This may pave the way for understanding life-threatening disorders such as cancer.Glaucoma is the second leading cause of irreversible blindness, and primary open-angle glaucoma (POAG) is the most common type. Due to inadequate diagnosis, treatment is often not administered until symptoms occur. Hence, approaches enabling earlier prediction or diagnosis of POAG are necessary. We aimed to identify novel drugs for glaucoma through bioinformatics and network analysis. Data from 36 samples, obtained from the trabecular meshwork of healthy individuals and patients with POAG, were acquired from a dataset. Next, differentially expressed genes (DEGs) were identified to construct a protein-protein interaction (PPI) network. In both stages, the genes were enriched by studying the critical biological processes and pathways related to POAG. Finally, a drug-gene network was constructed, and novel drugs for POAG treatment were proposed. Genes with p < 0.01 and |log fold change| > 0.3  were considered DEGs and utilized to construct a PPI network. Enrichment analysis yielded several key pathways that were upregulated or downregulated. For example, extracellular matrix organization, the immune system, neutrophil degranulation, and cytokine signaling were upregulated among immune pathways, while signal transduction, the immune system, extracellular matrix organization, and receptor tyrosine kinase signaling were downregulated. Finally, novel drugs including metformin hydrochloride, ixazomib citrate, and cisplatin warrant further analysis of their potential roles in POAG treatment. The candidate drugs identified in this computational analysis require  Glaucoma is the second leading cause of irreversible blindness worldwide -3. It isMajor risk factors for POAG include elevated IOP, older age, African ethnic origin, family history of glaucoma, and myopia. Less pivotal risk factors in the progression of glaucoma include cardiovascular risk factors such as dyslipidemia, hypertension, diabetes mellitus, and high body mass index or obesity . Since nProtein-protein interaction (PPI) network analysis is performed to extract the essential sub-modules from the PPI network. Integrated computational analysis has been used to introduce novel potential drugs for the treatment of age-related macular degeneration . Howeverhttps://www.ncbi.nlm.nih.gov/geo/). The samples, all obtained from trabecular meshwork tissue, included 17 from patients with POAG and 19 control samples  [https://string-db.org/) [Expression data with the accession number GSE27276 were downloaded from the National Center for Biotechnology Information Gene Expression Omnibus  . The chis total) . Before s total) . Benjamidb.org/) .https://david.ncifcrf.gov/), respectively [Additionally, a bioinformatics tool was utilized for functional enrichment and pathway analysis of DEGs obtained by gene ontology and Reactome pathways in the DAVID database  was used to construct the PPI network from DEGs with p < 0.01 and |log fold change| > 0.3. To visualize the data, Cytoscape version 3.8.2  was utilized. ClusterVis  was used to perform cluster analysis. Different algorithms exist for cluster analysis using ClusterVis. We selected the fast agglomerate edge clustering algorithm in this study. In this algorithm, a coefficient is calculated for each edge in the networks; then, based on the clustering coefficients, the edges are sorted in a decreasing way. Next, protein complexes are identified according to the bottom-up condensation of the hierarchical clustering algorithm. Used to analyze large protein networks, the fast agglomerate edge clustering algorithm is beneficial because of its fast computational power and low complexity . The parThen, further enrichment analysis was conducted for the top three modules for gene ontology and Reactome pathways (both performed with DAVID v.6.8).https://www.dgidb.org/) was utilized to identify potential candidate drugs [After selection of the significant subnetworks, the drug-gene network was constructed. The Drug Gene Interaction Database (DGIdb)  by comparing gene expression levels in POAG samples with controls .The significant pathways and functional enrichment information were extracted from the DAVID database. On the DEG list, the pathways of upregulated genes with p < 0.01 were selected as significant. The most significant pathways or systems were extracellular matrix (ECM) organization, the immune system, integrin cell surface interactions, diseases of metabolism, regulation of insulin-like growth factor transport and uptake by insulin-like growth factor binding proteins, post-translational protein phosphorylation, the adaptive immune system, and signaling by platelet-derived growth factor (PDGF); many other pathways showed significant results as well . The resA similar approach was utilized to study the significantly downregulated pathways, which included signal transduction, the immune system, ECM organization, cell junction organization, TP53 regulation of transcription of additional cell death genes with uncertain roles in p53-dependent apoptosis, toll-like receptor cascades, and many other pathways . The resThe PPI network of 1,350 genes was derived from the STRING database . ClusterThe DAVID database was used to perform an enrichment analysis of the genes in each module separately. Based on the Reactome pathway database, the most significant pathways of module 1 (p < 0.01) were post-translational protein modification, nucleotide excision repair, and PTEN regulation . For modThe results of the gene ontology enrichment analysis of each module, including significant (p < 0.01) biological processes, molecular functions, and cell components, are indicated in The DGIdb was used to identify drugs targeting the genes of the modules. The selected modules’ genes were merged; then, these genes were then imported into the DGIdb, and approved drugs targeting these genes were extracted. After detecting drug-gene interactions for the genes of all modules, the obtained interactions were utilized to construct a drug-gene network. Based on drug-gene interactions, six drugs were detected. However, we found no drug targeting multiple genes in the PPI modules. Finally, Cytoscape (version 3.6) was used to visualize the drug-gene network , and theThis study was performed to detect more effective drugs for POAG treatment, as well as to better understand POAG pathogenesis. Accordingly, DEGs were obtained between POAG and control samples. A total of 1,350 genes with p < 0.01 and |log fold change| > 0.3 were categorized as DEGs. Biological pathway analysis indicated that the upregulated DEGs were enriched in ECM organization, the immune system, neutrophil degranulation, ECM degradation, the innate immune system, PDGF signaling, and many other processes . The rolPDGF family in ocular disorders involving degeneration of neuronal and vascular retinal cells. This supports the importance of model study and analysis of this gene family and targeting-related cascade in the effort to cure neurodegenerative ocular disorders [Environmental factors and genetics have also been reported to contribute to the enhanced risk of glaucoma. Evidence now indicates that epigenetics may also play a critical role, offering potential novel therapeutic targets. Furthermore, several pathways are involved in the progression of this disease, such as Rho kinase, transforming growth factor-β, JNK, mitogen-activated protein kinase, PTEN, Bcl-2, brain-derived neurotrophic factor, calcium-calpain signaling, and phosphoinositide 3-kinase/Akt caspase. These pathways result in the upregulation of proapoptotic gene expression, the downregulation of neuroprotective and survival factors, and the generation of fibrosis at the trabecular meshwork, which may block the aqueous humor drainage system. Novel therapeutic agents targeting each component of these pathways have shown initial success in animal models and even human trials, indicating potential for preserving retinal neurons and vision . Additioisorders .Downregulated DEGs were mainly involved in biological pathways including signal transduction, ECM organization, the p53 apoptotic cascade, and toll-like receptor cascades. Importantly, pathways related to various forms of signal transduction, ECM organization, and the immune system were noted among both upregulated and downregulated DEGs. However, for p53, understanding the apoptosis pathway and key genes involved in this process is crucial. For example, p53 may control the expression level of proapoptotic and antiapoptotic genes, with diseases caused by its downregulation of apoptotic processes .However, the results could differ completely based on geographical context. For instance, a cohort study in Iran revealed that a polymorphism of p53 (Arg72Pro) was correlated with POAG, while another study of Japanese patients demonstrated no relation between p53 polymorphisms and the disease; thus, these studies have drawn inconsistent conclusions ,24.Toll-like receptor 4 is an active component of the innate immune system that was repeatedly mentioned in the pathway enrichment analysis. Similarly, it is involved in cell death, and its downregulation could impact the cell survival of retinal ganglion cells through decreasing TGF-β2–induced fibrosis . Based oPSMC1 gene); and carboplatin and cisplatin (which target the EIF3A gene) for potential repurposing. Clinical and laboratory studies should be conducted to confirm their effectiveness in POAG treatment.We constructed a PPI network based on DEGs between patients with POAG and control samples, with both sets of samples taken from the trabecular meshwork. Further investigations were based on three modules of proteins that were most correlated with POAG. Generally, the main goal of this study was to discover novel therapeutic candidate drugs for gene regulation in POAG cases. Hence, we constructed a gene-drug network, and we identified several drugs, including metformin hydrochloride (which targets multiple genes); bortezomib, ixazomib citrate, and carfilzomib  is an adaptive proteolytic system that controls numerous cellular processes, including protein degradation, DNA repair, stress responses, and cell proliferation . DysfuncMoreover, other drugs with proteasome-inhibiting activities have been investigated for the treatment of hematological malignancies and solid tumors . NotablyAlthough no information is available about the impact of cisplatin in POAG, one study assessed the role of this drug to obtain the relationship between the impact of this drug and specific methylation patterns of individuals. This research indicated