression in cultured human primary trabecular meshwork cells. Our findings are presented in terms of specific miRNAs (miRNA-centric), but given miRNAs work in networks to control cellular pathways and processes, a pathway-centric view of miRNA action is also reported. Evaluating TGFβ-responsive miRNA expression in trabecular meshwork cells will further our understanding of the important pathways and changes involved in the pathogenesis of glaucoma and could lead to the development of miRNAs as new therapeutic modalities in glaucoma.

Understanding molecular characteristics of extracellular vesicles derived from different types of mesenchymal stem cells for therapeutic translation

Mesenchymal stem cells (MSCs) have been studied for decades as candidates for cellular therapy, and their secretome, including secreted extracellular vesicles (EVs), has been identified to contribute significantly to regenerative and reparative functions. Emerging evidence has suggested that MSC-EVs alone, could be used as therapeutics that emulate the biological function of MSCs. However, just as with MSCs, MSC-EVs have been shown to vary in composition, depending on the tissue source of the MSCs as well as the protocols employed in culturing the MSCs and obtaining the EVs. Therefore, the importance of careful choice of cell sources and culture environments is receiving increasing attention. Many factors contribute to the therapeutic potential of MSC-EVs, including the source tissue, isolation technique, and culturing conditions. This review illustrates the molecular landscape of EVs derived from different types of MSC cells along with culture strategies. A thorough analysis of publicly available omic datasets was performed to advance the precision understanding of MSC-EVs with unique tissue source-dependent molecular characteristics. The tissue-specific protein and miRNA-driven Reactome ontology analysis was used to reveal distinct patterns of top Reactome ontology pathways across adipose, bone marrow, and umbilical MSC-EVs. Moreover, a meta-analysis assisted by an AI technique was used to analyze the published literature, providing insights into the therapeutic translation of MSC-EVs based on their source tissues.

Specific plasma microRNAs are associated with CD4 + T-cell recovery during suppressive antiretroviral therapy for HIV-1

OBJECTIVE

This study investigated the association of plasma microRNAs before and during antiretroviral therapy (ART) with poor CD4 + T-cell recovery during the first year of ART.

DESIGN

MicroRNAs were retrospectively measured in stored plasma samples from people with HIV (PWH) in sub-Saharan Africa who were enrolled in a longitudinal multicountry cohort and who had plasma viral-load less than 50 copies/ml after 12 months of ART.

METHODS

First, the levels of 179 microRNAs were screened in a subset of participants from the lowest and highest tertiles of CD4 + T-cell recovery (ΔCD4) ( N  = 12 each). Next, 11 discordant microRNAs, were validated in 113 participants (lowest tertile ΔCD4: n  = 61, highest tertile ΔCD4: n  = 52). For discordant microRNAs in the validation, a pathway analysis was conducted. Lastly, we compared microRNA levels of PWH to HIV-negative controls.

RESULTS

Poor CD4 + T-cell recovery was associated with higher levels of hsa-miR-199a-3p and hsa-miR-200c-3p before ART, and of hsa-miR-17-5p and hsa-miR-501-3p during ART. Signaling by VEGF and MET, and RNA polymerase II transcription pathways were identified as possible targets of hsa-miR-199a-3p, hsa-200c-3p, and hsa-miR-17-5p. Compared with HIV-negative controls, we observed lower hsa-miR-326, hsa-miR-497-5p, and hsa-miR-501-3p levels before and during ART in all PWH, and higher hsa-miR-199a-3p and hsa-miR-200c-3p levels before ART in all PWH, and during ART in PWH with poor CD4 + T-cell recovery only.

CONCLUSION

These findings add to the understanding of pathways involved in persistent HIV-induced immune dysregulation during suppressive ART.

Whole genome sequencing of mouse lines divergently selected for fatness (FLI) and leanness (FHI) revealed several genetic variants as candidates for novel obesity genes

BACKGROUND

Analysing genomes of animal model organisms is widely used for understanding the genetic basis of complex traits and diseases, such as obesity, for which only a few mouse models exist, however, without their lean counterparts.

OBJECTIVE

To analyse genetic differences in the unique mouse models of polygenic obesity (Fat line) and leanness (Lean line) originating from the same base population and established by divergent selection over more than 60 generations.

