DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

Elucidating the role of Rhodiola rosea L. in sepsis-induced acute lung injury via network pharmacology: emphasis on inflammatory response, oxidative stress, and the PI3K-AKT pathway

CONTEXT

Sepsis-induced acute lung injury (ALI) is associated with high morbidity and mortality. Rhodiola rosea L. (Crassulaceae) (RR) and its extracts have shown anti-inflammatory, antioxidant, immunomodulatory, and lung-protective effects.

OBJECTIVE

This study elucidates the molecular mechanisms of RR against sepsis-induced ALI.

MATERIALS AND METHODS

The pivotal targets of RR against sepsis-induced ALI and underlying mechanisms were revealed by network pharmacology and molecular docking. Human umbilical vein endothelial cells (HUVECs) were stimulated by 1 μg/mL lipopolysaccharide for 0.5 h and treated with 6.3, 12.5, 25, 50, 100, and 200 μg/mL RR for 24 h. Then, the lipopolysaccharide-stimulated HUVECs were subjected to cell counting kit-8 (CCK-8), enzyme-linked immunosorbent, apoptosis, and Western blot analyses. C57BL/6 mice were divided into sham, model, low-dose (40 mg/kg), mid-dose (80 mg/kg), and high-dose (160 mg/kg) RR groups. The mouse model was constructed through caecal ligation and puncture, and histological, apoptosis, and Western blot analyses were performed for further validation.

RESULTS

We identified six hub targets (MPO, HRAS, PPARG, FGF2, JUN, and IL6), and the PI3K-AKT pathway was the core pathway. CCK-8 assays showed that RR promoted the viability of the lipopolysaccharide-stimulated HUVECs [median effective dose (ED50) = 18.98 μg/mL]. Furthermore, RR inhibited inflammation, oxidative stress, cell apoptosis, and PI3K-AKT activation in lipopolysaccharide-stimulated HUVECs and ALI mice, which was consistent with the network pharmacology results.

DISCUSSION AND CONCLUSION

This study provides foundational knowledge of the effective components, potential targets, and molecular mechanisms of RR against ALI, which could be critical for developing targeted therapeutic strategies for sepsis-induced ALI.

Network-based identification and mechanism exploration of active ingredients against Alzheimer's disease via targeting endoplasmic reticulum stress from traditional chinese medicine

Alzheimer's disease is a neurodegenerative disease that leads to dementia and poses a serious threat to the health of the elderly. Traditional Chinese medicine (TCM) presents as a promising novel therapeutic therapy for preventing and treating dementia. Studies have shown that natural products derived from kidney-tonifying herbs can effectively inhibit AD. Furthermore, endoplasmic reticulum (ER) stress is a critical factor in the pathology of AD. Regulation of ER stress is a crucial approach to prevent and treat AD. Thus, in this study, we first collected kidney-tonifying herbs, integrated chemical ingredients from multiple TCM databases, and constructed a comprehensive drug-target network. Subsequently, we employed the endophenotype network (network proximity) method to identify potential active ingredients in kidney-tonifying herbs that prevented AD via regulating ER stress. By combining the predicted outcomes, we discovered that 32 natural products could ameliorate AD pathology via regulating ER stress. After a comprehensive evaluation of the multi-network model and systematic pharmacological analyses, we further selected several promising compounds for in vitro testing in the APP-SH-SY5Y cell model. Experimental results showed that echinacoside and danthron were able to effectively reduce ER stress-mediated neuronal apoptosis by inhibiting the expression levels of BIP, p-PERK, ATF6, and CHOP in APP-SH-SY5Y cells. Overall, this study utilized the endophenotype network to preliminarily decipher the effective material basis and potential molecular mechanism of kidney-tonifying Chinese medicine for prevention and treatment of AD.

Vitamin D Relieves Epilepsy Symptoms and Neuroinflammation in Juvenile Mice by Activating the mTOR Signaling Pathway via RAF1: Insights from Network Pharmacology and Molecular Docking Studies

Epilepsy is a common neurological disorder, and the exploration of potential therapeutic drugs for its treatment is still ongoing. Vitamin D has emerged as a promising treatment due to its potential neuroprotective effects and anti-epileptic properties. This study aimed to investigate the effects of vitamin D on epilepsy and neuroinflammation in juvenile mice using network pharmacology and molecular docking, with a focus on the mammalian target of rapamycin (mTOR) signaling pathway. Experimental mouse models of epilepsy were established through intraperitoneal injection of pilocarpine, and in vitro injury models of hippocampal neurons were induced by glutamate (Glu) stimulation. The anti-epileptic effects of vitamin D were evaluated both in vivo and in vitro. Network pharmacology and molecular docking analysis were used to identify potential targets and regulatory pathways of vitamin D in epilepsy. The involvement of the mTOR signaling pathway in the regulation of mouse epilepsy by vitamin D was validated using rapamycin (RAPA). The levels of inflammatory cytokines (TNF-α, IL-1β, and IL-6) were assessed by enzyme-linked immunosorbent assay (ELISA). Gene and protein expressions were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot, respectively. The terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick end-labeling (TUNEL) staining was used to analyze the apoptosis of hippocampal neurons. In in vivo experiments, vitamin D reduced the Racine scores of epileptic mice, prolonged the latency of epilepsy, and inhibited the production of TNF-α, IL-1β, and IL-6 in the hippocampus. Furthermore, network pharmacology analysis identified RAF1 as a potential target of vitamin D in epilepsy, which was further confirmed by molecular docking analysis. Additionally, the mTOR signaling pathway was found to be involved in the regulation of mouse epilepsy by vitamin D. In in vitro experiments, Glu stimulation upregulated the expressions of RAF1 and LC3II/LC3I, inhibited mTOR phosphorylation, and induced neuronal apoptosis. Mechanistically, vitamin D activated the mTOR signaling pathway and alleviated mouse epilepsy via RAF1, while the use of the pathway inhibitor RAPA reversed this effect. Vitamin D alleviated epilepsy symptoms and neuroinflammation in juvenile mice by activating the mTOR signaling pathway via RAF1. These findings provided new insights into the molecular mechanisms underlying the anti-epileptic effects of vitamin D and further supported its use as an adjunctive therapy for existing anti-epileptic drugs.

The PP2A inhibitor LB-100 mitigates lupus nephritis by suppressing tertiary lymphoid structure formation

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by multi-organ involvement and autoantibody production. Patients with SLE face a substantial risk of developing lupus nephritis (LN), which imposes a substantial burden on both patients and their families. Protein phosphatase 2A (PP2A) is a widely distributed serine/threonine phosphatase that participates in regulating multiple signaling pathways. Inhibition of PP2A has been implicated in the treatment of various diseases. LB-100, a small molecule inhibitor of PP2A, has demonstrated anti-tumor therapeutic effects and high safety profile in preclinical experiments. However, the role of PP2A and its inhibitor has been insufficiently studied in LN. In this study, we assessed the potential effects of LB-100 in both MRL/lpr mice and R848-induced BALB/c mice. Our findings indicated that LB-100 administration led to reduced spleen enlargement, decreased deposition of immune complexes, ameliorated renal damage, and improved kidney function in both spontaneous and R848-induced lupus mouse models. Importantly, we observed the formation of tertiary lymphoid structures (TLSs) in the kidneys of two distinct lupus mouse models. The levels of signature genes of TLS were elevated in the kidneys of lupus mice, whereas LB-100 mitigated chemokine production and inhibited TLS formation. In addition, we confirmed that inhibition or knockdown of PP2A reduced the production of T cell-related chemokines by renal tubular epithelial cells (RTEC). In summary, our study highlighted the renal protective potential of the PP2A inhibitor LB-100 in two distinct lupus mouse models, suggesting its potential as a novel strategy for treating LN and other autoimmune diseases.

Leonurus japonicus Houtt. modulates neuronal apoptosis in intracerebral hemorrhage: Insights from network pharmacology and molecular docking

ETHNOPHARMACOLOGICAL RELEVANCE

Leonurus japonicus Houtt. (Labiatae), commonly known as Chinese motherwort, is a herbaceous flowering plant that is native to Asia. It is widely acknowledged in traditional medicine for its diuretic, hypoglycemic, antiepileptic properties and neuroprotection. Currently, Leonurus japonicus (Leo) is included in the Pharmacopoeia of the People's Republic of China. Traditional Chinese Medicine (TCM) recognizes Leo for its myriad pharmacological attributes, but its efficacy against ICH-induced neuronal apoptosis is unclear.

AIMS OF THE STUDY

This study aimed to identify the potential targets and regulatory mechanisms of Leo in alleviating neuronal apoptosis after ICH.

MATERIALS AND METHODS

The study employed network pharmacology, UPLC-Q-TOF-MS technique, molecular docking, pharmacodynamic studies, western blotting, and immunofluorescence techniques to explore its potential mechanisms.

RESULTS

Leo was found to assist hematoma absorption, thus improving the neurological outlook in an ICH mouse model. Importantly, molecular docking highlighted JAK as Leo's potential therapeutic target in ICH scenarios. Further experimental evidence demonstrated that Leo adjusts JAK1 and STAT1 phosphorylation, curbing Bax while augmenting Bcl-2 expression.

CONCLUSION

Leo showcases potential in mitigating neuronal apoptosis post-ICH, predominantly via the JAK/STAT mechanism.

