Identification Of Therapeutic Targets Research Articles

Microglial Drivers of Alzheimer's Disease Pathology: AnEvolution of Diverse Participating States.

Microglia, the resident immune-competent cells of the brain, become dysfunctional in Alzheimer's disease (AD), and their aberrant immune responses contribute to the accumulation of pathological proteins and neuronal injury. Genetic studies implicate microglia in the development of AD, prompting interest in developing immunomodulatory therapies to prevent or ameliorate disease. However, microglia take on diverse functional states in disease, playing both protective and detrimental roles in AD, which largely overlap and may shift over the disease course, complicating the identification of effective therapeutic targets. Extensive evidence gathered using transgenic mouse models supports an active role of microglia in pathology progression, though results vary and can be contradictory between different types of models and the degree of pathology at the time of study. Here, we review microglial immune signaling and responses that contribute to the accumulation and spread of pathological proteins or directly affect neuronal health. We additionally explore the use of induced pluripotent stem cell (iPSC)-derived models to study living human microglia and how they have contributed to our knowledge of AD and may begin to fill in the gaps left by mouse models. Ultimately, mouse and iPSC-derived models have their own limitations, and a comprehensive understanding of microglial dysfunction in AD will only be established by an integrated view across models and an appreciation for their complementary viewpoints and limitations.

The BAG3-IFITM2 Axis Enhances Pancreatic Ductal Adenocarcinoma Growth via the MAPK Signaling Pathway.

Pancreatic ductal adenocarcinoma (PDAC), a highly lethal malignancy, exhibits escalating incidence and mortality rates, underscoring the urgent need for the identification of novel therapeutic targets and strategies. The BAG3 protein, a multifunctional regulator involved in various cellular processes, notably plays a crucial role in promoting tumor progression and acts as a potential "bridge" between tumors and the tumor microenvironment. In this study, we demonstrate that PDAC cells secrete BAG3 (sBAG3), which engages the IFITM2 receptor to activate the MAPK signaling pathway, specifically enhancing pERK activity, thereby propelling PDAC growth. Furthermore, our preliminary investigation into the effects of sBAG3 on co-cultured NK cells intriguingly discovered that sBAG3 diminishes NK cell cytotoxicity and active molecule expression. In conclusion, our findings confirm the pivotal role of the sBAG3-IFITM2 axis in fostering PDAC progression, highlighting the potential significance of sBAG3 as a dual therapeutic target for both tumor and immune cells.

Joint metabolomics and transcriptomics analysis systematically reveal the impact of MYCN in neuroblastoma.

The limited understanding of the molecular mechanism underlying MYCN-amplified (MNA) neuroblastoma (NB) has hindered the identification of effective therapeutic targets for MNA NB, contributing to its higher mortality rate compared to MYCN non-amplified (non-MNA) NB. Therefore, a comprehensive analysis integrating metabolomics and transcriptomics was conducted to systematically investigate the MNA NB. Metabolomics analysis utilized plasma samples from 28 MNA NB patients and 68 non-MNA NB patients, while transcriptomics analysis employed tissue samples from 15 MNA NB patients and 37 non-MNA NB patients. Notably, joint metabolomics and transcriptomics analysis was performed. A total of 46 metabolites exhibited alterations, with 21 displaying elevated levels and 25 demonstrating reduced levels in MNA NB. In addition, 884 mRNAs in MNA NB showed significant changes, among which 766 mRNAs were higher and 118 mRNAs were lower. Joint-pathway analysis revealed three aberrant pathways involving glycerolipid metabolism, purine metabolism, and lysine degradation. This study highlights the substantial differences in metabolomics and transcriptomics between MNA NB and non-MNA NB, identifying three abnormal metabolic pathways that may serve as potential targets for understanding the molecular mechanisms underlying MNA NB.

IL-16 Mediates the Effect of Circulating Metabolites on Postmenopausal Osteoporosis: A Two-Step, Multivariable Mendelian Randomization Study.