METHODS

Genetic variability was analysed using WGS. Variants were identified with GATK and annotated with Ensembl VEP. g.Profiler, WebGestalt, and KEGG were used for GO and pathway enrichment analysis. miRNA seed regions were obtained with miRPathDB 2.0, LncRRIsearch was used to predict targets of identified lncRNAs, and genes influencing adipose tissue amount were searched using the IMPC database.

RESULTS

WGS analysis revealed 6.3 million SNPs, 1.3 million were new. Thousands of potentially impactful SNPs were identified, including within 24 genes related to adipose tissue amount. SNP density was highest in pseudogenes and regulatory RNAs. The Lean line carries SNP rs248726381 in the seed region of mmu-miR-3086-3p, which may affect fatty acid metabolism. KEGG analysis showed deleterious missense variants in immune response and diabetes genes, with food perception pathways being most enriched. Gene prioritisation considering SNP GERP scores, variant consequences, and allele comparison with other mouse lines identified seven novel obesity candidate genes: 4930441H08Rik, Aff3, Fam237b, Gm36633, Pced1a, Tecrl, and Zfp536.

CONCLUSION

WGS revealed many genetic differences between the lines that accumulated over the selection period, including variants with potential negative impacts on gene function. Given the increasing availability of mouse strains and genetic polymorphism catalogues, the study is a valuable resource for researchers to study obesity.

Exosomal miR-122-3p represses the growth and metastasis of MCF-7/ADR cells by targeting GRK4-mediated activation of the Wnt/β-catenin pathway

Breast cancer (BC) is a common cancer whose incidence continues to grow while its medical progress has stagnated. miRNAs are vital messengers that facilitate communications among different cancer cells. This study was to reveal the correlation of miR-122-3p expression with BC metastasis and Adriamycin (ADM) resistance and its mechanism of inhibiting BC metastasis. We found that expression of miR-122-3p is negatively correlated with BC metastasis and is lower in MCF-7/ADR cells. Overexpression of miR-122-3p in MCF-7/ADR cancer cells impairs their ability to migrate, invade, and stimulate blood vessel formation. Further research found that miR-122-3p directly binds to the 3' UTR of GRK4, reducing the phosphorylation of LRP6, which activates the Wnt/β-catenin signaling pathway, facilitating BC development and metastasis. In addition, we observed that miR-122-3p is present in MCF-7  cells, and treatment of MCF-7/ADR cells with MCF-7-derived exosomes, but not with exosomes from miR-122-3p-deficient MCF-7 cells, has identical effects to miR-122-3p overexpression. Data from xenograft experiments further suggest that excess miR-122-3p and MCF-7-derived exosomes inhibit the growth and metastasis of MCF-7/ADR cancer cells in vivo. In conclusion our data reveal that exosomal miR-122-3p may negatively regulate BC growth and metastasis, potentially serving as a diagnostic and druggable target for BC treatment.

DAE-CFR: detecting microRNA-disease associations using deep autoencoder and combined feature representation

BACKGROUND

MicroRNA (miRNA) has been shown to play a key role in the occurrence and progression of diseases, making uncovering miRNA-disease associations vital for disease prevention and therapy. However, traditional laboratory methods for detecting these associations are slow, strenuous, expensive, and uncertain. Although numerous advanced algorithms have emerged, it is still a challenge to develop more effective methods to explore underlying miRNA-disease associations.

RESULTS

In the study, we designed a novel approach on the basis of deep autoencoder and combined feature representation (DAE-CFR) to predict possible miRNA-disease associations. We began by creating integrated similarity matrices of miRNAs and diseases, performing a logistic function transformation, balancing positive and negative samples with k-means clustering, and constructing training samples. Then, deep autoencoder was used to extract low-dimensional feature from two kinds of feature representations for miRNAs and diseases, namely, original association information-based and similarity information-based. Next, we combined the resulting features for each miRNA-disease pair and used a logistic regression (LR) classifier to infer all unknown miRNA-disease interactions. Under five and tenfold cross-validation (CV) frameworks, DAE-CFR not only outperformed six popular algorithms and nine classifiers, but also demonstrated superior performance on an additional dataset. Furthermore, case studies on three diseases (myocardial infarction, hypertension and stroke) confirmed the validity of DAE-CFR in practice.