DREAMER: Exploring Common Mechanisms of Adverse Drug Reactions and Disease Phenotypes through Network-Based Analysis

Adverse drug reactions (ADRs) are a major concern in clinical healthcare, significantly affecting patient safety and drug development. This study introduces DREAMER, a novel network-based method for exploring the mechanisms underlying ADRs and disease phenotypes at a molecular level by leveraging a comprehensive knowledge graph obtained from various datasets. By considering drugs and diseases that cause similar phenotypes, and investigating their commonalities regarding their impact on specific modules of the protein-protein interaction network, DREAMER can robustly identify protein sets associated with the biological mechanisms underlying ADRs and unravel the causal relationships that contribute to the observed clinical outcomes. Applying DREAMER to 649 ADRs, we identified proteins associated with the mechanism of action for 67 ADRs across multiple organ systems. In particular, DREAMER highlights the importance of GABAergic signaling and proteins of the coagulation pathways for personality disorders and intracranial hemorrhage, respectively. We further demonstrate the application of DREAMER in drug repurposing and propose sotalol, ranolazine, and diltiazem as candidate drugs to be repurposed for cardiac arrest. In summary, DREAMER effectively detects molecular mechanisms underlying phenotypes.

Transcriptional reprogramming post-peripheral nerve injury: A systematic review

Neuropathic pain is characterised by periodic or continuous hyperalgesia, numbness, or allodynia, and results from insults to the somatosensory nervous system. Peripheral nerve injury induces transcriptional reprogramming in peripheral sensory neurons, contributing to increased spinal nociceptive input and the development of neuropathic pain. Effective treatment for neuropathic pain remains an unmet medical need as current therapeutics offer limited effectiveness and have undesirable effects. Understanding transcriptional changes in peripheral nerve injury-induced neuropathy might offer a path for novel analgesics. Our literature search identified 65 papers exploring transcriptomic changes post-peripheral nerve injury, many of which were conducted in animal models. We scrutinize their transcriptional changes data and conduct gene ontology enrichment analysis to reveal their common functional profile. Focusing on genes involved in 'sensory perception of pain' (GO:0019233), we identified transcriptional changes for different ion channels, receptors, and neurotransmitters, shedding light on its role in nociception. Examining peripheral sensory neurons subtype-specific transcriptional reprograming and regeneration-associated genes, we delved into downstream regulation of hypersensitivity. Identifying the temporal program of transcription regulatory mechanisms might help develop better therapeutics to target them effectively and selectively, thus preventing the development of neuropathic pain without affecting other physiological functions.

Olanzapine manipulates neuroactive signals and may onset metabolic disturbances

Olanzapine is one of the most prescribed atypical antipsychotics to treat psychiatric illness and is associated with weight gain and metabolic disturbance. The present study investigated the olanzapine-regulated metabolic pathways using functional enrichent analysis including binding affinity with G-protein-coupled receptors (GPCRs). Proteins modulated by olanzapine were retrieved from SwissTargetPrediction, DIGEP-Pred, and BindingDB and then enriched in Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) to assess molecular function, biological process, and cellular components including Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We used homology modeling to improve the 3D structure for GPCR synapse proteins including dopamine, serotonin, muscarinic, and histamine receptors which were then optimized using molecular dynamics (MD) simulations. The protein-olanzapine binding mechanisms for different GPCR binders were evaluated using molecular docking; later refined by MD simulations. Binding mechanism of olanzapine with D2, 5HT1A, 5HT2A, 5HT2B, 5HT2C, M1, and M2 receptors were created using homology modeling and optimized using MD simulations. In target identification, it was observed that olanzapine majority targeted G-protein coupled receptors. Further, enrichment analysis identified around 76% of the total genes regulated in molecular function, biological process, and cellular components were common including KEGG pathways. Moreover, it was observed that olanzapine had a major potency over the neurotransmitter synapse including neuroactive signals . Olanzapine-induced weight gain and metabolic alterations could be due to the deregulation of multiple synapses like dopamine, serotonin, muscarinic, and histamine at the feeding center followed by cGMP-PKG, cAMP, and PI3K-Akt signaling pathways. HIGHLIGHTSOlanzapine is used in the management of psychiatric illnesses.Olanzapine causes disturbance in lipids and glucosehomeostasis and manipulates energy expenditure.Olanzapine-induced weight gain may occur due to the deregulation of the multiple synapse and cGMP-PKG, cAMP, and PI3K-Akt signaling pathwayCommunicated by Ramaswamy H. Sarma.

Integrated Transcriptomics and Network Analysis Identified Altered Neural Mechanisms in Frontal Aging Brain-Associated Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disease. The late stage of AD typically develops after 60 years of age and AD pathogenesis can be detected predominately in the frontal lobe, which is responsible for memory. Multiple alterations in cellular mechanisms have been associated with AD, but there is no clear information on AD pathogenesis during brain aging. This study aimed to explore the differentially expressed genes (DEGs) in the frontal lobe of aging brains and to identify shared crucial mechanisms in the aging brain linked to AD pathogenesis. Three datasets were downloaded from the Gene Expression Omnibus (GEO). Biological function analysis was performed by DAVID and KEGG databases. An AD patient's cohort (GSE150696) was collected for verification of the enriched pathway. The results demonstrated that multiple neurochemical synapsis and regulation of the cytoskeleton are linked to AD pathogenesis during aging. Taken together, this study contributes to our further understanding of neural alterations during aging in AD that could be used to develop therapeutics for early intervention to prevent or slow progression.

Computational prediction of crucial genes involved in gonorrhea infection and neoplastic cell transformation: A multiomics approach

Neisseria gonorrheae, the causative agent of genitourinary infections, has been associated with asymptomatic or recurrent infections and has the potential to form biofilms and induce inflammation and cell transformation. Herein, we aimed to use computational analysis to predict novel associations between chronic inflammation caused by gonorrhea infection and neoplastic transformation. Prioritization and gene enrichment strategies based on virulence and resistance genes utilizing essential genes from the DEG and PANTHER databases, respectively, were performed. Using the STRING database, protein‒protein interaction networks were constructed with 55 nodes of bacterial proteins and 72 nodes of proteins involved in the host immune response. MCODE and cytoHubba were used to identify 12 bacterial hub proteins (murA, murB, murC, murD, murE, purN, purL, thyA, uvrB, kdsB, lpxC, and ftsH) and 19 human hub proteins, of which TNF, STAT3 and AKT1 had high significance. The PPI networks are based on the connectivity degree (K), betweenness centrality (BC), and closeness centrality (CC) values. Hub genes are vital for cell survival and growth, and their significance as potential drug targets is discussed. This computational study provides a comprehensive understanding of inflammation and carcinogenesis pathways that are activated during gonorrhea infection.

The Identification of Potential Anti-Depression/Anxiety Drug Targets by Stress-Induced Rat Brain Regional Proteome and Network Analyses

Depression and anxiety disorders are prevalent stress-related neuropsychiatric disorders and involve multiple molecular changes and dysfunctions across various brain regions. However, the specific and shared pathophysiological mechanisms occurring in these regions remain unclear. Previous research used a rat model of chronic mild stress (CMS) to segregate and identify depression-susceptible, anxiety-susceptible, and insusceptible groups; then the proteomes of six distinct brain regions (the hippocampus, prefrontal cortex, hypothalamus, pituitary, olfactory bulb, and striatum) were separately and quantitatively analyzed. To gain a comprehensive and systematic understanding of the molecular abnormalities, this study aimed to investigate and compare differential proteomics data from the six regions. Differentially expressed proteins (DEPs) were identified in between specific regions and across all regions and subjected to a series of bioinformatics analyses. Regional comparisons showed that stress-induced proteomic changes and corresponding gene ontology and pathway enrichments were largely distinct, attributable to differences in cell populations, protein compositions, and brain functions of these areas. Additionally, a notable degree of overlap in the significantly enriched terms was identified, potentially suggesting strong connections in the enrichment across different regions. Furthermore, intra-regional and inter-regional protein-protein interaction networks and drug-target-DEP networks were constructed. Integrated analysis of the three association networks in the six regions, along with the DisGeNET database, identified ten DEPs as potential targets for anti-depression/anxiety drugs. Collectively, these findings revealed commonalities and differences across different brain regions at the protein level induced by CMS, and identified several novel protein targets for the development of new therapeutics for depression and anxiety.

Low-level brain somatic mutations in exonic regions are collectively implicated in autism with germline mutations in autism risk genes

Low-level somatic mutations in the human brain are implicated in various neurological disorders. The contribution of low-level brain somatic mutations to autism spectrum disorder (ASD), however, remains poorly understood. Here, we performed high-depth exome sequencing with an average read depth of 559.3x in 181 cortical, cerebellar, and peripheral tissue samples to identify brain somatic single nucleotide variants (SNVs) in 24 ASD subjects and 31 controls. We detected ~2.4 brain somatic SNVs per exome per single brain region, with a variant allele frequency (VAF) as low as 0.3%. The mutational profiles, including the number, signature, and type, were not significantly different between the ASD patients and controls. Intriguingly, when considering genes with low-level brain somatic SNVs and ASD risk genes with damaging germline SNVs together, the merged set of genes carrying either somatic or germline SNVs in ASD patients was significantly involved in ASD-associated pathophysiology, including dendrite spine morphogenesis (p = 0.025), mental retardation (p = 0.012), and intrauterine growth retardation (p = 0.012). Additionally, the merged gene set showed ASD-associated spatiotemporal expression in the early and mid-fetal cortex, striatum, and thalamus (all p < 0.05). Patients with damaging mutations in the merged gene set had a greater ASD risk than did controls (odds ratio = 3.92, p = 0.025, 95% confidence interval = 1.12-14.79). The findings of this study suggest that brain somatic SNVs and germline SNVs may collectively contribute to ASD-associated pathophysiology.