Objectives: This study aimed to explore the relationship between circulating metabolites and postmenopausal osteoporosis (PMOP) and to assess the mediating role of inflammatory factors. Methods: Utilizing summary-level data from genome-wide association studies (GWAS) and employing a Mendelian Randomization approach, a two-sample MR analysis was conducted to assess the relationship between circulating metabolites and PMOP. Additionally, a two-step MR was used to quantify the mediating impact of inflammatory factors on the effect of circulating metabolites on PMOP. Results: The results revealed a significant association between certain metabolites and the risk of PMOP, notably the ratio of free cholesterol to total lipids in very large VLDL particles (OR: 1.399, 95% CI: 1.002-1.954, p = 0.048) and IL-16 (OR: 0.773, 95% CI: 0.608-0.983, p = 0.036). IL-16 was found to partially mediate the impact of circulating metabolites on PMOP, with a mediation effect of 10.4%. Conclusion: This study underscores the crucial role of circulating metabolites and inflammatory factors in PMOP pathogenesis. A causal relationship between circulating metabolites and PMOP was established, with IL-16 mediating some effects. These findings hold promise for clinical applications in early detection, personalized medicine, and the identification of therapeutic targets for PMOP.

Biological and clinical relevance of correlated expression levels of coding and long noncoding RNAs in HPV16 positive cervical cancers.

Human papillomavirus (HPV) drives cervical cancer (CaCx) pathogenesis and viral oncoproteins jeopardize global gene expression in such cancers. In this study, our aim was to identify differentially expressed coding (DEcGs) and long noncoding RNA genes (DElncGs) specifically sense intronic and Natural Antisense Transcripts as they are located in the genic regions and may have a direct influence on the expression pattern of their neighbouring coding genes. We compared HPV16-positive CaCx patients (N = 44) with HPV-negative normal individuals (N = 34) by employing strand-specific RNA-seq and determined the relationships between DEcGs and DElncGs and their clinical implications. By performing Gene set enrichment and protein-protein interaction (PPI) analyses of DEcGs, we identified enrichment of processes crucial for abortive virus life cycle and cancer progression. The DEcGs formed 16 gene clusters which we identified through Molecular Complex Detection (MCODE) plugin of Cytoscape. All the gene clusters portrayed cancer-related functions. We recorded significantly correlated expression levels of 79 DElncGs with DEcGs at proximal genomic loci based on Pearson's Correlation coefficients. Of these gene pairs, 24 pairs portrayed significantly altered correlation coefficients among patients, compared to normal individuals. Of these, 6 DEcGs of 6 such gene pairs, belonged to 5 of the identified gene clusters, one of which was survival-associated. Out of the 24 correlated DEcG: DElncG pairs, we identified 3 pairs, where expression of both members was significantly associated with patient overall survival. The findings justify the cooperative roles of these gene pairs, in patient prognostication, thereby bearing immense potential for translation. Thus, elucidation of correlative strengths between paired DElncGs and DEcGs in patient and normal samples, could serve as a foundation for identification of therapeutic and prognostic targets of HPV16-positive CaCx.

VEGF and ELAVL1/HuR protein levels are increased in dry and wet AMD patients. A New Tile in the Pathophysiologic Mechanisms Underlying RPE Degeneration?

Age-related macular degeneration (AMD) is a common retinal pathology characterized by degeneration of macula's retinal pigment epithelium (RPE) and photoreceptors, visual impairment, or loss. Compared to wet AMD, dry AMD is more common, but lacks cures; therefore, identification of new potential therapeutic targets and treatments is urgent. Increased oxidative stress and declining antioxidant, detoxifying systems contribute to the pathophysiologic mechanisms underlying AMD. The present work shows that the Embryonic Lethal Abnormal Vision-Like 1/Human antigen R (ELAVL1/HuR) and the Vascular Endothelial Growth Factor (VEGF) protein levels are higher in the RPE of both dry and wet AMD patients compared to healthy subjects. Moreover, increased HuR protein levels are detected in the retina, and especially in the RPE layer, of a dry AMD model, the nuclear factor erythroid 2-related factor 2 (Nrf2) / peroxisome proliferator-activated receptor gamma coactivator-1α (PGC-1α) double knock-out mouse. The crosstalk among Nrf2, HuR and VEGF has been also studied in ARPE-19 cells in basal and stressful conditions related to the AMD context (i.e., oxidative stress, autophagy impairment, Nrf2 deficit), offering new evidence of the mutual influence between Nrf2 and HuR, of the dependence of VEGF expression and secretion by these two factors, and of the increased susceptibility of cells to stressful conditions in Nrf2- or HuR-impaired contexts. Overall, this study shows evidence of the interplay among Nrf2, HuR and VEGF, essential factors for RPE homeostasis, and represents an additional piece in the understanding of the complex pathophysiologic mechanisms underlying AMD.