CONCLUSIONS

DAE-CFR achieved outstanding performance in predicting miRNA-disease associations and can provide evidence to inform biological experiments and clinical therapy.

The miRNA-target interactions: An underestimated intricacy

MicroRNAs (miRNAs) play indispensable roles in posttranscriptional gene regulation. Their cellular regulatory impact is determined not solely by their sheer number, which likely amounts to >2000 individual miRNAs in human, than by the regulatory effectiveness of single miRNAs. Although, one begins to develop an understanding of the complex mechanisms underlying miRNA-target interactions (MTIs), the overall knowledge of MTI functionality is still rather patchy. In this critical review, we summarize key features of mammalian MTIs. We especially highlight latest insights on (i) the dynamic make-up of miRNA binding sites including non-canonical binding sites, (ii) the cooperativity between miRNA binding sites, (iii) the adaptivity of MTIs through sequence modifications, (iv) the bearing of intra-cellular miRNA localization changes and (v) the role of cell type and cell status specific miRNA interaction partners. The MTI biology is discussed against the background of state-of-the-art approaches with particular emphasis on experimental strategies for evaluating miRNA functionality.

Trials and Tribulations of MicroRNA Therapeutics

The discovery of the link between microRNAs (miRNAs) and a myriad of human diseases, particularly various cancer types, has generated significant interest in exploring their potential as a novel class of drugs. This has led to substantial investments in interdisciplinary research fields such as biology, chemistry, and medical science for the development of miRNA-based therapies. Furthermore, the recent global success of SARS-CoV-2 mRNA vaccines against the COVID-19 pandemic has further revitalized interest in RNA-based immunotherapies, including miRNA-based approaches to cancer treatment. Consequently, RNA therapeutics have emerged as highly adaptable and modular options for cancer therapy. Moreover, advancements in RNA chemistry and delivery methods have been pivotal in shaping the landscape of RNA-based immunotherapy, including miRNA-based approaches. Consequently, the biotechnology and pharmaceutical industry has witnessed a resurgence of interest in incorporating RNA-based immunotherapies and miRNA therapeutics into their development programs. Despite substantial progress in preclinical research, the field of miRNA-based therapeutics remains in its early stages, with only a few progressing to clinical development, none reaching phase III clinical trials or being approved by the US Food and Drug Administration (FDA), and several facing termination due to toxicity issues. These setbacks highlight existing challenges that must be addressed for the broad clinical application of miRNA-based therapeutics. Key challenges include establishing miRNA sensitivity, specificity, and selectivity towards their intended targets, mitigating immunogenic reactions and off-target effects, developing enhanced methods for targeted delivery, and determining optimal dosing for therapeutic efficacy while minimizing side effects. Additionally, the limited understanding of the precise functions of miRNAs limits their clinical utilization. Moreover, for miRNAs to be viable for cancer treatment, they must be technically and economically feasible for the widespread adoption of RNA therapies. As a result, a thorough risk evaluation of miRNA therapeutics is crucial to minimize off-target effects, prevent overdosing, and address various other issues. Nevertheless, the therapeutic potential of miRNAs for various diseases is evident, and future investigations are essential to determine their applicability in clinical settings.

DNI-MDCAP: improvement of causal MiRNA-disease association prediction based on deep network imputation

BACKGROUND

MiRNAs are involved in the occurrence and development of many diseases. Extensive literature studies have demonstrated that miRNA-disease associations are stratified and encompass ~ 20% causal associations. Computational models that predict causal miRNA-disease associations provide effective guidance in identifying novel interpretations of disease mechanisms and potential therapeutic targets. Although several predictive models for miRNA-disease associations exist, it is still challenging to discriminate causal miRNA-disease associations from non-causal ones. Hence, there is a pressing need to develop an efficient prediction model for causal miRNA-disease association prediction.