Identification and immune landscape of sarcopenia-related molecular clusters in inflammatory bowel disease by machine learning and integrated bioinformatics

Sarcopenia, a prevalent comorbidity of inflammatory bowel disease (IBD), is characterized by diminished skeletal muscle mass and strength. Nevertheless, the underlying interconnected mechanisms remain elusive. This study identified distinct expression patterns of sarcopenia-associated genes (SRGs) across individuals with IBD and in samples of normal tissue. By analyzing SRG expression profiles, we effectively segregated 541 IBD samples into three distinct clusters, each marked by its unique immune landscape. To unravel the transcriptional disruptions underlying these clusters, the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm was employed to spotlight key genes linked to each cluster. A diagnostic model based on four key genes (TIMP1, PLAU, PHLDA1, TGFBI) was established using Random Forest and LASSO (least absolute shrinkage and selection operator) algorithms, and validated with the GSE179285 dataset. Moreover, the GSE112366 dataset facilitated the exploration of gene expression dynamics within the ileum mucosa of UC patients pre- and post-Ustekinumab treatment. Additionally, insights into the intricate relationship between immune cells and these pivotal genes were gleaned from the single-cell RNA dataset GSE162335. In conclusion, our findings collectively underscored the pivotal role of sarcopenia-related genes in the pathogenesis of IBD. Their potential as robust biomarkers for future diagnostic and therapeutic strategies is particularly promising, opening avenues for a deeper understanding and improved management of these interconnected conditions.

Macaque Brainnetome Atlas: A multifaceted brain map with parcellation, connection, and histology

The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas is fundamental to biomedical and evolutionary research. However, even though connectivity is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained images. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes: (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, neuronal-tracing, and histological images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.

Determining expression changes of ANO7 and SLC38A4 membrane transporters in colorectal cancer

Membrane transporters are proteins responsible for facilitating the movement of molecules within biological membranes. They play a vital role in maintaining cellular homeostasis by regulating the transport of nutrients, ions, and other molecules into and out of cells. Our aim is to identify biomarkers in colorectal cancer using membrane transporter proteins. We utilized COAD TCGA data for this purpose. Subsequently, we conducted differential gene analysis and feature selection using membrane transporter proteins. Furthermore, we identified two potential genes, including ANO7 and SLC38A4. To validate the expression profiles of ANO7 and SLC38A4, key genes in this context, RT-qPCR was employed on colorectal cancer samples and adjacent normal tissues. Additionally, utilizing GEPIA2, Kaplan-Meier survival analysis, and cBioPortal, we assessed the status of these genes in various cancers, examining their methylation and mutation patterns. In conclusion, we suggest that ANO7 and SLC38A4 serve as prognostic biomarkers in colorectal cancer.

The unfolded features on the synchronized fashion of gut microbiota and Drynaria rhizome against obesity via integrated pharmacology

Drynaria rhizome (DR) is used as a natural remedy to ameliorate obesity (OB) in East Asia; in parallel, the gut microbiota (GM) might exert a positive impact on OB through their metabolites. This study elucidates the orchestrated effects of DR and GM on OB. DR-GM, - a key signaling pathway-target-metabolite (DGSTM) networks were used to unveil the relationship between DR and GM, and Molecular Docking Test (MDT) and Density Functional Theory (DFT) were adopted to underpin the uppermost molecules. The NR1H3 (target) - 3-Epicycloeucalenol (ligand), and PPARG (target) - Clionasterol (ligand) conjugates from DR, FABP3 (target) - Ursodeoxycholic acid, FABP4 (target) - Lithocholic acid (ligand) or Deoxycholic acid (ligand), PPARA (target) - Equol (ligand), and PPARD (target) - 2,3-Bis(3,4-dihydroxybenzyl)butyrolactone (ligand) conjugates from GM formed the most stable conformers via MDT and DFT. Overall, these findings suggest that DR-GM might be a promising ameliorator on PPAR signaling pathway against OB.

Identification and validation of CCL5 as a key gene in HIV infection and pulmonary arterial hypertension

Background

The relationship between human immunodeficiency virus (HIV) infection and pulmonary arterial hypertension (PAH) has garnered significant scrutiny. Individuals with HIV infection have a higher risk of developing PAH. However, the specific mechanism of HIV-associated PAH remains unclear. Our study aims at investigating the shared biomarkers in HIV infection and PAH and predicting the potential therapeutic target for HIV-associated PAH.

Methods

Data for HIV infection and PAH were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) analysis was performed to detect shared genes in HIV infection and PAH. Enrichment analysis was conducted to identify the function of common DEGs. Protein-protein interaction (PPI) analysis was used to detect key genes. These crucial genes were subsequently verified by RT-qPCR. Finally, candidate drugs were identified by using the Drug Signatures Database (DSigDB).

Results

Nineteen common DEGs were identified in HIV infection and PAH. Enrichment analysis exhibited that the functions of these genes were mainly enriched in inflammatory responses, mainly including cellular immunity and interaction between viral proteins and cytokines. By constructing PPI networks, we identified the key gene CC-type chemokine ligand 5 (CCL5), and we verified that CCL5 was highly expressed in hypoxia induced human pulmonary artery endothelial cells (hPAECs) and human pulmonary artery smooth muscle cells (hPASMCs). In addition, we predicted 10 potential drugs targeting CCL5 by Autodock Vina.

Conclusion

This study revealed that CCL5 might be a common biomarker of HIV infection and PAH and provided a new therapeutic target for HIV-associated PAH. However, further clinical validation is still indispensable.

Single-cell discovery of m6A RNA modifications in the hippocampus

N 6-Methyladenosine (m6A) is a prevalent and highly regulated RNA modification essential for RNA metabolism and normal brain function. It is particularly important in the hippocampus, where m6A is implicated in neurogenesis and learning. Although extensively studied, its presence in specific cell types remains poorly understood. We investigated m6A in the hippocampus at a single-cell resolution, revealing a comprehensive landscape of m6A modifications within individual cells. Through our analysis, we uncovered transcripts exhibiting a dense m6A profile, notably linked to neurological disorders such as Alzheimer's disease. Our findings suggest a pivotal role of m6A-containing transcripts, particularly in the context of CAMK2A neurons. Overall, this work provides new insights into the molecular mechanisms underlying hippocampal physiology and lays the foundation for future studies investigating the dynamic nature of m6A RNA methylation in the healthy and diseased brain.

Single-nucleus transcriptomics uncovers a geroprotective role of YAP in primate gingival aging

Aging has a profound impact on the gingiva and significantly increases its susceptibility to periodontitis, a worldwide prevalent inflammatory disease. However, a systematic characterization and comprehensive understanding of the regulatory mechanism underlying gingival aging is still lacking. Here, we systematically dissected the phenotypic characteristics of gingiva during aging in primates and constructed the first single-nucleus transcriptomic landscape of gingival aging, by which a panel of cell type-specific signatures were elucidated. Epithelial cells were identified as the most affected cell types by aging in the gingiva. Further analyses pinpointed the crucial role of YAP in epithelial self-renew and homeostasis, which declined during aging in epithelial cells, especially in basal cells. The decline of YAP activity during aging was confirmed in the human gingival tissues, and downregulation of YAP in human primary gingival keratinocytes recapitulated the major phenotypic defects observed in the aged primate gingiva while overexpression of YAP showed rejuvenation effects. Our work provides an in-depth understanding of gingival aging and serves as a rich resource for developing novel strategies to combat aging-associated gingival diseases, with the ultimate goal of advancing periodontal health and promoting healthy aging.

Using clusterProfiler to characterize multiomics data

With the advent of multiomics, software capable of multidimensional enrichment analysis has become increasingly crucial for uncovering gene set variations in biological processes and disease pathways. This is essential for elucidating disease mechanisms and identifying potential therapeutic targets. clusterProfiler stands out for its comprehensive utilization of databases and advanced visualization features. Importantly, clusterProfiler supports various biological knowledge, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, through performing over-representation and gene set enrichment analyses. A key feature is that clusterProfiler allows users to choose from various graphical outputs to visualize results, enhancing interpretability. This protocol describes innovative ways in which clusterProfiler has been used for integrating metabolomics and metagenomics analyses, identifying and characterizing transcription factors under stress conditions, and annotating cells in single-cell studies. In all cases, the computational steps can be completed within ~2 min. clusterProfiler is released through the Bioconductor project and can be accessed via https://bioconductor.org/packages/clusterProfiler/ .

Revealing the atomic and electronic mechanism of human manganese superoxide dismutase product inhibition

Human manganese superoxide dismutase (MnSOD) is a crucial oxidoreductase that maintains the vitality of mitochondria by converting superoxide (O2●-) to molecular oxygen (O2) and hydrogen peroxide (H2O2) with proton-coupled electron transfers (PCETs). Human MnSOD has evolved to be highly product inhibited to limit the formation of H2O2, a freely diffusible oxidant and signaling molecule. The product-inhibited complex is thought to be composed of a peroxide (O22-) or hydroperoxide (HO2-) species bound to Mn ion and formed from an unknown PCET mechanism. PCET mechanisms of proteins are typically not known due to difficulties in detecting the protonation states of specific residues that coincide with the electronic state of the redox center. To shed light on the mechanism, we combine neutron diffraction and X-ray absorption spectroscopy of the product-bound, trivalent, and divalent states of the enzyme to reveal the positions of all the atoms, including hydrogen, and the electronic configuration of the metal ion. The data identifies the product-inhibited complex, and a PCET mechanism of inhibition is constructed.