Kinome state is predictive of cell viability in pancreatic cancer tumor and cancer-associated fibroblast cell lines.

Numerous aspects of cellular signaling are regulated by the kinome-the network of over 500 protein kinases that guides and modulates information transfer throughout the cell. The key role played by both individual kinases and assemblies of kinases organized into functional subnetworks leads to kinome dysregulation driving many diseases, particularly cancer. In the case of pancreatic ductal adenocarcinoma (PDAC), a variety of kinases and associated signaling pathways have been identified for their key role in the establishment of disease as well as its progression. However, the identification of additional relevant therapeutic targets has been slow and is further confounded by interactions between the tumor and the surrounding tumor microenvironment. In this work, we attempt to link the state of the human kinome, or kinotype, with cell viability in treated, patient-derived PDAC tumor and cancer-associated fibroblast cell lines. We applied classification models to independent kinome perturbation and kinase inhibitor cell screen data, and found that the inferred kinotype of a cell has a significant and predictive relationship with cell viability. We further find that models are able to identify a set of kinases whose behavior in response to perturbation drive the majority of viability responses in these cell lines, including the understudied kinases CSNK2A1/3, CAMKK2, and PIP4K2C. We next utilized these models to predict the response of new, clinical kinase inhibitors that were not present in the initial dataset for model devlopment and conducted a validation screen that confirmed the accuracy of the models. These results suggest that characterizing the perturbed state of the human protein kinome provides significant opportunity for better understanding of signaling behavior and downstream cell phenotypes, as well as providing insight into the broader design of potential therapeutic strategies for PDAC.

Causal Association between Circulating Metabolites and Dementia: A Mendelian Randomization Study

The causal association of circulating metabolites with dementia remains uncertain. We assessed the causal association of circulating metabolites with dementia utilizing Mendelian randomization (MR) methods. We performed univariable MR analysis to evaluate the associations of 486 metabolites with dementia, Alzheimer’s disease (AD), and vascular dementia (VaD) risk. For secondary validation, we replicated the analyses using an additional dataset with 123 metabolites. We observed 118 metabolites relevant to the risk of dementia, 59 of which were lipids, supporting the crucial role of lipids in dementia pathogenesis. After Bonferroni adjustment, we identified nine traits of HDL particles as potential causal mediators of dementia. Regarding dementia subtypes, protective effects were observed for epiandrosterone sulfate on AD (OR = 0.60, 95% CI: 0.48–0.75) and glycoproteins on VaD (OR = 0.89, 95% CI: 0.83–0.95). Bayesian model averaging MR (MR-BMA) analysis was further conducted to prioritize the predominant metabolites for dementia risk, which highlighted the mean diameter of HDL particles and the concentration of very large HDL particles as the predominant protective factors against dementia. Moreover, pathway analysis identified 17 significant and 2 shared metabolic pathways. These findings provide support for the identification of promising predictive biomarkers and therapeutic targets for dementia.

Annexin A1 binds PDZ and LIM domain 7 to inhibit adipogenesis and prevent obesity.

Obesity is a global issue that warrants the identification of more effective therapeutic targets and a better understanding of the pivotal molecular pathogenesis. Annexin A1 (ANXA1) is known to inhibit phospholipase A2, exhibiting anti-inflammatory activity. However, the specific effects of ANXA1 in obesity and the underlying mechanisms of action remain unclear. Our study reveals that ANXA1 levels are elevated in the adipose tissue of individuals with obesity. Whole-body or adipocyte-specific ANXA1 deletion aggravates obesity and metabolic disorders. ANXA1 levels are higher in stromal vascular fractions (SVFs) than in mature adipocytes. Further investigation into the role of ANXA1 in SVFs reveals that ANXA1 overexpression induces lower numbers of mature adipocytes, while ANXA1-knockout SVFs exhibit the opposite effect. This suggests that ANXA1 plays an important role in adipogenesis. Mechanistically, ANXA1 competes with MYC binding protein 2 (MYCBP2) for interaction with PDZ and LIM domain 7 (PDLIM7). This exposes the MYCBP2-binding site, allowing it to bind more readily to the SMAD family member 4 (SMAD4) and promoting its ubiquitination and degradation. SMAD4 degradation downregulates peroxisome proliferator-activated receptor gamma (PPARγ) transcription and reduces adipogenesis. Treatment with Ac2-26, an active peptide derived from ANXA1, inhibits both adipogenesis and obesity through the mechanism. In conclusion, the molecular mechanism of ANXA1 inhibiting adipogenesis was first uncovered in our study, which is a potential target for obesity prevention and treatment.