RESULTS

We developed DNI-MDCAP, an improved computational model that incorporated additional miRNA similarity metrics, deep graph embedding learning-based network imputation and semi-supervised learning framework. Through extensive predictive performance evaluation, including tenfold cross-validation and independent test, DNI-MDCAP showed excellent performance in identifying causal miRNA-disease associations, achieving an area under the receiver operating characteristic curve (AUROC) of 0.896 and 0.889, respectively. Regarding the challenge of discriminating causal miRNA-disease associations from non-causal ones, DNI-MDCAP exhibited superior predictive performance compared to existing models MDCAP and LE-MDCAP, reaching an AUROC of 0.870. Wilcoxon test also indicated significantly higher prediction scores for causal associations than for non-causal ones. Finally, the potential causal miRNA-disease associations predicted by DNI-MDCAP, exemplified by diabetic nephropathies and hsa-miR-193a, have been validated by recently published literature, further supporting the reliability of the prediction model.

CONCLUSIONS

DNI-MDCAP is a dedicated tool to specifically distinguish causal miRNA-disease associations with substantially improved accuracy. DNI-MDCAP is freely accessible at http://www.rnanut.net/DNIMDCAP/ .

Impact of miR-29c-3p in the Nucleus Accumbens on Methamphetamine-Induced Behavioral Sensitization and Neuroplasticity-Related Proteins

Methamphetamine (METH) abuse inflicts both physical and psychological harm. While our previous research has established the regulatory role of miR-29c-3p in behavior sensitization, the underlying mechanisms and target genes remain incompletely understood. In this study, we employed the isobaric tags for relative and absolute quantitation (iTRAQ) technique in conjunction with Ingenuity pathway analysis (IPA) to probe the putative molecular mechanisms of METH sensitization through miR-29c-3p inhibition. Through a microinjection of AAV-anti-miR-29c-3p into the nucleus accumbens (NAc) of mice, we observed the attenuation of METH-induced locomotor effects. Subsequent iTRAQ analysis identified 70 differentially expressed proteins (DEPs), with 22 up-regulated potential target proteins identified through miR-29c-3p target gene prediction and IPA analysis. Our focus extended to the number of neuronal branches, the excitatory synapse count, and locomotion-related pathways. Notably, GPR37, NPC1, and IREB2 emerged as potential target molecules for miR-29c-3p regulation, suggesting their involvement in the modulation of METH sensitization. Quantitative PCR confirmed the METH-induced aberrant expression of Gpr37, Npc1, and Ireb2 in the NAc of mice. Specifically, the over-expression of miR-29c-3p led to a significant reduction in the mRNA level of Gpr37, while the inhibition of miR-29c-3p resulted in a significant increase in the mRNA level of Gpr37, consistent with the regulatory principle of miRNAs modulating target gene expression. This suggests that miR-29c-3p potentially influences METH sensitization through its regulation of neuroplasticity. Our research indicates that miR-29c-3p plays a crucial role in regulating METH-induced sensitization, and it identified the potential molecular of miR-29c-3p in regulating METH-induced sensitization.

Candidate biomarkers of EV-microRNA in detecting REM sleep behavior disorder and Parkinson's disease

Parkinson's disease (PD) lacks reliable, non-invasive biomarker tests for early intervention and management. Thus, a minimally invasive test for the early detection and monitoring of PD and REM sleep behavior disorder (iRBD) is a highly unmet need for developing drugs and planning patient care. Extracellular vehicles (EVs) are found in a wide variety of biofluids, including plasma. EV-mediated functional transfer of microRNAs (miRNAs) may be viable candidates as biomarkers for PD and iRBD. Next-generation sequencing (NGS) of EV-derived small RNAs was performed in 60 normal controls, 56 iRBD patients and 53 PD patients to profile small non-coding RNAs (sncRNAs). Moreover, prospective follow-up was performed for these 56 iRBD patients for an average of 3.3 years. Full-scale miRNA profiles of plasma EVs were evaluated by machine-learning methods. After optimizing the library construction method for low RNA inputs (named EVsmall-seq), we built a machine learning algorithm that identified diagnostic miRNA signatures for distinguishing iRBD patients (AUC 0.969) and PD patients (AUC 0.916) from healthy individuals; and PD patients (AUC 0.929) from iRBD patients. We illustrated all the possible expression patterns across healthy-iRBD-PD hierarchy. We also showed 20 examples of miRNAs with consistently increasing or decreasing expression levels from controls to iRBD to PD. In addition, four miRNAs were found to be correlated with iRBD conversion. Distinct characteristics of the miRNA profiles among normal, iRBD and PD samples were discovered, which provides a panel of promising biomarkers for the identification of PD patients and those in the prodromal stage iRBD.