that specific mitochondrial DNA patterns are associated with different responses to cisplatin treatment .Lastly, little data are available from the phase I/II clinical trial study of subconjunctival carboplatin injection on retinoblastoma and eye-related disorders. Although they described carboplatin as encouraging, those authors still recommended enucleation when the patient lacks functional vision, such as in cases of large tumors, long-standing retinal detachment, and neovascular glaucoma . In suchOverall, since most of the drugs obtained in this study are related to cancer in general or eye-related cancers in particular, their administration in glaucoma has been insufficiently investigated. Therefore, in accordance with our study’s aims, we propose that drugs including metformin hydrochloride, ixazomib citrate, and cisplatin are novel and warrant further clinical and laboratory investigations of their potential in treating glaucoma.in vitro and in vivo validation of each drug's safety and usefulness. In that case, the drugs proposed in this study could pave the way to understanding life-threatening disorders such as cancer and eye disease.Here, we aimed to compare the trabecular meshwork tissue of healthy patients with that of patients with POAG. We identified 1,350 DEGs, then constructed a PPI network based on significant DEGs (p < 0.01 and |log fold change| > 0.3). Lastly, we reconstructed a drug-gene network for the genes of the PPI modules. However, our study consisted of computational analysis and lacked experimental methods to confirm the findings. In particular, the candidate drugs obtained in this study require


Artemisia argyi H. Lév. and Vaniot is a variety of Chinese mugwort widely cultured in central China. A. verlotorum Lamotte, another variety of Chinese mugwort, has been used in the southern region of China since ancient times. Despite their similar uses in traditional medicine, little is known about the differences in their active ingredients and potential benefits. Herein, the chemical compositions of the essential oils (EOs) from both varieties were analyzed using chromatography-mass spectrometry (GC-MS). A series of databases, such as the Traditional Chinese Medicine Systems Pharmacology database (TCMSP), SuperPred database and R tool, were applied to build a networking of the EOs. Our results revealed significant differences in the chemical compositions of the two Artemisia EOs. However, we found that they shared similar ingredient–target–pathway networking with diverse bioactivities, such as neuroprotective, anti-cancer and anti-inflammatory. Furthermore, our protein connection networking analysis showed that transcription factor p65 (RELA), phosphatidylinositol 3-kinase regulatory subunit alpha (PIK3R1) and mitogen-activated protein kinase 1 (MAPK1) are crucial for the biological activity of Artemisia EOs. Our findings provided evidence for the use of A. verlotorum as Chinese mugwort in southern China. Artemisia spps. are grown in Asia, North America and Europe [Artemisia EOs have pleiotropic bioactivity [d Europe . They ard Europe . Due to activity  and haveA. argyi, has a long history of use in China for controlling dysmenorrhea, bleeding and eczema [A. argyi (AAEOs) are one of the major active ingredients [A. verlotorum, a perennial plant widely distributed in the northern hemisphere [A. argyi, and is also widely used to make Chinese mugwort in southern China, especially in Guangdong province [A. verlotorum (AVEOs) are still unclear.Chinese mugwort, made from the leaves of d eczema ,5. The eredients . AAEOs hredients ,8, anti-redients , anti-miredients , anti-furedients , anti-hiredients , analgesredients , anti-turedients . It is nmisphere , has simprovince ,17. HoweA. argyi and A. verlotorum using gas chromatography-mass spectrometry (GC-MS) as the basis for potential activity exploration. We applied a networking pharmacology approach to study the interrelationships between the compounds, targets and related pathways for the EOs extracted from the leaves of A. argyi and A. verlotorum. The study involved a complex networking approach to investigate the interrelationships between the ingredients, target proteins and related signaling pathways of the EOs from both Artemisia. We further studied the statistical characteristics of the networking to explore the main active compounds and potential activities of the Artemisia EOs. Our results indicated that the ingredients of the EOs from the two Artemisia were different. The contents of monoterpenoids and sesquiterpenes could be used as markers to distinguish AAEOs from AVEOs. However, the networking pharmacology analysis suggested that the AAEOs and AVEOs have similar potential targets and pathways, indicating that they have similar biological activities. Our results provided evidence for the use of A. verlotorum as Chinese mugwort in southern China.Herein, we analyzed the chemical ingredients of the EOs from different parts of A. argyi and A. verlotorum have been used as Ay Tsao or Chinese mugwort in China [A. argyi is known as northern Ay Tsao or northern Chinese mugwort, whereas A. verlotorum is called southern Chinese mugwort and is widely used by local people in southern China. Although many studies have reported the chemical constituents of A. argyi, few have reported on the chemical compositions of A. verlotorum. EOs are one of the major active ingredients of aromatic plants [A. argyi , the leaves of A. argyi , the whole grass of A. verlotorum  and the leaves of A. verlotorum  using GC-MS , 37 monoterpenoids  and three diterpenoids. Additionally, these EOs also contained five aromatics and 16 aliphatics. Among them, caryophyllene, caryophyllene oxide, neointermedeol and seven other ingredients were common components in the Artemisia essential oils. Diverse sesquiterpenoids accounted for the highest percentage of all Artemisia oils. The total contents of the sesquiterpeoids in the GAAEOs (38.42%), LAAEOs (52.01%), GAVEOs (63.56%) and LAVEOs (77.72%) were greater than 35%.A total of 132 volatile compounds of the ompounds . The ArtThe chemical compositions of the Vs were more abundant than the AVEOs and differed significantly. Among them, neointermedeol and eucalyptol were the main ingredients of the AAEOs , while cA. argyi used in this study was collected in Henan province, China. For the EOs of the whole grass of A. argyi , 65 volatile compounds were identified. Among them, 22 monoterpenoids (38.71%), 27 sesquiterpenoids (38.42%), one diterpenoids (0.11%), four aromatics (2.03%) and 11 aliphatics (3.11%) were detected. Neointermedeol (9.69%) was the major compound, followed by caryophyllene (8.73%), caryophyllene oxide (5.93%), cis-chrysanthenol (5.92%) and eucalyptol (5.77%) (The  (5.77%) . It is nrpenoids 8.71%, 27A. argyi  (α-terpinenol (5.68%) and (+)-2-bornanone (5.14%) were the major monoterpenes. Sesquiterpenoids accounted for a higher proportion and contain more abundant structural skeletons, of which caryophyllene (9.24%), neointermedeol (8.02%) and caryophyllene oxide (3.42%) were the principal components. Moreover, a few aromatic compounds, such as eugenol (0.84%), were observed, as well as aliphatics, such as 1-octen-3-ol (0.34%). The chemical composition of the LAAEOs was relatively consistent with previous reports [α-terpinenol and humulene [A. argyi samples [A. argyi.For the leaves of s, YP-2) , we iden reports ,18,23. Oyllene 9.%, neointhumulene . Additiohumulene . Howeverhumulene . However samples . Many imA. argyi were more chemically diverse than the leaves. The main chemical substances of the EOs from the two parts of A. argyi were similar, while the contents had some differences. There were 42 identical components, including neointermedeol, caryophyllene, caryophyllene oxide, etc.,  (β-eudesmol (6.67%), neointermedeol (4.72%), α-gurjunene (3.82%) and isospathulenol (3.77%) were the major sesquiterpenoids. Similarly to the LAVEOs, the GAVEOs had a higher content and diverse structure of sesquiterpenes compared to monoterpenes. It is clear that the yield and constitutes of Artemisia oils may be influenced by the cultivation location, harvest time, vegetative cycle stage, extraction method and selection of plant parts, based on preliminary studies [Artemisia from the gene perspective suggested that there was a significant difference in the expression pattern of genes [The s, YP-3) , we dete studies ,28. A coof genes .A. verlotorum  (δ-cadinene (3.55%). The sesquiterpenoids with significant structural diversity had a higher proportion (>65%) than those of monoterpenoids (<5%). The chemical compositions of the LAVEOs were completely different from those in previous reports. For example, germacrene D (23.6%) was the major component of AVEOs steam from Mauritius [α-thujone (47.0%), β-thujone (10.0%), eucalyptol (21.0%) and caryophyllene (3.4%) were identified from LAVEOs harvested in France [α-thujone (47.0%) and β-thujone were not detected in our EOs. Interestingly, the content of caryophyllene (3.8%) in our study was consistent with the report in this study [For the leaves of s, YP-4) , we deteauritius , which wn France . Howeveris study . A. verlotorum. Thirty common constituents were identified in the LAVEOs and GAVEOs, such as himbaccol, (+)-β-eudesmol, isospathulenol, etc.  was the main substance in the EOs from different parts of ol, etc. .Artemisia EOs and created an “ingredient–target-pathway” map with a merge function. The networking was visualized using Cytoscape 3.9.1 software  and 9-(1-methylethylidene)-1,5-cycloundecadiene (the highest-scoring compound in LAVEOs).Methyleugenol, the highest scoring compound in the GAAEOs, was a phenylpropanoid used as a flavoring agent, a fragrance and an anesthetic in rodents ,33. HoweThe caryophyllene oxide and neointermedeol were the common components of these four Eos, as shown in Artemisia essential oils with similar biological activity.Compounds show bioactivities by binding with particular proteins. . Table 3Artemisia in therapy. RELA  is a pleiotropic transcription factor in practically all cell types. It is the endpoint of a series of signal transduction events that are sparked by various stimuli related to numerous biological processes, including tumorigenesis, differentiation, cell growth and apoptosis [A protein association network was constructed using STRING databases to screen the key target proteins with high interactions . The nodpoptosis ,44,45,46poptosis ,48. Thespoptosis ,49, neurpoptosis , hypoglypoptosis , as wellpoptosis ,53 and opoptosis ,54.Additionally, the study found that the two MAPKs that are crucial