Sensory and motor cortices parcellations estimated via distance-weighted sparse representation with application to autism spectrum disorder

BackgroundMotor impairments and sensory processing abnormalities are prevalent in autism spectrum disorder (ASD), closely related to the core functions of the primary motor cortex (M1) and the primary somatosensory cortex (S1). Currently, there is limited knowledge about potential therapeutic targets in the subregions of M1 and S1 in ASD patients. This study aims to map clinically significant functional subregions of M1 and S1. MethodsResting-state functional magnetic resonance imaging data (NTD = 266) from Autism Brain Imaging Data Exchange (ABIDE) were used for subregion modeling. We proposed a distance-weighted sparse representation algorithm to construct brain functional networks. Functional subregions of M1 and S1 were identified through consensus clustering at the group level. Differences in the characteristics of functional subregions were analyzed, along with their correlation with clinical scores. ResultsWe observed symmetrical and continuous subregion organization from dorsal to ventral aspects in M1 and S1, with M1 subregions conforming to the functional pattern of the motor homunculus. Significant intergroup differences and clinical correlations were found in the dorsal and ventral aspects of M1 (p < 0.05/3, Bonferroni correction) and the ventromedial BA3 of S1 (p < 0.05/5). These functional characteristics were positively correlated with autism severity. All subregions showed significant results in the ROI-to-ROI intergroup differential analysis (p < 0.05/80). LimitationsThe generalizability of the segmentation model requires further evaluation. ConclusionsThis study highlights the significance of M1 and S1 in ASD treatment and may provide new insights into brain parcellation and the identification of therapeutic targets for ASD.

Correlation between inflammatory cytokines and the likelihood of developing multiple types of digestive system cancers: A Mendelian randomization study

ObjectiveInflammatory cytokines have been linked to digestive system cancers, yet their exact causal connection remains uncertain. Consequently, we conducted a Mendelian randomization (MR) analysis to gauge how inflammatory cytokines are linked to the risk of five prevalent digestive system cancers (DSCs). MethodsWe collected genetic variation data for 41 inflammatory cytokines from genome-wide association studies (GWAS), and the results data for five common diseases from the Finnish database. Our primary analytical approach involved employing the inverse-variance weighted, residual sum (IVW) method, complemented by the MR-Egger method, the weighted median method, simple mode analysis, and weighted mode analysis as supplementary analytical techniques. Furthermore, we conducted multiple sensitivity analyses. ResultsTumor necrosis factor-related apoptosis-inducing ligand (TRAIL), macrophage colony-stimulating factor (M-CSF), and interleukin (IL)-18 showed a negative association with the risk of hepatocellular carcinoma. Conversely, TRAIL was inversely linked to the risk of gastric cancer, while IL-16 exhibited a positive correlation with gastric cancer risk. Stem cell factor (SCF) acted as a protective factor against pancreatic cancer. For colorectal cancer, IL-7, IL-9, IL-13, and vascular endothelial growth factor (VEGF) were identified as risk factors. Notably, our results did not indicate a significant correlation between inflammatory cytokines and the risk of esophageal cancer. ConclusionOur research unveils potential connections between 41 inflammatory cytokines and the risk of five common DSCs through a MR analysis. These associations offer valuable insights that could aid in the development of diagnostic biomarkers and the identification of novel therapeutic targets for DSCs.

Epigenetic regulation of macrophage activation in chronic obstructive pulmonary disease.