Extracellular vesicles from differentiated stem cells contain novel proangiogenic miRNAs and induce angiogenic responses at low doses

Extracellular vesicles (EVs) released from healthy endothelial cells (ECs) have shown potential for promoting angiogenesis, but their therapeutic efficacy remains poorly understood. We have previously shown that transplantation of a human embryonic stem cell-derived endothelial cell product (hESC-ECP), promotes new vessel formation in acute ischemic disease in mice, likely via paracrine mechanism(s). Here, we demonstrated that EVs from hESC-ECPs (hESC-eEVs) significantly increased EC tube formation and wound closure in vitro at ultralow doses, whereas higher doses were ineffective. More important, EVs isolated from the mesodermal stage of the differentiation (hESC-mEVs) had no effect. Small RNA sequencing revealed that hESC-eEVs have a unique transcriptomic profile and are enriched in known proangiogenic microRNAs (miRNAs, miRs). Moreover, an in silico analysis identified three novel hESC-eEV-miRNAs with potential proangiogenic function. Differential expression analysis suggested that two of those, miR-4496 and miR-4691-5p, are highly enriched in hESC-eEVs. Overexpression of miR-4496 or miR-4691-5p resulted in increased EC tube formation and wound closure in vitro, validating the novel proangiogenic function of these miRNAs. In summary, we demonstrated that hESC-eEVs are potent inducers of EC angiogenic response at ultralow doses and contain a unique EV-associated miRNA repertoire, including miR-4496 and miR-4691-5p, with novel proangiogenic function.

Skin treatment with non-thermal plasma modulates the immune system through miR-223-3p and its target genes

Non-thermal plasma, a partially ionized gas, holds significant potential for clinical applications, including wound-healing support, oral therapies, and anti-tumour treatments. While its applications showed promising outcomes, the underlying molecular mechanisms remain incompletely understood. We thus apply non-thermal plasma to mouse auricular skin and conducted non-coding RNA sequencing, as well as single-cell blood sequencing. In a time-series analysis (five timepoints spanning 2 hours), we compare the expression of microRNAs in the plasma-treated left ears to the unexposed right ears of the same mice as well as to the ears of unexposed control mice. Our findings indicate specific effects in the treated ears for a set of five miRNAs: mmu-miR-144-5p, mmu-miR-144-3p, mmu-miR-142a-5p, mmu-miR-223-3p, and mmu-miR-451a. Interestingly, mmu-miR-223-3p also exhibits an increase over time in the right non-treated ear of the exposed mice, suggesting systemic effects. Notably, this miRNA, along with mmu-miR-142a-5p and mmu-miR-144-3p, regulates genes and pathways associated with wound healing and tissue regeneration (namely ErbB, FoxO, Hippo, and PI3K-Akt signalling). This co-regulation is particularly remarkable considering the significant seed dissimilarities among the miRNAs. Finally, single-cell sequencing of PBMCs reveals the downregulation of 12 from 15 target genes in B-cells, Cd4+ and Cd8+ T-cells. Collectively, our data provide evidence for a systemic effect of non-thermal plasma.

MicroRNA-451a inhibits gemcitabine-refractory biliary tract cancer progression by suppressing the MIF-mediated PI3K/AKT pathway