Computational analysis of phytocompounds in Centella asiatica for its antifibrotic and drug-likeness properties - Herb to drug study

Oral submucous fibrosis (OSMF) is a potentially malignant disorder with no permanent cure that affects the quality of life due to trismus. Computational pharmacology has accelerated the discovery of drug candidates for the treatment of incurable diseases. The present study aimed to screen the compounds of the miracle herb Centella asiatica with drug-likeness properties based on the absorption, distribution, metabolism, and excretion (ADME) properties. The pharmacological actions of these screened compounds against OSMF were identified by network pharmacology, gene ontology, pathway enrichment analysis, molecular docking, and simulation. Fifteen drug-like ligands were identified after virtual screening viz; asiatic acid, kaempferol, quercetin, luteolin, apigenin, bayogenin, gallic acid, isothankunic acid, madecassic acid, madasiatic acid, arjunolic acid, terminolic acid, catechin, epicatechin, and nobiletin. 850 potential targets were predicted for the ligands, which were analyzed against 354 proteins associated with OSMF. Compound pathway analysis and disease pathway analysis identified 53 common proteins. The GO enrichment analysis identified 472 biological process terms, 76 molecular function terms, and 44 cellular component terms. Pathway enrichment analysis predicted 142 KEGG pathways, 35 Biocarta pathways, and 236 Reactome pathways for the target proteins. The analysis revealed that the herb targets crucial events of fibrosis such as inflammation, oxidative stress, apoptosis, collagen deposition, and epithelial-mesenchymal transition. The common 53 proteins were used for protein-protein interaction (PPI) network analysis, which revealed 4 key proteins interacting with the phytocompounds viz; transforming growth factor-β1 (TGF-β1), mothers against decapentaplegic-3 (SMAD-3), mitogen-activated protein kinase-1 (MAPK-1) and proto-oncogene tyrosine-protein kinase (SRC). Molecular docking revealed that all ligands had a good binding affinity to the target proteins. Bayogenin had the highest binding affinity towards MAPK-1 (-9.7 kcal/mol), followed by isothankunic acid towards SRC protein (-9.3 kcal/mol). Madasiatic acid had the highest binding affinity to SMAD-3 (-7.6 kcal/mol) and TGF-β1 (-7.1 kcal/mol). Molecular dynamics simulation demonstrated stable ligand protein interactions of bayogenin and MAPK complex, isothankunic acid and SRC complex. This in silico study is the first to identify potential phytochemicals present in Centella asiatica and their target molecules, which might be responsible for reversing OSMF.

Metabolomics and network pharmacology exploration of the effects of bile acids on carotid atherosclerosis and potential underlying mechanisms

Background

Bile acids (BAs), products of gut microbiota metabolism, have long been implicated in atherosclerotic disease pathogenesis. Characterizing the serum bile acid profile and exploring its potential role in carotid atherosclerosis (CAS) development are crucial tasks.

Methods

In this study, we recruited 73 patients with CAS as the disease group and 77 healthy individuals as the control group. We systematically measured the serum concentrations of 15 bile acids using ultrahigh-performance liquid chromatography-mass spectrometry (UPLC-MS/MS). Multivariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression were applied to analyze the impact of bile acids on the disease and select the key BAs. The possible molecular mechanism was elucidated by network pharmacology.

Results

(1) The BA profile of patients with CAS significantly differed. (2) Multifactorial logistic regression analysis identified elevated levels of GCDCA (OR: 1.01, P < 0.001), DCA (OR: 1.01, P = 0.005), and TDCA (OR: 1.05, P = 0.002) as independent risk factors for CAS development. Conversely, GCA (OR: 0.99, P = 0.020), LCA (OR: 0.83, P = 0.002), and GUDCA (OR: 0.99, P = 0.003) were associated with protective effects against the disease. GCA, DCA, LCA, and TDCA were identified as the four key BAs. (3) TNF, FXR, GPBAR1, ESR1 and ACE were predicted to be targets of BAs against AS. These four BAs potentially impact AS progression by triggering signaling pathways, including cAMP, PPAR, and PI3K-AKT pathways, via their targets.

Conclusion

This study offers valuable insights into potential therapeutic strategies for atherosclerosis that target bile acids.

Genomic variants associated with age at diagnosis of childhood-onset type 1 diabetes

Age at diagnosis (AAD) of Type 1 diabetes (T1D) is determined by the age at onset of the autoimmune attack and by the rate of beta cell destruction that follows. Twin studies found that T1D AAD is strongly influenced by genetics, notably in young children. In young UK, Finnish, Sardinian patients AAD-associated genomic variants were previously identified, which may vary across populations and with time. In 1956 children of European ancestry born in mainland France in 1980-2008 who declared T1D before 15 years, we tested 94 T1D-associated SNPs for their association with AAD using nonparametric Kruskal-Wallis test. While high-risk HLA genotypes were not found to be associated with AAD, fourteen SNPs located in 12 non-HLA loci showed a strong association (2.9 × 10-12 < P < 1.4 × 10-3 after FDR correction). Four of these loci have been associated with AAD in previous cohorts (GSDMB, IL2, TNFAIP3, IL1), supporting a partially shared genetic influence on AAD of T1D in the studied European populations. In contrast, the association of 8 new loci CLEC16A, TYK2, ERBB3, CCR7, FCRL3, DNAH2, FGF3/4, and HPSE2 with AAD is novel. The 12 protein-coding genes located within these loci are involved in major immune pathways or in predisposition to other autoimmune diseases, which suggests a prominent role for these genes in the early immune mechanisms of beta cell destruction.

Transcriptome signatures of the medial prefrontal cortex underlying GABAergic control of resilience to chronic stress exposure

Analyses of postmortem human brains and preclinical studies of rodents have identified somatostatin (SST)-positive interneurons as key elements that regulate the vulnerability to stress-related psychiatric disorders. Conversely, genetically induced disinhibition of SST neurons or brain region-specific chemogenetic activation of SST neurons in mice results in stress resilience. Here, we used RNA sequencing of mice with disinhibited SST neurons to characterize the transcriptome changes underlying GABAergic control of stress resilience. We found that stress resilience of male but not female mice with disinhibited SST neurons is characterized by resilience to chronic stress-induced transcriptome changes in the medial prefrontal cortex. Interestingly, the transcriptome of non-stressed stress-resilient male mice resembled the transcriptome of chronic stress-exposed stress-vulnerable mice. However, the behavior and the serum corticosterone levels of non-stressed stress-resilient mice showed no signs of physiological stress. Most strikingly, chronic stress exposure of stress-resilient mice was associated with an almost complete reversal of their chronic stress-like transcriptome signature, along with pathway changes indicating stress-induced enhancement of mRNA translation. Behaviorally, the mice with disinhibited SST neurons were not only resilient to chronic stress-induced anhedonia - they also showed an inversed anxiolytic-like response to chronic stress exposure that mirrored the chronic stress-induced reversal of the chronic stress-like transcriptome signature. We conclude that GABAergic dendritic inhibition by SST neurons exerts bidirectional control over behavioral vulnerability and resilience to chronic stress exposure that is mirrored in bidirectional changes in expression of putative stress resilience genes, through a sex-specific brain substrate.

Integrated ML-Based Strategy Identifies Drug Repurposing for Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) affects an estimated global population of around 3 million individuals. IPF is a medical condition with an unknown cause characterized by the formation of scar tissue in the lungs, leading to progressive respiratory disease. Currently, there are only two FDA-approved small molecule drugs specifically for the treatment of IPF and this has created a demand for the rapid development of drugs for IPF treatment. Moreover, denovo drug development is time and cost-intensive with less than a 10% success rate. Drug repurposing currently is the most feasible option for rapidly making the drugs to market for a rare and sporadic disease. Normally, the repurposing of drugs begins with a screening of FDA-approved drugs using computational tools, which results in a low hit rate. Here, an integrated machine learning-based drug repurposing strategy is developed to significantly reduce the false positive outcomes by introducing the predock machine-learning-based predictions followed by literature and GSEA-assisted validation and drug pathway prediction. The developed strategy is deployed to 1480 FDA-approved drugs and to drugs currently in a clinical trial for IPF to screen them against "TGFB1", "TGFB2", "PDGFR-a", "SMAD-2/3", "FGF-2", and more proteins resulting in 247 total and 27 potentially repurposable drugs. The literature and GSEA validation suggested that 72 of 247 (29.14%) drugs have been tried for IPF, 13 of 247 (5.2%) drugs have already been used for lung fibrosis, and 20 of 247 (8%) drugs have been tested for other fibrotic conditions such as cystic fibrosis and renal fibrosis. Pathway prediction of the remaining 142 drugs was carried out resulting in 118 distinct pathways. Furthermore, the analysis revealed that 29 of 118 pathways were directly or indirectly involved in IPF and 11 of 29 pathways were directly involved. Moreover, 15 potential drug combinations are suggested for showing a strong synergistic effect in IPF. The drug repurposing strategy reported here will be useful for rapidly developing drugs for treating IPF and other related conditions.