Macrophages in the innate immune system play a vital role in various lung diseases such as asthma, chronic obstructive pulmonary disease (COPD), acute lung injury and pulmonary fibrosis. Macrophages involved in the process of immunity need to go through a process of activation, including changes in gene expression and cell metabolism. Epigenetic modifications are key factors of macrophage activation including DNA methylation, histone modification and non-coding RNA regulation. Understanding the role and mechanisms of epigenetic regulation of macrophage activation can provide insights into the function of macrophages in lung diseases and help identification of potential therapeutic targets. This review summarizes the latest progress in the epigenetic changes and regulation of macrophages in their development process and in normal physiological states, and the epigenetic regulation of macrophages in COPD as well as the influence of macrophage activation on COPD development.

Cell Death of P. vivax Blood Stages Occurs in Absence of Classical Apoptotic Events and Induces Eryptosis of Parasitized Host Cells.

Elucidation of pathways regulating parasite cell death is believed to contribute to identification of novel therapeutic targets for protozoan diseases, and in this context, apoptosis-like cell death has been reported in different groups of protozoa, in which metacaspases seem to play a role. In the genus Plasmodium, apoptotic markers have been detected in P. falciparum and P. berghei, and no study focusing on P. vivax cell death has been reported so far. In the present study, we investigated the susceptibility of P. vivax to undergo apoptotic cell death after incubating mature trophozoites with the classical apoptosis inducer staurosporine. As assessed by flow cytometry assays, staurosporine inhibited parasite intraerythrocytic development, which was accompanied by a decrease in cell viability, evidenced by reduced plasmodial mitochondrial activity. However, typical signs of apoptosis, such as DNA fragmentation, chromatin condensation, and nuclear segregation, were not detected in the parasites induced to cell death, and no significant alteration in metacaspase gene expression (PvMCA1) was observed under cell death stimulus. Interestingly, dying parasites positively modulated cell death (eryptosis) of host erythrocytes, which was marked by externalization of phosphatidylserine and cell shrinkage. Our study shows for the time that P. vivax blood stages may not be susceptible to apoptosis-like processes, while they could trigger eryptosis of parasitized cells by undergoing cell death. Further studies are required to elucidate the cellular machinery involved in cell death of P. vivax parasites as well as in the modulation of host cell death.

Defining Neuroblastoma: from origin to precision medicine.

Neuroblastoma (NB), an heterogenous pediatric tumor of the sympathetic nervous system, is the most common and deadly extracranial solid malignancy diagnosed in infants. Numerous efforts have been invested in understanding its origin and in development of novel curative targeted therapies. Here, we summarize the recent advances in the identification of the cell of origin and the genetic alterations occurring during development contributing to NB. We discuss current treatment regimens, present and future directions for identification of novel therapeutic metabolic targets, differentiation agents, as well as personalized combinatory therapies as potential approaches for improving survival and quality of life of children with NB.

RNA splicing as a biomarker and phenotypic driver of meningioma DNA methylation groups.

Advances in our understanding of the molecular biology of meningiomas have led to significant gains in the ability to predict patient prognosis and tumor recurrence and to identify novel targets for therapeutic design. Specifically, classification of meningiomas based on DNA methylation has greatly improved our ability to risk stratify patients, however new questions have arisen in terms of the underlying impact these DNA methylation signatures have on meningioma biology. This study utilizes RNA-seq data from 486 meningioma samples corresponding to three meningioma DNA methylation groups (Merlin-intact, Immune-enriched, and Hypermitotic), followed by in vitro experiments utilizing human meningioma cell lines. We identify alterations in RNA splicing between meningioma DNA methylation groups including individual splicing events that correlate with Hypermitotic meningiomas and predict tumor recurrence and overall patient prognosis and compile a set of splicing events that can accurately predict DNA methylation classification based on RNA-seq data. Furthermore, we validate these events using RT-PCR in patient samples and meningioma cell lines. Additionally, we identify alterations in RNA binding proteins and splicing factors that lie upstream of RNA splicing events, including upregulation of SRSF1 in Hypermitotic meningiomas which we show drives alternative RNA splicing changes. Finally, we design splice switching antisense oligonucleotides to target RNA splicing changes in NASP and MFF observed in Hypermitotic meningiomas, providing a rationale for RNA-based therapeutic design. RNA splicing is an important driver of meningioma phenotypes that can be useful in prognosticating patients and as a potential exploit for therapeutic vulnerabilities.