to the MAPK/ERK cascade are MAPK1/ERK2 and MAPK3/ERK1. The regulation of transcription, translation and cytoskeletal rearrangements by the MAPK/ERK cascade regulates a variety of biological tasks, including cell growth, adhesion, survival and differentiation, depending on the cellular context ,56. Our The biological processes, cellular components and molecular functions were the three major functional categories identified from the GO term enrichment analysis of the EOs. The top ten GO terms of each category are illustrated in To identify the pathways and targets that were involved directly, the pathway information related to the targets was obtained through KEGG analysis. Artemisia essential oils  and its targets and pathways  assay in combination with an in vivo zebrafish assay. In this regard, Artemisia essential oils are highly safe.As a processing of Chinese materia medica widely used in clinic, the toxicological evaluation of the for 24 h A,B. Furtebrafish C. This sArtemisia species have complicated locations and origins [A. argyi have been investigated, the mechanism by which these components act on human health at the cell level has remained largely unknown. Few studies have focused on the biological activity of the essential oils of A. verlotorum. Aromatic chemical components from folkloric medicinal plants, such as EOs, have been claimed to be useful in treating or preventing a variety of illnesses . The fra origins . AlthougA. argyi and A. verlotorum were quite different. However, networking pharmacology and R cluster analysis studies showed that they share similar key target proteins, as well as highly consistent protein interactions and signaling pathways. This indicated that these two Artemisia essential oils could be substituted for each other in aromatic therapy. Our study provides evidence to better understand the development and application of A. argyi and A. verlotorum in Chinese traditional medicine and lays a foundation for the clinical safety and scientific medication of Artemisia essential oils.Herein, we analyzed the compositional differences and potential bioactivities of EOs from two Chinese mugworts. The results showed that the chemical composition of the EOs from A. argyi H. Lév. and Vaniot and A. verlotorum Lamotte were derived from different species of the same genus and have extremely similar morphological characteristics. These samples were (n = 3) collected from Nanyang, Henan Province, and Luofo mountain, Guangdong Province  [The n sites) ,63, PeopA. argyi (YP-1 and YP-2) and A. verlotorum (YP-3 and YP-4). The dried Artemisia (100 g), in a round bottom flask, was added to distilled water (1 L). The extractions of Eos, in detail, followed previous studies [Steam distillation was used to extract the EOs from different parts of the whole grass and leaves of  studies . DetaileGC-MS was used to analyze the compounds of AAEOs and AVEOs. The methods, in detail, followed previous studies .http://tcmspw.com/tcmsp.php, 18 February 2022) [https://pubchem.ncbi.nlm.nih.gov/, 18 February 2022) were used to assess these crucial pharmaceutical features.The discovered chemicals in the EOs were screened for drug-like characteristics using Lipinski’s five rules . The Trary 2022)  and PubChttps://prediction.charite.de, 20 February 2022), SwissTargetPrediction  and TargetNet . The ingredients’ absent target proteins were eliminated. In addition, the information on all the collected proteins was made uniform using Uniprot  [Potential targets of the compounds in the AAEOs and AVEOs were collected via networking databases (probability > 0.7), including SuperPred (ch 2022) . http://www.kegg.jp/kegg/, 4 March 2022) and the Database for Annotation, Visualization and Integrated Discovery (DAVID) , the analysis of pathways was carried out on the chosen targets. The database is an encyclopedia of genes and genomes and includes information on signal transduction, cellular biology and homologous conservative route [Using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database . In this study, we eliminated the isolated targets and constructed a PPI networking by screening them with a confidence score > 0.90.Based on the top targets in the R processing results, protein–protein interaction networking analysis (PPI) was also carried out to assess the targets. The association between the targets was evaluated as follows. PPI: To show how the target proteins interact, the target proteins were uploaded to the STRING databases platform  enrichment analysis was performed on the candidate targets using the online tool DAVID and KEGG, as well as KEGG pathway annotation. Artemisia essential oils on HEK-293T cells  was detected using the MTT method, consistent with the previous study [Artemisia essential oils  for 24 h. The cells incubated with 3 µM paclitaxel (PTX)  was used as the positive control .Cytotoxicity assay: The toxicity of us study . Cells wArtemisia essential oils (10 μg/mL) in the sterile 12 well plate. Each group was provided with 20 embryos . The development and morphological changes of the embryos after drug exposure were observed, photographed and recorded using an inverted optical microscope at 18 and 36 hpf, and recorded the hatching rate of the embryos at 36 hpf.Zebrafish toxicity assay: Healthy 24 h post-fertilization (hpf) embryos (transparent fertilized eggs) were randomly transferred to different concentrations of methanol extract of p values < 0.05 were considered statistically significant.All the data were statistically analyzed using the GraphPad Prism 9 software, using a two-tailed Student’s t-test.


Clinacanthus nutans (for abbreviation thereafter) is often used as medicine in the form of fresh juice in the folk to treat many kinds of cancers, including renal cell carcinoma (RCC). It is speculated that its active ingredient may have heat sensitivity, but there are currently no reports on this aspect. Therefore, based on the folk application for fresh juice of C nutans, this study used metabonomics and network pharmacology to explore the material basis and mechanism of action of C nutans against RCC.C nutans. Secondly, we collected the targets of metabolites in the Swiss Target Prediction platform. In addition, the targets of RCC were obtained in the GeneCards database. The “component-target-disease” network was established by Cytoscape3.9.0 software. Then we constructed a protein-protein interaction network in the STRING network platform to screen core targets. The gene ontology and kyoto encyclopedia of genes and genomes enrichment analysis of core targets were carried out to predict the relevant pathway of C nutans in the treatment of RCC. Finally, the molecular docking verification of the core targets were carried out.Firstly, untargeted metabolomics profiling was performed by Liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry to screen the metabolites down-regulated by heat in the extract of In this study, 35 potential active ingredients and 125 potential targets were obtained. And the core targets were Cellular tumor antigen p53, Signal transducer and activator of transcription 3, and so on. Then, 48 biological processes, 30 cell components, and 36 molecular functions were obtained by gene ontology enrichment analysis. Besides, 44 pathways were obtained by Kyoto encyclopedia of genes and genomes enrichment analysis, including Pathway in cancer, PI3K-Akt signal pathway, P53 signal pathway, and so on. The docking model between the core target and its corresponding components was stable.C nutans, showed its potential active ingredients by metabonomics, and predicted the potential mechanism of C nutans in the treatment of RCC by network pharmacology. It provides new references for follow-up research and new drug development.This research is based on the folk application of  Clinacanthus nutans, is a herbaceous plant of the Acanthaceae family, and its leaves are mostly used as medicine. It has a good reputation for cancer treatment among Southeast Asian people and is even called “sambung nyawa” by the Indonesian people, which means life-saving grass. Thailand has listed it as a basic healthcare medicinal plant. In addition, the acute toxicity study of different polar solvent extracts of C nutans including ethanol, methanol, and water showed that C nutans was safe.–6 All kinds of signs show that the herb has the potential to be developed into an anticancer drug. Modern research shows that it has many biological activities such as antitumor, anti-inflammatory, antioxidant, and so on. Most folk people take it orally as medicine in the form of fresh juice, which is used to treat liver cancer, nephritis, kidney cancer, and other diseases. However, the antitumor active ingredients and mechanism of C nutans have not been clearly reported. The onset of RCC is hidden, and it is often in the late stage of cancer when relevant symptoms occur. According to the SEER database of NIH in the United States, with the continuous progress of modern medical technology, although the 5-year survival rate of renal cell carcinoma has been improved, the prognosis of patients with advanced renal cell carcinoma is still not optimistic, and the 5-year survival rate of patients with metastatic renal cell carcinoma is only 12%. The comprehensive treatment based on drug treatment is very important for the improvement of its prognosis. Therefore, the development of new drugs for RCC is very urgent.Renal cell carcinoma (RCC) is a common malignant tumor in the urinary system, which is characterized by strong invasion and high risk of metastasis. In recent years, the incidence rate of RCC has continued to rise in most countries and regions. Many unique folk herbs have achieved good results in treating various diseases. However, as the result of the lack of clinical and scientific research, it is difficult to carry out effective development and application without the support of scientific data.Due to the huge advantages of multi-component drugs in the treatment of chronic and complex diseases such as cancer through synergistic effects, traditional Chinese medicine has gradually become a research hotspot.–17 Besides, nature medicine act synergistically through multiple components, therefore the mechanisms involved are very complex. Network pharmacology can explore the overall relationship between active ingredients of nature medicine and diseases by establishing a network that connects components and diseases with targets as transition points.