DiPPI: A Curated Data Set for Drug-like Molecules in Protein-Protein Interfaces

Proteins interact through their interfaces, and dysfunction of protein-protein interactions (PPIs) has been associated with various diseases. Therefore, investigating the properties of the drug-modulated PPIs and interface-targeting drugs is critical. Here, we present a curated large data set for drug-like molecules in protein interfaces. We further introduce DiPPI (Drugs in Protein-Protein Interfaces), a two-module web site to facilitate the search for such molecules and their properties by exploiting our data set in drug repurposing studies. In the interface module of the web site, we present several properties, of interfaces, such as amino acid properties, hotspots, evolutionary conservation of drug-binding amino acids, and post-translational modifications of these residues. On the drug-like molecule side, we list drug-like small molecules and FDA-approved drugs from various databases and highlight those that bind to the interfaces. We further clustered the drugs based on their molecular fingerprints to confine the search for an alternative drug to a smaller space. Drug properties, including Lipinski's rules and various molecular descriptors, are also calculated and made available on the web site to guide the selection of drug molecules. Our data set contains 534,203 interfaces for 98,632 protein structures, of which 55,135 are detected to bind to a drug-like molecule. 2214 drug-like molecules are deposited on our web site, among which 335 are FDA-approved. DiPPI provides users with an easy-to-follow scheme for drug repurposing studies through its well-curated and clustered interface and drug data and is freely available at http://interactome.ku.edu.tr:8501.

Broadcasters, receivers, functional groups of metabolites, and the link to heart failure by revealing metabolomic network connectivity

BACKGROUND AND OBJECTIVE

Blood-based small molecule metabolites offer easy accessibility and hold significant potential for insights into health processes, the impact of lifestyle, and genetic variation on disease, enabling precise risk prevention. In a prospective study with records of heart failure (HF) incidence, we present metabolite profiling data from individuals without HF at baseline.

METHODS

We uncovered the interconnectivity of metabolites using data-driven and causal networks augmented with polygenic factors. Exploring the networks, we identified metabolite broadcasters, receivers, mediators, and subnetworks corresponding to functional classes of metabolites, and provided insights into the link between metabolomic architecture and regulation in health. We incorporated the network structure into the identification of metabolites associated with HF to control the effect of confounding metabolites.

RESULTS

We identified metabolites associated with higher and lower risk of HF incidence, such as glycine, ureidopropionic and glycocholic acids, and LPC 18:2. These associations were not confounded by the other metabolites due to uncovering the connectivity among metabolites and adjusting each association for the confounding metabolites. Examples of our findings include the direct influence of asparagine on glycine, both of which were inversely associated with HF. These two metabolites were influenced by polygenic factors and only essential amino acids, which are not synthesized in the human body and are obtained directly from the diet.

CONCLUSION

Metabolites may play a critical role in linking genetic background and lifestyle factors to HF incidence. Revealing the underlying connectivity of metabolites associated with HF strengthens the findings and facilitates studying complex conditions like HF.

Yixin-Fumai granules modulate autophagy through the PI3K/AKT/FOXO pathway and lead to amelioration of aging mice with sick sinus syndrome

OBJECTIVE

By employing network pharmacology alongside molecular docking techniques, we can delve into the intricate workings of Yixin-Fumai granules (YXFMs) and their impact on sick sinus syndrome (SSS) within wrinkles mice. Specifically, we aim to understand how YXFMs enhance autophagy through the PI3K/AKT/FOXO path.

METHODS

The active ingredients and medicinal uses of Ginseng, ligusticum wallichii, Ophiopogon, Schisandra, salvia, and astragalus were compiled using the BATMAN-TCM database. We also used Genecards, OMIM, and Disgenet files to identify the disease goals. A hierarchical diagram of "disease-drug-key targets" was generated using the Cytoscape programs. In addition, we established a target protein interaction (PPI) network using the STRING database. Then, the Cluster Profiler R package was used to conduct GO functional enrichment evaluation and KEGG pathway enrichment analyses of the targets. Based on the PPI system, we chose the top communicating targets and substances over molecular docking. In vivo studies were performed to validate these selections further. The mouse model was induced to study the damaged sinoatrial node (SAN) in mice with lower heart rates due to age-related changes. Electrocardiogram and Masson staining assessments were performed to obtain the results. The transmission electron microscope was used to assess the autophagy level of SAN cells. Western blot was employed to analyze the impact of YXFMs on protein expression in the PI3K/AKT/FOXO signaling process throughout SSS therapy in aging mice.

RESULTS

One hundred forty-two active ingredients, 1858 targets, 1226 disease targets, and 266 intersection targets were obtained. The key targets of the PPI network encompassed TP53, AKT1, CTNNB1, INS, and TNF, among others. According to GO functional analysis, the mechanism underlying YXFMs in SSS treatment may primarily be associated with the control of ion transport across membranes, cardiac contraction, regulation of blood circulation, and other biological processes. Based on the results of KEGG pathway enrichment analysis, it was determined that they were mainly enriched in multiple pathways of signaling such as the PI3K-Akt signaling route, MAPK signaling process, AGE-RAGE signaling path, FOXO signaling path, HIF-1 signaling process, and several other paths. Molecular docking demonstrated that five compounds had excellent binding to the key candidate target proteins AKT1 and INS. Through the in vivo studies, we noticed notable effects when administering YXFMs. These effects included the suppression of aging-induced SSS, a decrease in the R-R interval, a rise in heart rate, a reduction in fibrosis, a boost in the autophagy process level, and a spike in the levels of expression of key protein molecules in the PI3K/AKT/FOXO signaling path.

CONCLUSION

This research has made preliminary predictions about the potential of YXFMs in treating SSS. It suggests that YXFMs may have the ability to target key proteins and critical paths associated with the condition. Further testing has been conducted to discover new findings and evidence of ideas for tackling SSS triggered by aging.

Alzheimer's Disease Knowledge Graph Enhances Knowledge Discovery and Disease Prediction

Background

Alzheimer's disease (AD), a progressive neurodegenerative disorder, continues to increase in prevalence without any effective treatments to date. In this context, knowledge graphs (KGs) have emerged as a pivotal tool in biomedical research, offering new perspectives on drug repurposing and biomarker discovery by analyzing intricate network structures. Our study seeks to build an AD-specific knowledge graph, highlighting interactions among AD, genes, variants, chemicals, drugs, and other diseases. The goal is to shed light on existing treatments, potential targets, and diagnostic methods for AD, thereby aiding in drug repurposing and the identification of biomarkers.

Results

We annotated 800 PubMed abstracts and leveraged GPT-4 for text augmentation to enrich our training data for named entity recognition (NER) and relation classification. A comprehensive data mining model, integrating NER and relationship classification, was trained on the annotated corpus. This model was subsequently applied to extract relation triplets from unannotated abstracts. To enhance entity linking, we utilized a suite of reference biomedical databases and refine the linking accuracy through abbreviation resolution. As a result, we successfully identified 3,199,276 entity mentions and 633,733 triplets, elucidating connections between 5,000 unique entities. These connections were pivotal in constructing a comprehensive Alzheimer's Disease Knowledge Graph (ADKG). We also integrated the ADKG constructed after entity linking with other biomedical databases. The ADKG served as a training ground for Knowledge Graph Embedding models with the high-ranking predicted triplets supported by evidence, underscoring the utility of ADKG in generating testable scientific hypotheses. Further application of ADKG in predictive modeling using the UK Biobank data revealed models based on ADKG outperforming others, as evidenced by higher values in the areas under the receiver operating characteristic (ROC) curves.

Conclusion

The ADKG is a valuable resource for generating hypotheses and enhancing predictive models, highlighting its potential to advance AD's disease research and treatment strategies.

Network pharmacology: an efficient but underutilized approach in oral, head and neck cancer therapy-a review

The application of network pharmacology (NP) has advanced our understanding of the complex molecular mechanisms underlying diseases, including neck, head, and oral cancers, as well as thyroid carcinoma. This review aimed to explore the therapeutic potential of natural network pharmacology using compounds and traditional Chinese medicines for combating these malignancies. NP serves as a pivotal tool that provides a comprehensive view of the interactions among compounds, genes, and diseases, thereby contributing to the advancement of disease treatment and management. In parallel, this review discusses the significance of publicly accessible databases in the identification of oral, head, and neck cancer-specific genes. These databases, including those for head and neck oral cancer, head and neck cancer, oral cancer, and genomic variants of oral cancer, offer valuable insights into the genes, miRNAs, drugs, and genetic variations associated with these cancers. They serve as indispensable resources for researchers, clinicians, and drug developers, contributing to the pursuit of precision medicine and improved treatment of these challenging malignancies. In summary, advancements in NP could improve the globalization and modernization of traditional medicines and prognostic targets as well as aid in the development of innovative drugs. Furthermore, this review will be an eye-opener for researchers working on drug development from traditional medicines by applying NP approaches.

Network Pharmacology Reveals Curcuma aeruginosa Roxb. Regulates MAPK and HIF-1 Pathways to Treat Androgenetic Alopecia

Androgenetic alopecia (AGA) is the most prevalent hair loss disorder worldwide, driven by excessive sensitivity or response to androgen. Herbal extracts, such as Curcuma aeruginosa Roxb., have shown promise in AGA treatment due to their anti-androgenic activities and hair growth effects. However, the precise mechanism of action remains unclear. Hence, this study aims to elucidate the active compounds, putative targets, and underlying mechanisms of C. aeruginosa for the therapy of AGA using network pharmacology and molecular docking. This study identified 66 bioactive compounds from C. aeruginosa, targeting 59 proteins associated with AGA. Eight hub genes were identified from the protein-protein interaction network, namely, CASP3, AKT1, AR, IL6, PPARG, STAT3, HIF1A, and MAPK3. Topological analysis of components-targets network revealed trans-verbenol, myrtenal, carvone, alpha-atlantone, and isoaromandendrene epoxide as the core components with potential significance in AGA treatment. The molecular docking verified the binding affinity between the hub genes and core compounds. Moreover, the enrichment analyses showed that C. aeruginosa is involved in hormone response and participates in HIF-1 and MAPK pathways to treat AGA. Overall, this study contributes to understanding the potential anti-AGA mechanism of C. aeruginosa by highlighting its multi-component interactions with several targets involved in AGA pathogenesis.