Gemcitabine is an effective chemotherapeutic agent for biliary tract cancers (BTCs), including gallbladder cancer (GBC) and cholangiocarcinoma (CCA). However, few other effective agents are currently available, particularly for GEM-refractory BTCs. We previously identified microRNA-451a (miR-451a) as a potential therapeutic target in GBC. To elucidate the antineoplastic effects of miR-451a and its underlying mechanisms, we transfected miR-451a into GBC, gemcitabine-resistant GBC (GR-GBC), and gemcitabine-resistant CCA (GR-CCA) cell lines. Furthermore, mimicking in vivo conditions, tumorigenic GBC organoids and three-dimensional (3D) cell culture systems were employed to investigate the anti-proliferative effects of miR-451a on BTCs, and its effect on stem cell properties. We found that miR-451a significantly inhibited cell proliferation, induced apoptosis, and reduced chemoresistant phenotypes, such as epithelial-mesenchymal transition, in both GBC and GR-GBC. The principal mechanism is probably the negative regulation of the phosphatidylinositol 3-kinase/AKT pathway, partially accomplished by directly downregulating macrophage migration inhibitory factor. The Gene Expression Omnibus database revealed that miR-451a was the most significantly downregulated microRNA in CCA tissues. The introduction of miR-451a resulted in similar antineoplastic effects in GR-CCA. Furthermore, miR-451a reduced cell viability in 3D spheroid models and tumorigenic GBC organoids. These findings suggest that the supplementation of miR-451a is a potential treatment strategy for GEM-refractory BTCs.

Cross-kingdom regulation by plant-derived miRNAs in mammalian systems

MicroRNAs (miRNAs) are small noncoding RNA molecules ubiquitously distributed across diverse organisms, serving as pivotal regulators of genetic expression. Notably, plant-derived miRNAs have been demonstrated to have unique bioactivity and certain stability in mammalian systems, thereby facilitating their capacity for cross-kingdom modulation of gene expression. While there is substantial evidence supporting the regulation of mammalian cells by plant-derived miRNAs, several questions remain unanswered. Specifically, a comprehensive investigation of the mechanisms underlying the stability and transport of plant miRNAs and their cross-kingdom regulation of gene expression in mammals remains to be done. In this review, we summarized the origin, processing, and functional mechanisms of plant miRNAs in mammalian tissues and circulation, emphasizing their greater resistance to mammalian digestion and circulation systems compared to animal miRNAs. Additionally, we introduce four well-known plant miRNAs that have been extensively studied for their functions and mechanisms in mammalian systems. By delving into these aspects, we aim to offer a fundamental understanding of this intriguing field and shed light on the complex interactions between plant miRNAs and mammalian biology.

Identification of circulating miRNA as early diagnostic molecular markers in malignant glioblastoma base on decision tree joint scoring algorithm

PURPOSE

The lack of clinical markers prevents early diagnosis of glioblastoma (GBM). Many studies have found that circulating microRNAs (miRNAs) can be used as early diagnostic markers of malignant tumours. Therefore, the identification of novel circulating miRNA biomolecular markers could be beneficial to clinicians in the early diagnosis of GBM.

METHODS

We developed a decision tree joint scoring algorithm (DTSA), systematically integrating significance analysis of microarray (SAM), Pearson hierarchical clustering, T test, Decision tree and Entropy weight score algorithm, to screen out circulating miRNA molecular markers with high sensitivity and accuracy for early diagnosis of GBM.

RESULTS

DTSA was developed and applied for GBM datasets and three circulating miRNA molecular markers were identified, namely, hsa-miR-2278, hsa-miR-555 and hsa-miR-892b. We have found that hsa-miR-2278 and hsa-miR-892b regulate the GBM pathway through target genes, promoting the development of GBM and affecting the survival of patients. DTSA has better classification effect in all data sets than other classification algorithms, and identified miRNAs are better than existing markers of GBM.

CONCLUSION

These results suggest that DTSA can effectively identify circulating miRNA, thus contributing to the early diagnosis and personalised treatment of GBM.

Associations Between Epigenetic Age Acceleration and microRNA Expression Among U.S. Firefighters