–20Metabolomics is widely used in the study of natural medicine due to its wide coverage and high accuracy, which enables efficient qualitative and quantitative analysis of components.Clinacanthus nutans by Professor Chen Jiannan of Guangzhou University of Traditional Chinese Medicine and its samples were stored in the New Chinese Medicine Development Laboratory of Guangzhou University of Traditional Chinese Medicine.The Clinacanthus nutans used in this project was introduced from Wuzhi Mountain in Hainan to Huolu Mountain Planting Base in Guangzhou. It was collected and identified as C nutans were freeze-dried and then superfine crushed. After 30 minutes of ultrasonic extraction with 10 times of dichloromethane, the filtrate is naturally volatilized in the fume hood for 12 hours, and then freeze-dried for 24 hours. Finally, extract was obtained, and it was named as freeze-dried sample, which was prepared 3 times and numbered F-1, F-2, F-3; Take a certain amount of extract and heat it at 105°C for 6 hours, and name it as heated sample. Repeat the preparation for 3 times, numbered H-1, H-2, H-3. The samples were stored at 4°C.The fresh leaves of Take a certain amount of the freeze-dried sample and the heated sample in the centrifuge tube and seal them for storage. Put the centrifuge tube into dry ice and send it to Chengqi Medical (Shenzhen) Technology Co., Ltd. for testing.Add precooled methanol-acetonitrile-water solution to the sample, ultrasonic for 30 minutes, 14,000 g centrifugation for 20 minutes, take the supernatant for vacuum drying, add acetonitrile water solution for redissolution, 14,000 g centrifugation for 15 minutes, take the supernatant for analysis.The sample injection volume is 2.0 μL. The column temperature is 40°C and the flow rate is 0.4 mL/minutes; Mobile phase A is 25 mM ammonium acetate −0.5% formic acid water; Mobile phase B is methanol. Mobile phase gradient downward: 0 to 0.5 minutes, 5%B; 0.5 to 10 minutes, 5% to 100%B; 10.0 to 12.0 minutes, 100%B; 12.0 to 12.1 minutes, 100% to 5%B; 12.1 to 16 minutes, 5%B; QC samples are inserted into the samples to monitor the stability of the system. AB Triple TOF 6600 mass spectrometer was used for sample data collection.The metabolite structure identification is carried out in the metabolome database of new life plants in the Chinese family. Finally, the data are processed and analyzed, including univariate statistical analysis, multidimensional statistical analysis, differential metabolite screening, etc.Take a certain amount of freeze-dried sample and heated sample samples and add dichloromethane to make the final concentration of 1.0 mg/mL, ultrasound for 30 minutes, and pass 0.45μm microporous membrane, filtrate analysis.The sample injection volume is 1.0 μL. The flow rate is 1.0 mL/minutes. The heating procedure is as follows: 0 to 2 minutes, 60°C; 2 to 10 minutes, 60°C to 180%°C; 10.0 to 15.0 minutes, 180%°C; 15.0 to 32.5 minutes, 250%°C. After running at 300°C for 5 minutes, conduct the next sample injection, and insert the QC sample into the sample. The mass spectrometer is used for full scan mode scanning of m/z 50 to 550, and the mass spectrum is collected at 70eV.https://cloud.metware.cn/), including univariate statistical analysis, multidimensional statistical analysis, differential metabolite screening, etc.Identify the name and molecular weight of the compound in the NIST library. Then conduct data analysis on the Metware Cloud platform (https://pubchem.ncbi.nlm.nih.gov/). The oral availability and drug-like properties were investigated on the Swiss ADME platform (http://www.swissadme.ch/). Collect ingredients that are “high” in gastrointestinal absorption and “yes” in Lipinski.Collect the down-regulated metabolites in the above metabolomics and get their SMILES formula in the PubChem database (http://www.swisstargetprediction.ch/), and take “probability > 0.1” as the screening criteria. Compare and determine the targets in the Uniprot database (https://www.uniprot.org/), and obtain the targets of the ingredients of C nutans at last.We predict the targets of the components that meet the conditions in the Swiss Target Prediction platform (https://www.genecards.org/). According to the correlation score, the top 5% of the targets are selected as the disease targets of RCC.Collect potential targets related to renal cell carcinoma by the keywords “Renal cell carcinoma”, “RCC”, and “Kidney cancer” in the Gene Cards database (http://www.bioinformatics.com.cn/) to obtain the intersection targets of C nutans and RCC, and import it into Cytoscape3.9.0 software (https://cytoscape.org/) for visualization processing to build a “component-target-disease” network.The Venn Diagram is established in the Bioinformatics platform (https://cn.string-db.org/), the species option is “Homesapiens,” the interaction score ≥ 0.4, the PPI network is established, and the target point of network interruption is deleted. After the core targets are obtained by screening with the median of Degree, Betweenness Centrality, and Closeness Centrality, the PPI network is reestablished under the same conditions, and the results are visualized.Introduce intersection genes into the STRING network platform (https://metascape.org/). The species option is “Homosapiens,” which is used for enrichment analysis of biological processes, cell components, and molecular functions. Import the analysis results into the Glue GO plug-in, and conduct cluster analysis under the conditions of P value ≤ .01, Kappa score = 0.12. The results are made into a bubble chart according to the size of P value.The core targets are imported into the Metascape platform  and obtain the 3D structure of the components from PubChem. Vina software is used for molecular docking to obtain the lowest binding energy. The docking results are visualized through Discovery Studio software.Collect the core targets in PPI and get its corresponding components. Collect the structure file of the targets in the PDB database  and STAT3 (PDB ID: 6TLC) with the highest degree value obtained in the network pharmacology research to establish the molecular docking model with their corresponding components. The binding activity of components and target proteins is expressed in the form of binding energy.ell Fig. . It showC nutans is the flavonoid components such as Schaftoside, vitexin, orientin, but this does not mean that some unusual components can be ignored. Although these flavonoids have been reported to have antitumor activity, they are widely found in many plants–33 and are not unique to C nutans. According to the use of fresh extract of C nutans as medicine, it is speculated that the active ingredients of C nutans against RCC may have the characteristics of easy decomposition or volatilization when heated. Combined with some studies, the dichloromethane part of C nutans is potential to have the best antitumor activity.At present, the mainstream of the research on  It has the advantages of wide coverage and high accuracy.,37 It mainly uses high-resolution mass spectrometry to identify and analyze the chemical components in traditional Chinese medicine. By comparing the differences between samples, important differences are screened out from huge data.,39 LC-MS and GC-MS are widely used because of their high sensitivity and good reproducibility. LC-MS is mainly used for metabolites with high boiling point and poor thermal stability, while GC-MS is mainly used for metabolites with low boiling point and low polarity. The metabonomics study using LC-MS and GC-MS simultaneously can effectively improve the integrity of identifying all differential metabolites.,41 Therefore, based on folk application, this study screened the metabolites related to drug efficacy in the dichloromethane extract of C nutans by metabonomics.,43Metabolomics is the qualitative and quantitative analysis of biological metabolites under certain conditions. However, due to the wide variety of components of traditional Chinese medicine, the complexity of the effect of traditional Chinese medicine is far higher than that of single drugs. Therefore, the method of network pharmacology is adopted to take into account the complex situation of multiple targets and synergistic effects of traditional Chinese medicine when it exerts its efficacy, so as to explore the mechanism of C nutans in treating RCC.,47Drugs exert their effects mainly in the form of regulating biological networks.C nutans in the treatment of RCC. Inhibiting the activation of PI3K/Akt/m TOR signal pathway can inhibit the progress of cell cycle, and also regulate the expression of Bax and Bcl-2, thus inducing the process of cell apoptosis.,50 It has been reported that the growth of renal cell carcinoma cells can also be inhibited by regulating the PI3K/mTOR/p53 signal pathway.According to the results of network pharmacology, PI3K-Akt signal pathway and p53 signal pathway may be the potential pathway of  However, in almost all renal cell carcinomas, p53 exists as wild-type, and its signal pathway will lose its anticancer function due to tissue or disease specificity. The abnormal condition of VHL, HIF, MDM2, MDM4, and other genes linked to the development of renal cell carcinoma is closely related to the disappearance of its anticancer function. Even in some renal cell carcinomas with p53 mutations, p53 also shows a cancer-promoting effect. Therefore, the role of p53 in renal cell carcinoma needs further study. STAT3 is critical for cancer progression by regulating tumor cell survival, proliferation, and angiogenesis. Besides, STAT3 instability and degradation can effectively inhibit the development of RCC.TP53 gene, also known as p53, is an important tumor suppressor gene, which can activate p21, Bax and other downstream target genes to interfere with cell cycle, apoptosis, etc., and then inhibit the development of cancer.C nutans, this study screened the heat-sensitive ingredients by untargeted metabolomics profiling. These ingredients were used for network pharmacology and molecular docking research. The research results showed that these components have a good effect on anti-RCC. Therefore, these ingredients are the potential active ingredients of C nutans in anti-RCC. It provides a certain research direction for C nutans against RCC, and further experiments will be carried out in the future.In summary, according to the folk application of Conceptualization: Zhandong Ye.Data curation: Dan Li.Formal analysis: Zhiqiang Fang, Dan Li, Xiaogang Lin.Funding acquisition: Song Huang.Investigation: Zhiqiang Fang, Song Huang.Methodology: Zhandong Ye.Software: Zhiqiang Fang.Validation: Song Huang.Visualization: Zhandong Ye.Writing – original draft: Zhandong Ye.Writing – review & editing: Song Huang.