Fusion Genes Landscape of Lung Cancer Patients From Inner Mongolia, China

Lung cancer is the leading cause of cancer-related deaths globally. Gene fusion, a key driver of tumorigenesis, has led to the identification of numerous driver gene fusions for lung cancer diagnosis and treatment. However, previous studies focused on Western populations, leaving the possibility of unrecognized lung cancer-associated gene fusions specific to Inner Mongolia due to its unique genetic background and dietary habits. To address this, we conducted DNA sequencing analysis on tumor and adjacent nontumor tissues from 1200 individuals with lung cancer in Inner Mongolia. Our analysis established a comprehensive fusion gene landscape specific to lung cancer in Inner Mongolia, shedding light on potential region-specific molecular mechanisms underlying the disease. Compared to Western cohorts, we observed a higher occurrence of ALK and RET fusions in Inner Mongolian patients. Additionally, we discovered eight novel fusion genes in three patients: SLC34A2-EPHB1, CCT6P3-GSTP1, BARHL2-APC, HRAS-MELK, FAM134B-ERBB2, ABCB1-GIPC1, GPR98-ALK, and FAM134B-SALL1. These previously unreported fusion genes suggest potential regional specificity. Furthermore, we characterized the fusion genes' structures based on breakpoints and described their impact on major functional gene domains. Importantly, the identified novel fusion genes exhibited significant clinical and pathological relevance. Notably, patients with SLC34A2-EPHB1, CCT6P3-GSTP1, and BARHL2-APC fusions showed sensitivity to the combination of chemotherapy and immunotherapy. Patients with HRAS-MELK, FAM134B-ERBB2, and ABCB1-GIPC1 fusions showed sensitivity to chemotherapy. In summary, our study provides novel insights into the frequency, distribution, and characteristics of specific fusion genes, offering valuable guidance for the development of effective clinical treatments, particularly in Inner Mongolia.

REMEMProt: a resource of membrane-enriched proteome profiles, their disease associations, and biomarker status

The differential expression of plasma membrane proteins is integrally analyzed for their diagnosis, prognosis, and therapeutic applications in diverse clinical manifestations. Necessarily, distinct membrane protein enrichment methods and mass spectrometry platforms are employed for their global and relative quantitation. First of its kind to explore, we compiled membrane-associated proteomes in human and mouse systems into a database named, Resource of Experimental Membrane-Enriched Mass spectrometry-derived Proteome (REMEMProt). It currently hosts 14,626 proteins (9,507 proteins in Homo sapiens; 5,119 proteins in Mus musculus) with information on their membrane-protein enrichment methods, experimental/physiological context of detection in cells or tissues, transmembrane domain analysis, and their current attribution as biomarkers. Based on these annotations and the transmembrane domain analysis in proteins or their binary/complex protein-protein interactors, REMEMProt facilitates the assessment of the plasma membrane localization potential of proteins through batch query. A cross-study enrichment analysis platform is enabled in REMEMProt for comparative analysis of proteomes using novel/modified membrane enrichment methods and evaluation of methods for targeted enrichment of membrane proteins. REMEMProt data are made freely accessible to explore and download at https://rememprot.ciods.in/.

Exploring gene regulatory interaction networks and predicting therapeutic molecules for hypopharyngeal cancer and EGFR-mutated lung adenocarcinoma

Hypopharyngeal cancer is a disease that is associated with EGFR-mutated lung adenocarcinoma. Here we utilized a bioinformatics approach to identify genetic commonalities between these two diseases. To this end, we examined microarray datasets from GEO (Gene Expression Omnibus) to identify differentially expressed genes, common genes, and hub genes between the selected two diseases. Our analyses identified potential therapeutic molecules for the selected diseases based on 10 hub genes with the highest interactions according to the degree topology method and the maximum clique centrality (MCC). These therapeutic molecules may have the potential for simultaneous treatment of these diseases.

Preclinical side effect prediction through pathway engineering of protein interaction network models

Modeling tools aim to predict potential drug side effects, although they suffer from imperfect performance. Specifically, protein-protein interaction models predict drug effects from proteins surrounding drug targets, but they tend to overpredict drug phenotypes and require well-defined pathway phenotypes. In this study, we used PathFX, a protein-protein interaction tool, to predict side effects for active ingredient-side effect pairs extracted from drug labels. We observed limited performance and defined new pathway phenotypes using pathway engineering strategies. We defined new pathway phenotypes using a network-based and gene expression-based approach. Overall, we discovered a trade-off between sensitivity and specificity values and demonstrated a way to limit overprediction for side effects with sufficient true positive examples. We compared our predictions to animal models and demonstrated similar performance metrics, suggesting that protein-protein interaction models do not need perfect evaluation metrics to be useful. Pathway engineering, through the inclusion of true positive examples and omics measurements, emerges as a promising approach to enhance the utility of protein interaction network models for drug effect prediction.

A novel bioinformatics strategy to uncover the active ingredients and molecular mechanisms of Bai Shao in the treatment of non-alcoholic fatty liver disease

Introduction: As a new discipline, network pharmacology has been widely used to disclose the material basis and mechanism of Traditional Chinese Medicine in recent years. However, numerous researches indicated that the material basis of TCMs identified based on network pharmacology was the mixtures of beneficial and harmful substances rather than the real material basis. In this work, taking the anti-NAFLD (non-alcoholic fatty liver disease) effect of Bai Shao (BS) as a case, we attempted to propose a novel bioinformatics strategy to uncover the material basis and mechanism of TCMs in a precise manner. Methods: In our previous studies, we have done a lot work to explore TCM-induced hepatoprotection. Here, by integrating our previous studies, we developed a novel computational pharmacology method to identify hepatoprotective ingredients from TCMs. Then the developed method was used to discover the material basis and mechanism of Bai Shao against Non-alcoholic fatty liver disease by combining with the techniques of molecular network, microarray data analysis, molecular docking, and molecular dynamics simulation. Finally, literature verification method was utilized to validate the findings. Results: A total of 12 ingredients were found to be associated with the anti-NAFLD effect of BS, including monoterpene glucosides, flavonoids, triterpenes, and phenolic acids. Further analysis found that IL1-β, IL6, and JUN would be the key targets. Interestingly, molecular docking and molecular dynamics simulation analysis showed that there indeed existed strong and stable binding affinity between the active ingredients and the key targets. In addition, a total of 23 NAFLD-related KEGG pathways were enriched. The major biological processes involved by these pathways including inflammation, apoptosis, lipid metabolism, and glucose metabolism. Of note, there was a great deal of evidence available in the literature to support the findings mentioned above, indicating that our method was reliable. Discussion: In summary, the contributions of this work can be summarized as two aspects as follows. Firstly, we systematically elucidated the material basis and mechanism of BS against NAFLD from multiple perspectives. These findings further enhanced the theoretical foundation of BS on NAFLD. Secondly, a novel computational pharmacology research strategy was proposed, which would assist network pharmacology to uncover the scientific connotation TCMs in a more precise manner.

Down-regulation of SLC14A1 in prostate cancer activates CDK1/CCNB1 and mTOR pathways and promotes tumor progression

Prostate cancer (PCa) is the most common cancer among men in the United States and the leading cause of cancer-related death. The Solute Carrier Family 14 Member 1 (SLC14A1) is a member of urea transporters which are important for the regulation of urine concentration. However, the physiological significance of SLC14A1 in PCa still remains unclear. In the present study, via bioinformatics analysis and experiments, we found that expression of SLC14A1 is significantly decreased in PCa progression, which could be attributed to hypermethylation on SLC14A1 promoter region. Moreover, its low expression and hypermethylation on SLC14A1 promoter are closely related to the poor prognosis of PCa patients. On the other hand, overexpression of SLC14A1 inhibited cell proliferation and metastasis while its overexpression also suppressed CDK1/CCNB1 pathway and mTOR/MMP-9 signaling pathway. Additionally, SLC14A1 expression is enriched in prostate basal-type cells. In summary, our study indicates that its low expression level and promoter hypermethylation of SLC14A1 may represent novel indicators for PCa progression and prognosis, and SLC14A1 could inhibit the progression of PCa.

Angelicin: A leading culprit involved in fructus Psoraleae liver injury via inhibition of VKORC1

ETHNOPHARMACOLOGICAL RELEVANCE

The adverse effects of Fructus Psoraleae (FP), especially liver injury, have attracted wide attention in recent years.

AIM OF THE STUDY

To establish a system to explore potential hepatotoxic targets and the chief culprit of liver injury based on clinical experience, network pharmacological method, molecular docking, and in vitro and in vivo experiments.

MATERIALS AND METHODS

Clinical applications and adverse reactions to FP were obtained from public literatures. Components absorbed in the blood were selected as candidates to search for potential active targets (PATs) of FP. Subsequently, potential pharmacological core targets (PPCTs) were screened through the "drug targets-disease targets" network. Non-drug active targets (NPATs) were obtained by subtracting the PPCTs from the PATs. The potential hepatotoxic targets (PHTs) of FP were the intersection targets obtained from Venn analysis using NPATs, hepatotoxic targets, and adverse drug reaction (ADR) targets provided by the databases. Then, potential hepatotoxic components and targets were obtained using the "NPATS-component" network relationship. Molecular docking and in vitro and in vivo hepatotoxicity experiments were performed to verify the targets and related components.