Analysis of different expression RNA binding protein genes in mouse microglia cell from the brains of mice 72 h after subarachnoid hemorrhage or sham operation

BackgroundThe prognosis of brain injury caused by subarachnoid hemorrhage (SAH) is poor. Previous studies showed that abnormal function of RBPs might be involved in brain injury, neuroinflammation and further affect microglia homeostasis. However, no studies have systematically analyzed the genome-wide abnormal expression of RBPs genes in microglia during SAH.MethodsRNA-seq data of microglia from the SAH mouse group (SAH) and control sham-operated mouse group (sham) were downloaded from the GEO database in GSE167957, including four samples from the sham group and four samples from the SAH group for subsequent analysis.Utilizing GO and KEGG functional enrichment analyses, we conducted a comprehensive study of differentially expressed genes (DEGs), alternative splicing patterns, and co-expression networks to gain deeper insights into the differential expression of RNA-binding proteins (RBPs) and differential alternative splicing events (ASEs) between the SAH (subarachnoid hemorrhage) and sham groups. This analysis aimed to elucidate the potential mechanisms underlying the aberrant expression of RBPs in microglia during brain injury caused by SAH.ResultsASEs and co-expression analyses of differentially expressed RBPs and differential ASEs were carried out in microglia in terms of gene expression. GO and KEGG functional enrichment analysis showed that aberrantly expressed RBPs such as Mcm7, Mtdh, SRSF3, and Hnrnpa2b1 may affect and regulate downstream Csnk1d, Uckl1 and other protein phosphorylation-related genes by alterative splicing.ConclusionRBPs were aberrantly expressed in microglia during the development of brain injury secondary to SAH, regulating alterative splicing of downstream genes and influencing the progression of SAH brain injury in this study. This implies that RBPs are important for the identification of new therapeutic targets for brain injury after SAH.

Quantitative Proteomics Reveal the Mechanism of MiR-138-5p Suppressing Cervical Cancer via Targeting ZNF385A.

MicroRNAs are short, noncoding RNA molecules that exert pivotal roles in cancer development and progression by modulating various target genes. There is growing evidence that miR-138-5p is significantly involved in cervical cancer (CC). However, its precise molecular mechanism has yet to be fully understood. In the current investigation, a quantitative proteomics approach was utilized to detect possible miR-138-5p targets in HeLa cells systematically. In total, 364 proteins were downregulated, and 150 were upregulated after miR-138-5p overexpression. Bioinformatic analysis of these differentially expressed proteins (DEPs) revealed significant enrichment in several cancer-related pathways. Zinc finger protein 385A (ZNF385A) was determined as a novel direct target of miR-138-5p and discovered to facilitate the proliferation, migration, and cell cycle progression of HeLa cells. SFN and Fas cell surface death receptor(FAS) were then identified as functional downstream effectors of ZNF385A and miR-138-5p. Moreover, a tumor xenograft experiment was conducted to validate the association of miR-138-5p-ZNF385A-SFN/FAS axis with the development of CC in vivo. Our findings have collectively established a catalog of proteins mediated by miR-138-5p and have provided an in-depth comprehension of the molecular mechanisms responsible for the inhibitory effect of miR-138-5p on CC. The miR-138-5p-ZNF385A-SFN/FAS axis could also be beneficial to the identification of new therapeutic targets.

Comparison of classical Machine Learning-based algorithms to predict Triplex Forming Oligonucleotides

Machine learning algorithms can be utilized to tackle genomic challenges in biological systems, such as identifying therapeutic targets for drug development and searching for effective treatments for chronic diseases like cancer. Triplex-forming oligonucleotides (TFOs) can recognize specific sites in the major groove of duplex DNA sequences, aiding in the identification of therapeutic targets via computational methods. This study aims to compare the performance of five classical machine learning algorithms—Support Vector Machine (SVM), k-Nearest Neighbours (kNN), Decision Tree (DT), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost)—in classifying single-stranded DNA into TFOs. Three datasets were created from an oligo library targeting the supF gene, developed by Kaufmann et al., and used to train the algorithms. The classifiers were optimized through hyperparameter tuning and their performance was evaluated using accuracy, precision, recall, and F1-score metrics. SVM and kNN achieved less than 90 percent accuracy, while DT, RF, and XGBoost, which used tree-based methods, attained over 90 percent accuracy. The XGBoost model showed the best performance with over 96 percent accuracy in classifying single-stranded DNA into TFOs. This study demonstrates that supervised machine learning techniques are effective for accurately classifying single-stranded DNA into TFOs.