Astragalus membranaceus, a traditional Chinese herb that is frequently utilized in therapeutic practice, is a component of many Traditional Chinese Medicine formulas that have been documented to have anti-glioma properties. Uncertainty persists regarding the molecular mechanism behind the therapeutic effects. Based on results from network pharmacology and molecular docking, we thoroughly identified the molecular pathways of Astragalus membranaceus’ anti-glioma activities in this study. According to the findings of the enrichment analysis, 14 active compounds and 343 targets were eliminated from the screening process. These targets were mainly found in the pathways in cancer, neuroactive ligand–receptor interaction, protein phosphorylation, inflammatory response, positive regulation of phosphorylation, and inflammatory mediator regulation of Transient Receptor Potential (TRP) channels. The results of molecular docking showed that the active substances isoflavanone and 1,7-Dihydroxy-3,9-dimethoxy pterocarpene have strong binding affinities for the respective targets ESR2 and PTGS2. In accordance with the findings of our investigation, Astragalus membranaceus active compounds exhibit a multicomponent and multitarget synergistic therapeutic impact on glioma by actively targeting several targets in various pathways. Additionally, we propose that 1,7-Dihydroxy-3,9-dimethoxy pterocarpene and isoflavanone may be the main active ingredients in the therapy of glioma.Glioma treatment in traditional Chinese medicine has a lengthy history.  The majority (50–60%) of intracranial tumors are gliomas, which are the most prevalent and aggressive primary malignant tumors of the central nervous system ,2. AdultMost malignancies spread throughout the body and eventually result in death. Gliomas, on the other hand, grow quickly, invade healthy tissues, and are capable of destroying whatever tissue they come into contact with. Gliomas are difficult to locate precisely due to their atypical shape. The two main forms of treatment for gliomas are radiation therapy and surgery, which are frequently combined with chemotherapy. The chemotherapeutic agents temozolomide, nimustine, and avastin are frequently used for treating gliomas . TraditiThe natural world has gained popularity in recent years. Traditional Chinese Medicine has drawn a lot of attention because of its comparatively long-lasting benefits and relative safety. In the field of glioma treatment, encouraging advancements have been made, and breakthroughs are anticipated . Unlike Astragalus membranaceus, like Shezhihuangqitang , Buyanghuanwutang , and Xuefuzhuyutang . Astragalus membranaceus is a traditional Chinese herbal medicine commonly used in clinical practice, which has the effect of correcting and replenishing qi. Astragalus membranaceus has been found to have a range of active compounds, as demonstrated by modern pharmaceutical research. These substances include Astragalus membranaceus flavonoids, astragtilbene saponins, and polysaccharides -2,3,4,7,8,9,11,12,14,15,16,17-dodecahydro-1H-cyclopenta[a]phenanthren-3-ol(MOL000033), 1,7-Dihydroxy-3,9-dimethoxy pterocarpene(MOL000442), (3R)-3-chroman-7-ol (MOL000438), formononetin (MOL000392), and Bifendate (MOL000387). This finding indicates that these compounds could be the potential drugs targeting the important glioma-related target PIK3CA.According to the results of PPI analysis of the 343 targets, the top ten targets, including SRC1, PIK3R11, HSP90AA11, PIK3CA1, PIK3CB1 PIK3CD1, AKT11. ESR11, MAPK11, and HSP90AB11, may be the key targets of the treatment for glioma. We conducted GO and KEGG enrichment analyses on the 343 chosen targets in order to have a more systematic understanding of the various effects of function ,43. Whilfunction ,44,45,46tabolism , which wtabolism . PIK3CA,Astragalus membranaceus, has no reported targets. In this research, we studied the molecular mechanism of (3R)-3-chroman-7-o through molecular docking, and found that this compound may target multiple glioma-related targets, such as SRC , PTGS2 , and PTK2 .(3R)-3-chroman-7-ol(MOL000438) ,50, whicAstragalus membranaceus can regulate multiple pathways simultaneously to affect glioma.Moreover, to further explore and understand the potential function and interaction of the screened targets, the enrichment analysis of MCODE clusters discovered that several MCODE clusters are related to protein phosphorylation, which has been discussed in several studies ,52,53,54Astragalus membranaceus in the treatment of glioma.Finally, molecular docking was performed to evaluate nine key target proteins  and 14 active compounds, including EIC, Mairin, Jaranol, Hederagenin, 2,14,15,16,17- dodecahydro-1H-cyclopenta[a]phenanthren-3-ol, 3,9-di-O-methylnissolin, isoflavanone, Bifendate, Formononetin, 7-O-methylisomucronulatol, -9,10-dimethoxy-6a,11a-dihydro-6H-benzofuranochromen-3-ol, linolenic acid, (3R)-3-chroman-7-ol, 1,7-Dihydroxy-3,9-dimethoxy pterocarpene, -10,13-dimethyl-17-[-5-propan-2-yloctan-2-yl]-2,3,4,7,8,9,11. Two complexes, the ESR2-isoflavanone complex and the PTGS2-1,7-Dihydroxy-3,9-dimethoxy pterocarpene complex, had the lowest binding affinities , suggesting that they could be the main active ingredients and targets of Astragalus membranaceus has been examined during the past few years for its therapeutic benefit in the treatment of gliomas, not enough has been done to explore its mechanism. This study is the first to systematically analyze the molecular mechanism of Astragalus membranaceus for the treatment of glioma, using the network pharmacology and molecular docking approach. Furthermore, there is still a pressing need for innovative glioma treatment approaches. In this work, we offer a number of viable targets for glioma treatment, which may aid in the creation of fresh therapeutic approaches. It is important to note that this study has certain limitations. Initially, the bioactive component of Astragalus membranaceus and targets associated with gliomas were retrieved from the databases; hence, the dependability and precision of the analysis and forecast rely on the quality of the data. Secondly, additional in vivo and in vitro research is required to validate the results.While https://tcmsp-e.com/tcmsp.php, accessed on 1 August 2023) is a systems pharmacology platform for Chinese herbal medicines, provides interactive data related to the relationships between drugs, targets, and diseases [Astragalus membranaceus and active compounds were screened under the conditions of drug-likeness (DL) ≥ 0.18, which is determined upon the fact that the average DL index in the Drugbank [Traditional Chinese Medicine Systems Pharmacology  and UniProt  databases [https://pubchem.ncbi.nlm.nih.gov/, accessed on 1 August 2023) [http://www.swisstargetprediction.ch/, accessed on 1 August 2023) [The related targets of the active compounds obtained in the above steps were collected in TCMSP database, and the target protein names were converted to the official gene symbols using Perl (atabases . Unmatchst 2023) , then west 2023) ,65 in orhttps://www.genecards.org/, accessed on 12 August 2023) [https://www.disgenet.org, accessed on 12 August 2023) [https://ngdc.cncb.ac.cn/brainbase/, accessed on 13 August 2023) [Targets related to glioma were retrieved by using the keyword “glioma” in the GeneCards database (st 2023) . All tarst 2023) . Additiost 2023) ,69, whicAstragalus membranaceus were imported into VENN DIAGRAMS  to acquire intersection targets.Glioma-related targets and potential targets of Astragalus membranaceus targets were imported into the STRING database  [Common targets of glioma-related targets and st 2023) , which ist 2023)  to constst 2023) .http://metascape.org, accessed on 31 August 2023) [The Metascape platform (st 2023)  was usedst 2023) .http://Metascape.org, accessed on 31 August 2023). The species was set to “Homo Sapiens”, the p-value was set to “<0.01”, the smallest count was set to “3”, and the enrichment factor was set to “>1.5”. The heatmap was plotted by https://www.bioinformatics.com.cn, accessed on 31 August 2023), an online platform for data analysis and visualization.In order to obtain a more systematic and comprehensive understanding of the mechanisms behind the targets, Gene Ontology (GO), which includes biological processes, cellular components, and molecular functions , as wellAstragalus membranaceus that satisfy screening criteria, and glioma-related core targets were utilized in this study to build the compound–target–pathway interaction network.A compound–target–pathway was constructed and examined using Cytoscape 3.6.1 to illustrate and clarify the intricate relationships between active compounds, pathways, and targets in order to better investigate the regulatory mechanism of the active compounds against glioma. The top 20 enriched KEGG pathways, active compounds in Astragalus membranaceus and the top 8 target proteins selected from PPI and and MCODE analysis results. The 3D structures of the target protein (PDB format) were downloaded from the PDB database  [Molecular docking was performed using the 14 compounds from er 2023) . PyMOL 2The AutoDock Vina ,78 CMD cMolecular dynamics simulations and binding free energy calculations were performed on the best docked coordinates of each complex using GROMACS (version 2023.1) .The results were carefully analyzed and visualized by PyMOL 2.5.5 , LigPlusAstragalus membranaceus in treating glioblastoma utilizing network pharmacology and molecular docking. We discovered two potent compounds, isoflavanone and 1,7-Dihydroxy-3,9-dimethoxy pterocarpene, that may effectively connect with the respective targets ESR2 and PTGS2, as well as four main targets, namely PIK3R1, PIK3CB, SRC, and PIK3CA. These findings provide a research foundation for further investigation of Astragalus membranaceus in anti-glioma.This study elaborated the multi-component, multi-target, and multi-pathway properties of the bioactive component of