Epigenetic changes may be biomarkers of health. Epigenetic age acceleration (EAA), the discrepancy between epigenetic age measured via epigenetic clocks and chronological age, is associated with morbidity and mortality. However, the intersection of epigenetic clocks with microRNAs (miRNAs) and corresponding miRNA-based health implications have not been evaluated. We analyzed DNA methylation and miRNA profiles from blood sampled among 332 individuals enrolled across 2 U.S.-based firefighter occupational studies (2015-2018 and 2018-2020). We considered 7 measures of EAA in leukocytes (PhenoAge, GrimAge, Horvath, skin-blood, and Hannum epigenetic clocks, and extrinsic and intrinsic epigenetic age acceleration). We identified miRNAs associated with EAA using individual linear regression models, adjusted for sex, race/ethnicity, chronological age, and cell type estimates, and investigated downstream effects of associated miRNAs with miRNA enrichment analyses and genomic annotations. On average, participants were 38 years old, 88% male, and 75% non-Hispanic white. We identified 183 of 798 miRNAs associated with EAA (FDR q < 0.05); 126 with PhenoAge, 59 with GrimAge, 1 with Horvath, and 1 with the skin-blood clock. Among miRNAs associated with Horvath and GrimAge, there were 61 significantly enriched disease annotations including age-related metabolic and cardiovascular conditions and several cancers. Enriched pathways included those related to proteins and protein modification. We identified miRNAs associated with EAA of multiple epigenetic clocks. PhenoAge had more associations with individual miRNAs, but GrimAge and Horvath had greater implications for miRNA-associated pathways. Understanding the relationship between these epigenetic markers could contribute to our understanding of the molecular underpinnings of aging and aging-related diseases.

Circulating miRNAs as Noninvasive Biomarkers for PDAC Diagnosis and Prognosis in Mexico

Among malignant neoplasms, pancreatic ductal adenocarcinoma (PDAC) has one of the highest fatality rates due to its late detection. Therefore, it is essential to discover a noninvasive, early, specific, and sensitive diagnostic method. MicroRNAs (miRNAs) are attractive biomarkers because they are accessible, highly specific, and sensitive. It is crucial to find miRNAs that could be used as possible biomarkers because PDAC is the eighth most common cause of cancer death in Mexico. With the help of microRNA microarrays, differentially expressed miRNAs (DEmiRNAs) were found in PDAC tissues. The presence of these DEmiRNAs in the plasma of Mexican patients with PDAC was determined using RT-qPCR. Receiver operating characteristic curve analysis was performed to determine the diagnostic capacity of these DEmiRNAs. Gene Expression Omnibus datasets (GEO) were employed to verify our results. The Prisma V8 statistical analysis program was used. Four DEmiRNAs in plasma from PDAC patients and microarray tissues were found. Serum samples from patients with PDAC were used to validate their overexpression in GEO databases. We discovered a new panel of the two miRNAs miR-222-3p and miR-221-3p that could be used to diagnose PDAC, and when miR-221-3p and miR-222-3p were overexpressed, survival rates decreased. Therefore, miR-222-3p and miR-221-3p might be employed as noninvasive indicators for the diagnosis and survival of PDAC in Mexican patients.

MicroRNA networks linked with BRCA1/2, PTEN, and common genes for Alzheimer's disease and breast cancer share highly enriched pathways that may unravel targets for the AD/BC comorbidity treatment

MicroRNAs (miRNAs) are involved in the regulation of various cellular processes including pathological conditions. MiRNA networks have been extensively researched in age-related degenerative diseases, such as cancer, Alzheimer's disease (AD), and heart failure. Thus, miRNA has been studied from different approaches, in vivo, in vitro, and in silico including miRNA networks. Networks linking diverse biomedical entities unveil information not readily observable by other means. This work focuses on biological networks related to Breast cancer susceptibility 1 (BRCA1) in AD and breast cancer (BC). Using various bioinformatics approaches, we identified subnetworks common to AD and BC that suggest they are linked. According to our results, miR-107 was identified as a potentially good candidate for both AD and BC treatment (targeting BRCA1/2 and PTEN in both diseases), accompanied by miR-146a and miR-17. The analysis also confirmed the involvement of the miR-17-92 cluster, and miR-124-3p, and highlighted the importance of poorly researched miRNAs such as mir-6785 mir-6127, mir-6870, or miR-8485. After filtering the in silico analysis results, we found 49 miRNA molecules that modulate the expression of at least five genes common to both BC and AD. Those 49 miRNAs regulate the expression of 122 genes in AD and 93 genes in BC, from which 26 genes are common genes for AD and BC involved in neuron differentiation and genesis, cell differentiation and migration, regulation of cell cycle, and cancer development. Additionally, the highly enriched pathway was associated with diabetic complications, pointing out possible interplay among molecules underlying BC, AD, and diabetes pathology.