RESULTS

Overall, 234 NPATs were acquired from our analysis, and 6 targets were identified as PHTs. Results from molecular docking and in vitro and in vivo experiments showed that angelicin is the leading cause of liver injury in FP, and VKORC1 plays an important role.

CONCLUSION

The results indicate that six targets, especially VKORC1, are associated with the PHTs of FP, and angelicin is the leading culprit involved in FP liver injury via inhibition of VKORC1.

Exploring molecular targets: herbal isolates in cervical cancer therapy

OBJECTIVE

Cervical cancer (CxCa) stands as a significant global health challenge, ranking fourth in cancer-related mortality among the female population. While chemotherapy regimens have demonstrated incremental progress in extending overall survival, the outlook for recurrent CxCa patients remains disheartening. An imperative necessity arises to delve into innovative therapeutic avenues, with molecular targeted therapy emerging as a promising candidate. Previous investigations have shed light on the therapeutic effectiveness of five distinct herbal compounds, epicatechin, curcumin, myricetin, jatrorrhizine, and arborinine, within the context of CxCa.

METHODS

A systems biology approach was employed to discern differentially expressed genes (DEGs) in CxCa tissues relative to healthy cervical epithelial tissues. A protein-protein interaction network (PPIN) was constructed, anchored in the genes related to CxCa. The central genes were discerned within the PPIN, and Kaplan-Meier survival curves explored their prognostic significance. An assessment of the binding affinity of the selected herbal compounds to the master regulator of prognostic markers in CxCa was conducted.

RESULTS

A significant correlation between the overexpression of MYC, IL6, JUN, RRM2, and VEGFA and an adverse prognosis in CxCa was indicated. The regulation of these markers is notably influenced by the transcription factor CEBPD. Molecular docking analysis indicated that the binding affinity between myricetin and the CEBPD DNA binding site was robust.

CONCLUSION

The findings presented herein have unveiled pivotal genes and pathways that play a central role in the malignant transformation of CxCa. CEBPD has emerged as a potential target for harnessing the therapeutic potential of myricetin in this context.

Bioinformatics and system biology approach to identify potential common pathogenesis for COVID-19 infection and sarcopenia

Sarcopenia is a condition characterized by age-related loss of muscle mass and strength. Increasing evidence suggests that patients with sarcopenia have higher rates of coronavirus 2019 (COVID-19) infection and poorer post-infection outcomes. However, the exact mechanism and connections between the two is unknown. In this study, we used high-throughput data from the GEO database for sarcopenia (GSE111016) and COVID-19 (GSE171110) to identify common differentially expressed genes (DEGs). We conducted GO and KEGG pathway analyses, as well as PPI network analysis on these DEGs. Using seven algorithms from the Cytoscape plug-in cytoHubba, we identified 15 common hub genes. Further analyses included enrichment, PPI interaction, TF-gene and miRNA-gene regulatory networks, gene-disease associations, and drug prediction. Additionally, we evaluated immune cell infiltration with CIBERSORT and assessed the diagnostic accuracy of hub genes for sarcopenia and COVID-19 using ROC curves. In total, we identified 66 DEGs (34 up-regulated and 32 down-regulated) and 15 hub genes associated with sarcopenia and COVID-19. GO and KEGG analyses revealed functions and pathways between the two diseases. TF-genes and TF-miRNA regulatory network suggest that FOXOC1 and hsa-mir-155-5p may be identified as key regulators, while gene-disease analysis showed strong correlations with hub genes in schizophrenia and bipolar disorder. Immune infiltration showed a correlation between the degree of immune infiltration and the level of infiltration of different immune cell subpopulations of hub genes in different datasets. The ROC curves for ALDH1L2 and KLF5 genes demonstrated their potential as diagnostic markers for both sarcopenia and COVID-19. This study suggests that sarcopenia and COVID-19 may share pathogenic pathways, and these pathways and hub genes offer new targets and strategies for early diagnosis, effective treatment, and tailored therapies for sarcopenia patients with COVID-19.

Exploration of the Mechanisms of Bu-Yang-Huan-Wu Decoction in the Treatment of Diabetic Peripheral Neuropathy by Integrating of Serum Pharmacochemistry and Network Pharmacology

Diabetic peripheral neuropathy (DPN) is a significant and frequent complication of diabetes. Bu-Yang-Huan-Wu Decoction (BHD) is a classic traditional Chinese herbal prescription that is commonly used in modern clinical practice for the effective treatment of DPN, but the underlying mechanism is not yet clearly defined. The chemical constituents of BHD were characterized by UPLC-Q-Orbitrap HR MS/MS, and a total of 101 chemical components were identified, including 30 components absorbed into blood. An interaction network of "compound-target-disease" interactions was constructed based on the compounds detected absorbed in blood and their corresponding targets of diabetic neuropathy acquired from disease gene databases, and the possible biological targets and potential signalling pathways of BHD were predicted via network pharmacology analysis. Subsequently, methylglyoxal-induced (MGO-induced) Schwann cells (SCs) were used to identify the active ingredients in blood components of BHD and verify the molecular mechanisms of BHD. Through network topological analysis, 30 shared targets strongly implicated in the anti-DPN effects of BHD were identifed. Combined network pharmacology and in vitro cellular analysis, we found that the active ingredient of BHD may treat DPN by modulating the AGEs/RAGE pathway. This study provides valuable evidence for future mechanistic studies and potential therapeutic applications for patients with DPN.

Exploring the action mechanism of Gegensan in the treatment of alcoholic liver disease based on network pharmacology and bioinformatics

Gegensan (GGS) has been reported for the treatment of alcoholic liver disease (ALD), but its therapeutic mechanism is still unclear. This paper aims to determine the therapeutic mechanism and targets of action of GGS on alcoholic liver disease utilizing network pharmacology and bioinformatics. The active ingredients in GGS were screened in the literature and databases, and common targets of ALD were then obtained from public databases to construct the network diagram of traditional Chinese medicine-active ingredient targets. Based on the common targets, Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to find target enrichment pathways, and the core targets were screened out by combining differential analysis and protein-protein interaction network analysis. Molecular docking was performed to verify the binding effect between the core targets and the corresponding active ingredients. ALD and GGS have 84 common targets, corresponding to 91 active ingredients. After subsequent differential analysis and protein-protein interaction network analysis, 10 core targets were identified. Gene Ontology and KEGG enrichment analyses showed that the main BPs corresponding to the common targets included the response to lipopolysaccharide, inflammatory response, etc. The KEGG pathways involved in the regulation of the common targets included the lipid-atherosclerosis pathway and the alcoholic liver disease pathway, etc. Further molecular docking showed that the core targets CYP1A1, CYP1A2, CXCL8, ADH1C, MMP1, SERPINE1, COL1A1, APOB, MMP1, and their corresponding 4 active ingredients, Naringenin, Kaempferol, Quercetin, and Stigmasterol, have a greater docking potential. The above results suggest that GGS can regulate lipid metabolism and inflammatory response in the ALD process, and alleviate the lipid accumulation and oxidative stress caused by ethanol. This study analyzed the core targets and mechanisms of action of GGS on ALD, which provides certain theoretical support for the further development of GGS in the treatment of ALD, and provides a reference for the subsequent research on the treatment of ALD.

Ultrasound Neuromodulation of an Anti-Inflammatory Pathway at the Spleen Improves Experimental Pulmonary Hypertension

BACKGROUND

Inflammation is pathogenically implicated in pulmonary arterial hypertension; however, it has not been adequately targeted therapeutically. We investigated whether neuromodulation of an anti-inflammatory neuroimmune pathway involving the splenic nerve using noninvasive, focused ultrasound stimulation of the spleen (sFUS) can improve experimental pulmonary hypertension.

METHODS

Pulmonary hypertension was induced in rats either by Sugen 5416 (20 mg/kg SQ) injection, followed by 21 (or 35) days of hypoxia (sugen/hypoxia model), or by monocrotaline (60 mg/kg IP) injection (monocrotaline model). Animals were randomized to receive either 12-minute-long sessions of sFUS daily or sham stimulation for 14 days. Catheterizations, echocardiography, indices of autonomic function, lung and heart histology and immunohistochemistry, spleen flow cytometry, and lung single-cell RNA sequencing were performed after treatment to assess the effects of sFUS.

RESULTS

Splenic denervation right before induction of pulmonary hypertension results in a more severe disease phenotype. In both sugen/hypoxia and monocrotaline models, sFUS treatment reduces right ventricular systolic pressure by 25% to 30% compared with sham treatment, without affecting systemic pressure, and improves right ventricular function and autonomic indices. sFUS reduces wall thickness, apoptosis, and proliferation in small pulmonary arterioles, suppresses CD3+ and CD68+ cell infiltration in lungs and right ventricular fibrosis and hypertrophy and lowers BNP (brain natriuretic peptide). Beneficial effects persist for weeks after sFUS discontinuation and are more robust with early and longer treatment. Splenic denervation abolishes sFUS therapeutic benefits. sFUS partially normalizes CD68+ and CD8+ T-cell counts in the spleen and downregulates several inflammatory genes and pathways in nonclassical and classical monocytes and macrophages in the lung. Differentially expressed genes in those cell types are significantly enriched for human pulmonary arterial hypertension-associated genes.

CONCLUSIONS

sFUS causes dose-dependent, sustained improvement of hemodynamic, autonomic, laboratory, and pathological manifestations in 2 models of experimental pulmonary hypertension. Mechanistically, sFUS normalizes immune cell populations in the spleen and downregulates inflammatory genes and pathways in the lung, many of which are relevant in human disease.