Despite many efforts to treat atrial fibrillation (AF), the most common progressive and age-related cardiac tachyarrhythmia in the Western world, the efficacy is still suboptimal. A plausible reason for this is that current treatments are not directed at underlying molecular root causes that drive electrical conduction disorders and AF . Insights into AF-induced transcriptomic alterations may aid in a deeper understanding of electropathology. Specifically, RNA sequencing (RNA-seq) facilitates transcriptomic analyses and discovery of differences in gene expression profiles between patient groups. In the last decade, various RNA-seq studies have been conducted in atrial tissue samples of patients with AF versus controls in sinus rhythm. Identified differentially expressed molecular pathways so far include pathways related to mechanotransduction, ECM remodeling, ion channel signaling, and structural tissue organization through developmental and inflammatory signaling pathways. In this review, we provide an overview of the available human AF RNA-seq studies and highlight the molecular pathways identified. Additionally, a comparison is made between human RNA-seq findings with findings from experimental AF model systems and we discuss contrasting findings. Finally, we elaborate on new exciting RNA-seq approaches, including single-nucleotide variants, spatial transcriptomics and profiling of different populations of total RNA, small RNA and long non-coding RNA. At present, selection of an optimal strategy for effective management of atrial fibrillation (AF), the most common age-related cardiac arrhythmia, is challenging . The maiTo improve AF therapy and diagnostics, research is increasingly focused on dissection of the molecular and electrical root causes of AF. Evidence from experimental and clinical AF studies reveal a key role for so-called ‘electropathology’ as a driver of AF. Electropathology is defined as electrical conduction disorders, and consequently contractile dysfunction, that are caused by molecular changes in the atrial tissue that drive structural changes  and AF initiation and perpetuation . So far,Transcriptome analysis is a powerful tool for identifying molecular disease mechanisms. Extensive AF-related gene expression data have been collected through atrial tissue and peripheral blood microarray studies. Microarray studies on AF and the insights they provide have been comprehensively reviewed by Steenman . During RNA sequencing (RNA-seq) has become a valuable tool for transcriptome-wide analysis of differential gene expression ,7. RNA-sOver the past decade, several RNA-seq studies have been conducted in right and left atrial tissue samples of patients with AF, controls in sinus rhythm (SR) without reported history of AF and patients in SR who developed post-operative AF (PoAF) after open heart surgery. The AF classification does not indicate rhythm at time of surgery. Differences in gene expression are studied to elucidate molecular pathways that drive AF. Of all the 17 RNA-seq studies presented in n = 53), PeAF (n = 51), and SR patients (n = 91) [The study by Zeemering et al. sequenced the largest collection of atrial tissue samples from PAF (ents n = 1 [9]. A (n = 91) ,12. Ke e(n = 91) . PathwayVan den Berg et al. also performed a large sample size RNA-seq study to investigate structural remodeling processes in AF . LAA tisOther RNA-seq studies found a broad spectrum of AF-related pathways by comparing expression profiles between SR patients and PeAF patients. Enrichment of downregulated genes was found in pathways related to calcium signaling, MAPK signaling and Wnt signaling ,16,22,25Besides uncovering the expression profiles of protein-coding genes, RNA-seq has also unlocked unprecedented access to the non-coding part of the transcriptome . This isCircRNAs represent another class of non-coding RNAs of which the function is largely unknown . Due to Hsu and Sigurdsson studied the role of genetic variation on gene expression changes in AF ,25. Hsu In conclusion, based on the differentially expressed gene-related pathways, several molecular mechanisms that manifest in the atria at cellular and tissue level are associated with AF occurrence. Downregulated pathways recurring between studies are mostly signaling pathways that guide a cellular response to an extracellular signal, including MAPK signaling and Wnt signaling. Upregulated pathways include intracellular signaling pathways , cellular response to external stimuli (MAPK), and cardiac muscle contraction. The challenge remains to differentiate between factors in the onset and progression of AF with collateral effects of AF. Most AF-related pathways identified in RNA-seq studies are involved in tissue repair. In depth evaluation of differential gene expression in the PAF group and comparison with PeAF patients may help to separate cause and effect. Applying this AF progression stratification to (e)QTL studies or in cross-referencing transcriptomics results with GWAS studies may provide another opportunity to identify potentially causal mechanisms for AF onset and progression. Molecules in the Wnt signaling pathway are interesting candidates, as they are associated with AF through differential expression and genetic variation and they seem related to development of PoAF as well ,20,25. ERNA-seq approaches have also been used in experimental animal and cell model systems to gain insights in the molecular mechanisms of AF, as summarized in In general, the AF model systems can be assigned into three groups: human iPSC atrial CMs, rodent models and large animal models. The types of RNA-seq studies performed on these models are either a direct comparison between induced or simulated AF and controls, or studies on the effect of a treatment or a specific mutation. Differential gene expression studies in AF models in rats and rabbit suggest involvement of cell cycle-related processes, inflammatory signaling, phagosome and calcium signaling pathways ,62. CaniTreatment of mouse AF models with curcumin or colchicine, which are considered to protect against AF, affect gene expression in pathways associated with inflammatory regulation and fibrosis, and IL-17 signaling and renin secretion pathways, respectively ,60. The Specific AF-related gene variants were studied in rat and murine model systems and in one human iPSC atrial CM study ,56,57,61Overall, the general overlap in AF-related pathways resulting from RNA-seq studies from experimental AF model systems and AF patient groups is substantial and includes cardiac conduction, ECM remodeling, inflammation and cell–cell interaction. Inflammatory signaling and cellular response pathways are widely featured in experimental model studies of AF, whereas AF patient cohort studies seem to highlight more tissue level processes in ECM remodeling and regulatory signaling pathways. For example, the Wnt pathway is a common mechanism in patient studies, but does not surface in any of the experimental models. Both clinical and experimental studies use bulk RNA-seq or RNA sequencing of atrial CMs specifically. Cellular composition within the model systems is a critical consideration when translating findings to a human context. To illustrate, cardiomyocytes and fibroblasts are major cell types in adult human hearts, as either cell type represents between 20–30% of total cardiac cells, and immune cells only make up 10% of the total ,67. In cAs the experimental AF model groups involve artificially induced AF, their scope is limited to the translational response to atrial tachycardia and the resulting mechanisms for atrial remodeling. Notwithstanding, animal model AF research has inspired our current understanding of electropathology as a driver for AF, by introducing the concept of ‘AF begets AF’ ,69. EffeIn the interest of providing an overview of AF-associated pathways and the overlap in differentially expressed genes within patient AF studies and large animal studies, DEGs found between SR and PeAF groups in the studies of Zeemering et al. and Van den Berg et al. are compared to DEGs found in the studies of LeBlanc et al. and Alvarez Franco et al. ,10,64,65To provide an overview of common pathways associated with AF-associated genes, we mapped all differentially expressed genes to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Counts of DEGs mapped to specific pathways are displayed in Interestingly, we found a substantial overlap in the AF-related pathways in patient and large animal studies. Three major categories of pathways surfaced in our comparison: metabolic pathways, various signaling pathways, and disease-related pathways. Cancer, infection and disease-related pathways are included in KEGG as broader pathways, that commonly include the PI3K-Akt signaling pathway, as well as MAPK signaling, cytokine-cytokine receptor interaction, focal adhesion, and calcium signaling pathways.Despite the overlap in pathways identified in human and animal AF studies, the overlap in specific DEGs underlying