Unveiling circRNA-mediated ceRNA networks in ischemic stroke by integrative analysis of multi-source gene expression profiling

BackgroundCircular RNAs (circRNAs) are emerging as potential therapeutic targets for ischemic stroke (IS) due to their regulatory roles in inflammation and apoptosis. This study aimed to develop a comprehensive and robust IS-specific competing endogenous RNA (ceRNA) network to facilitate the identification of novel diagnostic and therapeutic targets. MethodsWe integrated expression data from 15 IS studies using the Rank-In algorithm to minimize batch effects. Differentially expressed circRNAs, miRNAs, and mRNAs were identified by comparing IS and control samples. Functional enrichment analysis of differentially expressed circRNA host genes revealed significantly enriched pathways and Gene Ontology (GO) terms relevant to IS pathogenesis. We further predicted miRNA-circRNA and mRNA-miRNA interactions, enabling the construction of a comprehensive ceRNA network to identify circRNA-related genes with diagnostic potential for IS. ResultsIntegrated analysis revealed 199 differentially expressed circRNAs, 103 miRNAs, and 1736 mRNAs in IS patients. Functional enrichment analysis implicated these molecules in relevant pathways like the neurotrophin signaling pathway and p53 signaling pathway. The constructed circRNA-miRNA-mRNA regulatory network provided insights into potential mechanisms underlying IS. Three circRNA-related genes (RGS2, CDK5R1, and NSF) displayed promising diagnostic potential for IS when combined. ConclusionsWe successfully constructed a robust and informative IS-specific ceRNA network by integrating data from diverse sources. This network identified differentially expressed RNAs and revealed enriched pathways potentially involved in IS pathogenesis. Notably, our analysis identified CDK5R1, RGS2, and NSF as potential diagnostic biomarkers for IS. This study sheds light on a circRNA-mediated regulatory network with potential diagnostic and therapeutic implications for ischemic stroke.

FGL1: a novel biomarker and target for non-small cell lung cancer, promoting tumor progression and metastasis through KDM4A/STAT3 transcription mechanism

Non-small cell lung cancer (NSCLC) is characterized by a high incidence rate and poor prognosis worldwide. A deeper insight into the pathogenesis of NSCLC and identification of novel therapeutic targets are essential to improve the prognosis of NSCLC. In this study, we revealed that fibrinogen-like protein 1 (FGL1) promotes proliferation, migration, and invasion of NSCLC cells. Mechanistically, we found that Stat3 acts as a transcription factor and can be recruited to the FGL1 promoter, enhancing FGL1 promoter activity. Lysine-specific demethylase 4A (KDM4A) interacts with Stat3 and facilitates the removal of methyl groups from H3K9me3, thereby enhancing Stat3-mediated transcription of FGL1. Furthermore, we observed that Stat3 and KDM4A promote NSCLC cell proliferation, migration, and invasion partly by upregulating FGL1 expression. Additionally, the expression of FGL1 was significantly higher in cancer tissues (n = 90) than in adjacent non-cancerous tissues (n = 90). Furthermore, patients with high FGL1 expression had a shorter overall survival (OS) compared to those with low FGL1 expression. We measured the expression levels of FGL1 on circulating tumor cells (CTCs) in 65 patients and found that patients with a dynamic decrease in FGL1 expression on CTCs exhibited a better therapeutic response. These findings suggest that the dynamic changes in FGL1 expression can serve as a potential biomarker for predicting treatment efficacy in NSCLC. Overall, this study revealed the significant role and regulatory mechanisms of FGL1 in the development of NSCLC, suggesting its potential as a therapeutic target for patients with NSCLC. Future studies should provide more personalized and effective treatment options for patients with NSCLC to improve clinical outcomes.