In-vivo neuronal dysfunction by Aβ and tau overlaps with brain-wide inflammatory mechanisms in Alzheimer's disease

The molecular mechanisms underlying neuronal dysfunction in Alzheimer's disease (AD) remain uncharacterized. Here, we identify genes, molecular pathways and cellular components associated with whole-brain dysregulation caused by amyloid-beta (Aβ) and tau deposits in the living human brain. We obtained in-vivo resting-state functional MRI (rs-fMRI), Aβ- and tau-PET for 47 cognitively unimpaired and 16 AD participants from the Translational Biomarkers in Aging and Dementia cohort. Adverse neuronal activity impacts by Aβ and tau were quantified with personalized dynamical models by fitting pathology-mediated computational signals to the participant's real rs-fMRIs. Then, we detected robust brain-wide associations between the spatial profiles of Aβ-tau impacts and gene expression in the neurotypical transcriptome (Allen Human Brain Atlas). Within the obtained distinctive signature of in-vivo neuronal dysfunction, several genes have prominent roles in microglial activation and in interactions with Aβ and tau. Moreover, cellular vulnerability estimations revealed strong association of microglial expression patterns with Aβ and tau's synergistic impact on neuronal activity (q < 0.001). These results further support the central role of the immune system and neuroinflammatory pathways in AD pathogenesis. Neuronal dysregulation by AD pathologies also associated with neurotypical synaptic and developmental processes. In addition, we identified drug candidates from the vast LINCS library to halt or reduce the observed Aβ-tau effects on neuronal activity. Top-ranked pharmacological interventions target inflammatory, cancer and cardiovascular pathways, including specific medications undergoing clinical evaluation in AD. Our findings, based on the examination of molecular-pathological-functional interactions in humans, may accelerate the process of bringing effective therapies into clinical practice.

Bioinformatics and systems biology approaches to identify potential common pathogeneses for sarcopenia and osteoarthritis

Sarcopenia, a geriatric syndrome characterized by progressive loss of muscle mass and strength, and osteoarthritis, a common degenerative joint disease, are both prevalent in elderly individuals. However, the relationship and molecular mechanisms underlying these two diseases have not been fully elucidated. In this study, we screened microarray data from the Gene Expression Omnibus to identify associations between sarcopenia and osteoarthritis. We employed multiple statistical methods and bioinformatics tools to analyze the shared DEGs (differentially expressed genes). Additionally, we identified 8 hub genes through functional enrichment analysis, protein-protein interaction analysis, transcription factor-gene interaction network analysis, and TF-miRNA coregulatory network analysis. We also discovered potential shared pathways between the two diseases, such as transcriptional misregulation in cancer, the FOXO signalling pathway, and endometrial cancer. Furthermore, based on common DEGs, we found that strophanthidin may be an optimal drug for treating sarcopenia and osteoarthritis, as indicated by the Drug Signatures database. Immune infiltration analysis was also performed on the sarcopenia and osteoarthritis datasets. Finally, receiver operating characteristic (ROC) curves were plotted to verify the reliability of our results. Our findings provide a theoretical foundation for future research on the potential common pathogenesis and molecular mechanisms of sarcopenia and osteoarthritis.

GSE1 promotes the proliferation and migration of lung adenocarcinoma cells by downregulating KLF6 expression

Lung cancer is one of the most prevalent human cancers with a high lethality rate worldwide. In this study, we demonstrated that GSE1 (genetic suppressor element 1) expression is aberrantly upregulated in lung adenocarcinoma and that GSE1 depletion inhibits the proliferation and migration of both A549 and H1299 cells. Immunoprecipitation assays demonstrated that GSE1 interacts with histone deacetylase 1 (HDAC1) and other BRAF-HDAC complex (BHC) components in cells. The transcriptome of GSE1-knockdown A549 cells indicated that 207 genes were upregulated and 159 were downregulated based on a p-value < .05 and fold change ≥ 1.5. Bioinformatics analysis suggested that 140 differentially expressed genes harbor binding sites for HDAC1, including the tumor suppressor gene KLF6 (Kruppel-like factor 6). Indeed, quantitative reverse-transcription polymerase chain reaction and western blot analysis revealed that GSE1 could inhibit the transcription of KLF6 in lung cancer cells. In conclusion, GSE1 cooperates with HDAC1 to promote the proliferation and metastasis of non-small cell lung cancer cells through the downregulation of KLF6 expression.

Single-cell sequencing of the substantia nigra reveals microglial activation in a model of MPTP

Background

N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is a neurotoxin widely used to induce PD models, but the effect of MPTP on the cells and genes of PD has not been fully elucidated.

Methods

Single-nucleus RNA sequencing was performed in the Substantia Nigra (SN) of MPTP mice. UMAP analysis was used for the dimensionality reduction visualization of the SN in the MPTP mice. Known marker genes highly expressed genes in each cluster were used to annotate most clusters. Specific Differentially Expressed Genes (DEGs) and PD risk genes analysis were used to find MPTP-associated cells. GO, KEGG, PPI network, GSEA and CellChat analysis were used to reveal cell type-specific functional alterations and disruption of cell-cell communication networks. Subset reconstruction and pseudotime analysis were used to reveal the activation status of the cells, and to find the transcription factors with trajectory characterized.

Results

Initially, we observed specific DEGs and PD risk genes enrichment in microglia. Next, We obtained the functional phenotype changes in microglia and found that IGF, AGRN and PTN pathways were reduced in MPTP mice. Finally, we analyzed the activation state of microglia and revealed a pro-inflammatory trajectory characterized by transcription factors Nfe2l2 and Runx1.

Conclusion

Our work revealed alterations in microglia function, signaling pathways and key genes in the SN of MPTP mice.

Comprehensive pan-cancer analysis reveals the versatile role of GALNT7 in epigenetic alterations and immune modulation in cancer

Cancer is a leading cause of mortality globally, characterized by intricate molecular alterations, including epigenetic changes such as glycosylation. This study presents a comprehensive pan-cancer analysis of Polypeptide N-Acetylgalactosaminyltransferase 7 (GALNT7), an enzyme involved in mucin-type O-linked protein glycosylation. GALNT7 has previously been linked to various cancers, but a unified analysis across cancer types is lacking. Leveraging data from TCGA, GTEx, and other sources, we scrutinized GALNT7's expression, prognostic relevance, links to immune-related genes, immune cell infiltration, and its involvement in tumor genetic heterogeneity across 33 cancer types. GALNT7 exhibited diverse expression patterns across cancer types, showcasing its potential as an oncogenic factor, with its expression levels linked to both positive and negative prognoses, highlighting the context-specific nature of its role in cancer progression. We delved into the intricate interplay between GALNT7 and immune genes, unveiling positive and negative correlations, underscoring complex interactions in the tumor microenvironment. GALNT7 was found to impact immune cell infiltration, which could have implications for treatment strategies. Additionally, GALNT7 displayed associations with genetic tumor aspects, encompassing genomic instability, DNA repair issues, and genetic mutations, hinting at its pivotal role in shaping the genetic landscape of diverse cancers. Enrichment analysis uncovered potential functions of GALNT7 beyond glycosylation, such as its participation in signaling pathways and its association with various diseases, notably cancer. This comprehensive analysis elucidates the multifaceted role of GALNT7 in cancer biology, underlining its potential as a therapeutic target and biomarker across various cancer types. These findings provide valuable insights for future research and the development of personalized cancer treatment strategies.

Stachydrine hydrochloride protects the ischemic heart by ameliorating endoplasmic reticulum stress through a SERCA2a dependent way and maintaining intracellular Ca2+ homeostasis

This study aimed to explore the effects and mechanism of action of stachydrine hydrochloride (Sta) against myocardial infarction (MI) through sarcoplasmic/endoplasmic reticulum stress-related injury. The targets of Sta against MI were screened using network pharmacology. C57BL/6 J mice after MI were treated with saline, Sta (6 or 12 mg kg-1) for 2 weeks, and adult mouse and neonatal rat cardiomyocytes (AMCMs and NRCMs) were incubated with Sta (10-4-10-6 M) under normoxia or hypoxia for 2 or 12 h, respectively. Echocardiography, Evans blue, and 2,3,5-triphenyltetrazolium chloride (TTC) staining were used for morphological and functional analyses. Endoplasmic reticulum stress (ERS), unfolded protein reaction (UPR), apoptosis signals, cardiomyocyte contraction, and Ca2+ flux were detected using transmission electron microscopy (TEM), western blotting, immunofluorescence, and sarcomere and Fluo-4 tracing. The ingredient-disease-pathway-target network revealed targets of Sta against MI were related to apoptosis, Ca2+ homeostasis and ERS. Both dosages of Sta improved heart function, decreased infarction size, and potentially increased the survival rate. Sta directly alleviated ERS and UPR and elicited less apoptosis in the border myocardium and hypoxic NRCMs. Furthermore, Sta upregulated sarcoplasmic reticulum Ca2+-ATPase 2a (SERCA2a) in both ischaemic hearts and hypoxic NRCMs, accompanied by restored sarcomere shortening, resting intracellular Ca2+, and Ca2+ reuptake time constants (Tau) in Sta-treated hypoxic ARCMs. However, 2,5-di-t-butyl-1,4-benzohydroquinone (BHQ) (25 μM), a specific SERCA inhibitor, totally abolished the beneficial effect of Sta in hypoxic cardiomyocytes. Sta protects the heart from MI by upregulating SERCA2a to maintain intracellular Ca2+ homeostasis, thus alleviating ERS-induced apoptosis.