these KEGG pathways was less prominent .The difference in number of DEGs found in the Zeemering and Van den Berg studies is striking, especially regarding Van den Berg et al. only included protein coding genes in their analysis ,10. DissTranscriptomics studies have underscored the complexity of AF, as it involves numerous molecular pathways , remodelAnother emerging technology that provides single-cell resolution is spatial transcriptomics. Spatial transcriptomics allows for the analysis of gene expression patterns in situ, by quantifying localized gene expression across tissue sections. This will leave the spatial context intact, which is otherwise destroyed by cell or nuclei isolation protocols. At this moment the resolution of spatial transcriptomics is substantially lower than single-cell RNA sequencing. Nevertheless, given the fast pace of technological developments, it is expected that single-cell spatial resolution in combination with genome scale gene expression will be available in the near future. It will be interesting to implement spatial transcriptomics to the atrial myocardium from patients suffering from AF. This will undoubtedly shed light on mechanisms of structural remodeling, inflammation and/or the epicardial contribution to AF.Despite the advantages of spatial transcriptomics and single-cell sequencing, there are also challenges related to these new technologies. Technical variability and low sequencing coverage due to limited amount of starting material, variability of cell size and low cDNA conversion efficiency inevitably result in higher technical noise. As such, these technologies are not suitable at the moment to interrogate lowly expressed transcripts, and accurately annotate alternative splicing and isoform diversity. It is expected that these hurdles will be overcome in the near future, and that sequencing data will be integrated with other omics technologies, such as proteomics, metabolomics, and epigenomics. This will inevitably provide a more comprehensive understanding of the biological systems in the diseased heart.Insights into AF-induced transcriptomic alterations in atrial tissue samples provide a deeper understanding of molecular mechanisms driving AF. RNA-seq facilitates transcriptomic analyses and discovery of differences in gene expression profiles between patient groups. Compared to controls, AF is associated with downregulation of mostly signaling pathways that guide a cellular response to an extracellular signal, including MAPK signaling and Wnt signaling, whereas upregulated pathways include intracellular signaling pathways , cellular response to external stimuli (MAPK), and cardiac muscle contraction. Structural and electrical remodeling mechanisms are also the focus of previous microarrays studies, but RNA-seq adds a layer of depth by including the analysis of ncRNAs as regulatory transcription elements . Experim


Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathway-level function and lack a streamlined analytical process. Here we present a comprehensive pathway-level survival analysis suite, DRPPM-PATH-SURVEIOR, which includes a Shiny user interface with extensive features for systematic exploration of pathways and covariates in a Cox proportional-hazard model. Moreover, our framework offers an integrative strategy for performing Hazard Ratio ranked Gene Set Enrichment Analysis (GSEA) and pathway clustering. As an example, we applied our tool in a combined cohort of melanoma patients treated with checkpoint inhibition (ICI) and identified several immune populations and biomarkers predictive of ICI efficacy. We also analyzed gene expression data of pediatric acute myeloid leukemia (AML) and performed an inverse association of drug targets with the patient’s clinical endpoint. Our analysis derived several drug targets in high-risk KMT2A-fusion-positive patients, which were then validated in AML cell lines in the Genomics of Drug Sensitivity database. Altogether, the tool offers a comprehensive suite for pathway-level survival analysis and a user interface for exploring drug targets, molecular features, and immune populations at different resolutions. Common pathway-level analysis tools, such as ENRICHR, GSEA 22, are abA one-stop tool for expression-based survival analyses.The ability to include multiple covariates inside the Cox-proportion hazard pathway model.The ability to summarize prioritized gene signatures into relevant clusters and pathway modules.The ability to perform hazard ratio ranked gene set enrichment analysisThese integrative summary scores represent a useful approach in highlighting signaling pathways and immune populations that correlate with the clinical outcome. But existing survival analysis tools either lack a user-friendly interface or has limited functionality for systematic screening of large pathway databases. They are often restricted in available patient cohort or limited to a small subset of pathways –27 and aSupplementary Result Section).Altogether, survival analysis is a critical branch of statistics for analyzing the time-to-event, and our tool facilitates a comprehensive survival analysis of pathway-level scores , survminer (v0.4.9), GSVA (v1.40.1) , and immTo evaluate the association between pathway and survival To evaluate the pathway association with survival after adjusting for patient meta information To evaluate the associated interaction between the pathway and patient meta information is defined by To facilitate the identification of top high-risk pathways and genes, we have developed a pipeline to systematically assess pathways associated with hazard by a Cox proportional hazard function. The user can provide or select individual genes and pathway databases to perform a systematic screening. Each expression feature is stratified based on a median cutoff. The user also has the option of performing a systematic screening with the inclusion of a covariate as an additive or multiplicative interactive model. The p.value is calculated on the likelihood ratio, wald test. An adjusted p.values can be calculated based on Benjamini-Hochberg correction method. In the output table, genes and pathways are ranked by the likelihood ratio p.value.The Connectivity Mode offers the user the ability to analyze the similarity between pathways associated with survival. The hazard ratio ranked pathways from the pipeline mode can be used as input to the DRPPM-Jaccard-Connectivity R Shiny app to generate hierarchical clustering based on gene-set similarity. A Jaccard function can calculate distance between pathways:The Jaccard score function A contains n set of genes, A = B contains m set of genes, B = The Jaccard matrix can be visualized as a heatmap.Next, the pathways can be clustered using the hclust function from R (v4.1.0) into k-groups (user-specified). Clusters can be visualized as a dendrogram. To overlap survival-associated gene expression, genes within the pathway can be displayed as a table with a flexible sorting feature and added annotation information.From the pipeline mode, we can derive a hazard ratio ranked gene list, which can then be applied as input to the DRPPM-HazardRatio-Ranked-GSEA R Shiny app. This application takes a two-column file of the gene symbols and hazards ratios, which is used as input to the GSEA function from clusterProfiler (v4.0.5). The application performs GSEA, and results can be visualized as a table with additional options for visualizing the GSEA plots through the gseaplot2 function from enrichplot (v1.12.3).3.To demonstrate functionalities of the DRPPM-PATH-SURVEIOR framework, we have included use-case examples of biomarker discovery in a cohort of immunotherapy-treated melanoma patients. We have also provided an example use-case strategy for drug repurposing in pediatric acute myeloid leukemia patients.Pipeline Mode” and identified 100 genes associated with the better prognosis (Supplementary Table S1). These include PRF1 and HLA-DPA1, which have been previously reported as predictive biomarkers for ICI therapy . Through the DRPPM-PATH-SURVEIOR suite of tools, we examined pathways and genes associated with poor outcome and identify therapeutic targets in high-risk patients. First, single samples gene set enrichment analysis (ssGSEA) was performed using the expression data in tandem with the Library of Integrated Network-based Cellular Signatures  LINCS1000 gene sets to calculate the pathway scores (f action . Notablyf action . Furtherf action . Taken t4.DRPPM-PATH-SURVEIOR is designed to visualize and perform systematic survival analysis based on gene pathway information. The application is designed for users with limited experience in programming as well as for advanced users to perform systematic high-throughput pathway screening. In the interactive mode, the Shiny application will ensure reproducibility and can be easily set up and applied in any cohort. In the pipeline mode, the user can apply univariate and multivariate analysis of pathway and patient covariates associated with patient outlook. Our current application can also perform GSEA based on hazard ratio ranking as well as pathway clustering to examine shared gene and pathway features associated with survival. As more RNA sequencing and proteomics data are being captured in large clinical trials, we anticipate DRPPM-PATH-SURVEIOR will enable a collaborative environment for exploring pathway-level and immune features that is predictive of treatment efficacy, especially for immunotherapy.


Ischemic stroke accounts for 70–80% of all stroke cases, leading to over two million people dying every year. Poor diagnosis and late detection are the major causes of the high death and disability rate.In the present study, we used the middle cerebral artery occlusion (MCAO) rat model and applied comparative transcriptomic analysis, followed by a systematic advanced bioinformatic analysis, including gene ontology enrichment analysis and Ingenuity Pathway Analysis (IPA). We aimed to identify novel biomarkers for the early detection of ischemic stroke. In addition, we aimed to delineate the molecular mechanisms underlying the development of ischemic stroke, in which we hoped to identify novel therapeutic targets for treating ischemic stroke.In the comparative transcriptomic analysis, we identified 2657 differentially expressed genes (DEGs) in the brain tissue of the MCAO model. The gene enrichment analysis highlighted the importance of these DEGs in oxygen regulation, neural functions, and inflammatory and immune responses. We identified the elevation of angiopoietin-2 and leptin receptor as potential novel biomarkers for early detection of ischemic stroke. Furthermore, the result of IPA suggested targeting the inflammasome pathway, integrin-linked kinase signaling pathway, and Th1 signaling pathway for treating ischemic stroke.The results of the present study provide novel insight into the biomarkers and therapeutic targets as potential treatments of ischemic stroke.The online version contains supplementary material available at 10.1186/s13036-023-00362-8. Due to the changes in living habits, stroke also tends to occur at a younger age [Stroke is the second-leading cause of death and the most frequent cause of permanent disability in adults worldwide , 2. Stronger age . Hence, nger age . In a monger age . Furthernger age . More inIn the present study, we used the middle cerebral artery occlusion (MCAO) mouse model and applied comparative transcriptome sequencing, followed by systematic bioinformatic analysis, including gene ontology (GO) and Ingenuity Pathway Analysis (IPA) to delineate the molecular mechanisms underlying the development of ischemic stroke. Our result showed the differential gene expression in the brain tissue of the MCAO model. The result of bioinformatic analysis further highlighted the importance of these genes in neuroinflammation and deteriorated neurological functions. More importantly, we have identified some novel biomarkers, including angiopoietin-2 (Angpt2) and leptin receptor (Lepr), for the detection of ischemic stroke. Angpt2 is reported to play a role in vascular physiology and pathophysiology . Lepr isMale Sprague Dawley rats  were obtained from the central animal facility of Guangxi Medical University . The animals were housed under standard conditions of light and dark cycles  with free access to food and water. Each rat was housed in a separate cage to avoid interference in the housing environment. In addition, the cages were regularly cleaned. All the animal studies were conducted according to the approved protocols and guidelines of the Institutional Animal Ethical Care Committee of Guangxi Medical University Experimental Animal Center.The establishment of the cerebral ischemia model has been described in a previous article . Seven rThe modified neurologic severity score (mNSS) was used to evaluate the neurobehavioral outcome 1 day after MCAO as described in a previous study . There aAt 24 h after the reperfusion, rats were euthanized by intraperitoneal injection of a 1% solution of pentobarbital sodium at a dose of 40 mg/kg. Then, ophthalmic scissors and surgical forceps were used to adequately expose the chest and abdomen. After clamping the abdominal aorta, an injection needle was inserted into the apex of the heart, followed by incising the right atrium to allow venous blood to drain. Approximately, 100 mL of physiological saline solution was injected through the injection needle to ensure successful perfusion, indicated by the whitening of the lungs and liver in the rat. Subsequently, brain tissue sampling was conducted. Brains were immediately removed and cut into five serials of 2 mm-thick coronal slices. A 2% solution of 2,3,5-triphenyl tetrazolium chloride was used to assess the infarct zone (white zone). Image-J® (image-processing software) was used by an independent observer, who was blinded to the group status, to measure the ischemic area (the unstained areas) and to calculate the infarct volume in each mouse brain. The infarct area was calculated as the area of the non-ischemic hemisphere minus the non-infarcted area of the ischemic hemisphere. Infarct volume = infarct area × thickness (2 mm). The percent of cerebral infarction was calculated using the following formula: The percentage of cerebral infarction = infarct volume /the volume of the non-ischemic hemisphere × 100.https://cutadapt.readthedocs.io/en/stable/, version:cutadapt-1.9). The clean reads were aligned to the rat reference genome (rn6) using the HISAT2  package. The mapped reads of each sample were assembled using StringTie  with default parameters. Then, all transcriptomes from all samples were merged to reconstruct a comprehensive transcriptome using gffcompare software . After the final transcriptome was generated, StringTie and ballgown  were used to estimate the expression levels of all transcripts and perform expression abundance for mRNAs by calculating fragment per kilobase of transcript per million. Differential gene expression analysis was performed using DESeq2 software. The genes with the parameter of false discovery rate below 0.05 and fold change ≥ 2 were considered differentially expressed genes (DEGs). DEGs were then subjected to GO enrichment analysis and Ingenuity Pathway Analysis (IPA). The Z-score is determined by using the IPA. The DEGs of each treatment group were uploaded to the IPA system for functional analysis . Canonical Pathway Analysis of IPA was used to identify significantly enriched canonical pathways in each treatment group, and Diseases and Functions Analysis of IPA was used to identify significantly enriched diseases and biological functions in each treatment group. The pathway or function with P-value < 0.05 was considered statistically significant. The activation z‐score is to infer the activation states of predicted transcriptional regulators. The activation state of an upstream regulator is determined by the regulation direction associated with the relationship from the regulator to the gene.After the rats were sacrificed (five rats per condition), the cerebral cortex ischemic penumbra was isolated and immediately placed in liquid nitrogen cryopreservation until sequencing. The cerebral ischemic core area of MCAO rats was white, and the brain tissue around the ischemic penumbra was regarded as the ischemic core area, which is intuitive. The ischemic penumbra of the cerebral cortex with a width of 1 mm around the white cerebral ischemic core area was used for sequencing. Total RNA was extracted using Trizol reagent following the manufacturer's instruction as previously described . The totThe brain tissue section was blocked with bovine serum albumin solution  for 1 h at room temperature. Then the section was incubated with primary antibodies against ANGPT2 or LEPR (1:200) at 4℃ overnight. The secondary antibody with horseradish peroxidase was used to bind the antigen antibody complex. The positive labeled cells were counted under microscopy system.p < 0.05), suggesting the severe neurological deficits in the ischemic stroke models. In addition, we found a significant induction of infarct volume, which reflected the clinicopathological deficits in the brain caused by an ischemic stroke .To investigate the biomarkers and molecular mechanisms underlying the development of stroke, the MCAO model was established. The neurobehavioral outcome was evaluated by using the mNSS, including motor, sensory, balance, and reflex tests, after MCAO. We found that the mNSS score was 10 in the MCAO group . The dysregulation of oxygen could lead to alteration of metabolic processes, including the response to the lipopolysaccharide and retinoic acid biosynthetic process, retinol metabolic process , and alteration of cell signaling pathways, such as one involved in the regulation of the extracellular signal-regulated kinase 1 and extracellular signal-regulated kinase 2 cascades, the mitogen-activated protein kinase cascade, protein kinase B signaling, I-kappaB kinase/NF-kappaB signaling, tumor necrosis factor production, NF-kappaB transcription factor activity, phosphatidylinositol 3-kinase signaling, and lipopolysaccharide-mediated signaling pathway in the brain tissue of the stroke model . These alterations might result in immune and inflammatory responses  and alteration of cell proliferation and cell apoptosis . The outcomes would be neurological disorders and diseases such as aging, axon injury, disruption of membrane potential, neuron differentiation, myeloid dendritic cell differentiation, and memory .To investigate the DEGs in the stroke model, a comparative transcriptomic analysis was conducted. We obtained at least 43 million clean reads per sample and translated a total of 66.15 Gb of clean data. By comparing the gene expression profile between the MCAO group and the control group, we identified 2657 DEGs, including 1517 upregulated genes and 1140 downregulated genes . Additionally, immune and inflammatory-related activity, such as chemokine activity, cytokine receptor activity, and C–C motif chemokine receptor binding, was highlighted in our results. In the GO analysis of cellular components, we observed the involvement of postsynaptic membrane, dendritic spine, synapse, immunological synapse, postsynaptic density, neuronal cell body, neuronal cell body membrane, and cortical actin cytoskeleton . Taken together, our data suggested the contribution of the dysregulated gene in the pathology of the stroke model.In the GO analysis of molecular function, we also found the structural alteration of myelin sheath and alteration of many functions related to ion channels such as calcium ion binding, potassium channel activity, extracellular ligand-gated ion channel activity, and chloride channel activity Fig. A . There were 107 DEGs that were closely associated with stroke (Table p < 0.05). Additionally, neuronal functions-and disorders-related signaling pathways, including cAMP response element-binding protein signaling in neurons, glioblastoma multiform signaling, and neuregulin signaling, were also highlighted . The network analysis showed the involvement of many ion channels, enzymes, cytokines, and complexes in these activations . On the other hand, the IPA analysis showed the inhibition of signaling was related to brain functions such as neurovascular coupling signaling pathway, semaphorin neuronal repulsive signaling pathway, endocannabinoid neuronal synapse pathway, dopamine-DARPP32 feedback in cAMP signaling, dopamine degradation, oxytocin in spinal neurons signaling pathway . Moreover, some important cell signaling pathways, including WNT/Ca+, protein A signaling, p53 signaling, Janus kinases (JAK1 and JAK2), tyrosine kinase 2 in interferon signaling, WNT/Î2-catenin signaling, and phosphatase and tensin homolog signaling, were also found to be inhibited in the stroke model. The gene network construction further demonstrated the contribution of ion channels, enzymes, and transcriptional factors in controlling these inhibitions .To delineate the molecular mechanisms and gene network involved in brain disorders in the MCAO model, IPA was conducted. In the diseases and biological functions of IPA, our results highlighted many neurological diseases and abnormalities, especially cerebrovascular dysfunction, and stroke Fig. A .To validate the findings from transcriptome sequencing, immunohistochemistry staining was used to evaluate the induction of the 2 identified biomarkers of ischemia stroke. The results of IHC well-matched with the findings of transcriptomic analysis that both Angpt2 and Lepr were induced in MACO model Fig. A & B  and Angpt2. Angptl4 is already reported as a prognostic marker for ischemic stroke because higher levels of Angptl4 in the plasma were associated with poor prognosis in acute ischemic stroke patients and were a predictive biomarker in atherosclerosis , 22. ManOther than the identification of biomarkers for early detection of ischemic stroke, we also aimed to delineate the molecular mechanisms underlying the development of stroke. We applied IPA, an advanced bioinformatic tool, to analyze the comparative transcriptome data. In this analysis, we primarily focused on the canonical pathways associated with inflammatory responses and neurological dysfunctions in the stroke model. Our results highlighted the activation of the inflammasome pathway, ILK signaling, and the Th1 pathway. Inflammasome, a cytosolic multiprotein complex, plays important roles in the innate immune system in response to inflammation . It contIn conclusion, our study discovered novel biomarkers, such as Angpt2 and Lepr, that could be used for the early detection of ischemic stroke. Moreover, we provided insight into the molecular mechanisms underlying the inflammatory responses and alteration of neural functions in the MCAO model. Our results provide possible pharmaceutical targets for treating ischemic stroke. However, further pre-clinical studies are necessary to warrant the findings of the present works. For instance, a comparative analysis on the serum or cerebrospinal fluid samples from clinical stroke patients would provide us a better understanding on the possible use of these markers for the early detection of ischemic stroke.Additional file 1.