Background: Clinical associations between erectile dysfunction and chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) have been noticed, but the common pathogenic mechanisms between them remain elusive. The aim of the study was to mine shared genetic alterations between ED and chronic prostatitis/chronic pelvic pain syndrome.Method: Transcriptome data of ED and chronic prostatitis/chronic pelvic pain syndrome-related genes (CPRGs) were retrieved from relevant databases and differentially expressed analysis was used to obtain significant CPRGs. Then function enrichment and interaction analyses were performed to show shared transcriptional signature, including gene ontology and pathway enrichment, the construction of protein-protein interaction (PPI) network, cluster analysis, and co-expression analysis. Hub CPRGs and key cross-link were selected by validating these genes in clinical samples, chronic prostatitis/chronic pelvic pain syndrome and ED-related datasets. Then the miRNA-OSRGs co-regulatory network was predicted and validated. Subpopulation distribution and disease association of hub CPRGs were further identified.Result: Differentially expressed analysis revealed 363 significant CPRGs between ED and chronic prostatitis/chronic pelvic pain syndrome, functioning in inflammatory reaction, oxidative stress, apoptosis, smooth muscle cell proliferation, and extracellular matrix organization. A PPI network containing 245 nodes and 504 interactions was constructed. Module analysis depicted that multicellular organismal process and immune metabolic process were enriched. 17 genes were screened in PPI via topological algorithms, and reactive oxygen species as well as interleukin-1 metabolism were regarded as the bridging interactive mechanism. After screening and validation, a hub-CPRG signature consisting of COL1A1, MAPK6, LPL, NFE2L2 and NQO1 were identified and associated miRNA were verified. These miRNAs played an important role in immune and inflammatory response likewise. Finally, NQO1 was identified as a key genetic link between ED and chronic prostatitis/chronic pelvic pain syndrome. It was predominately enriched in corpus cavernosum endothelial cell, and correlated with other male urogenital and immune system diseases tightly.Conclusion: We identified the genetic profiles as well as corresponding regulatory network underlying interaction between ED and chronic prostatitis/chronic pelvic pain syndrome via multi-omics analysis. These findings expanded a new understanding for the molecular mechanism of ED with chronic prostatitis/chronic pelvic pain syndrome. Erectile dysfunction (ED) is a common sexual disorder in men, characterized by the insufficient ability to achieve acceptable sexual performance due to the absence of adequate obtainment or maintenance of penile erectile . AlthougChronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is the most common type of prostatitis based on the NIH category, which could cause great distress to males from all ages . It maniBased on these, in the present study, we explored the genetic interrelationships between ED and CP/CPPS based on cell, tissue and human researches for the 1 time. Besides, significant biomarkers and associated biological pathways were identified and analyzed. Our study would help to clarify the common mechanisms and critical regulators behind the interplay of these two diseases, and guide the treatment in the occurrence of ED and CP/CPPS for further research.https://www.ncbi.nlm.nih.gov/geo/) with the key words “erectile dysfunction,” “chronic prostatitis” and “chronic pelvic pain syndrome”. After screening, five correlative datasets were obtained. Herein, GSE2457 contained expression profiling of corpus cavernosum in rats with ED and corresponding control group (https://www.genecards.org/) and validated in GSE159438.The datasets related to ED and CP/CPPS were searched in the Gene Expression Omnibus (GEO) database . These results were presented with heatmap and Venn diagram by “pheatmap” package and EVenn (http://www.ehbio.com/test/venn/)  .p-value <0.05 and count >2 in the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool (http://david.ncifcrf.gov). GO was categorized into three subsections: biological process, cellular component, and molecular function, and pathways were conducted by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome. And the results were visualized by “ggpubr” and “ggplot2” packages, respectively.After identification of significant CPRGs, Gene Ontology (GO) and pathway enrichment analyses were performed to reveal the possible biological roles of these genes with the threshold of adjusted http://string-db.org) to depict the interactive functions. The screening criteria was set as an interaction score >0.7 and abandonment of disconnected nodes. Then a protein-protein interaction (PPI) network was constructed in Cytoscape . In the present network, the Molecular Complex Detection (MCODE) plugin was utilized to conduct module analysis for representing specific molecular complexes with default values (http://metascape.org) to capture the relationship of enriched terms. It included GO biological processes, KEGG pathway, Reactome gene sets, CORUM and WikiPathways. Then these terms were collected and grouped into clusters based on their membership similarities. Terms with a p-value <0.01, a minimum count of 3, and an enrichment factor >1.5 were regarded as significant.Significant CPRGs were uploaded to the Search Tool for the Retrieval of Interacting Genes (STRING) database , which provided co-expression and functional analysis based on co-expression, co-localization and predicted interactions   , which chttp://mirwalk.umm.uni-heidelberg.de/) based on the reference databases of miRTarBase, TargetScan and miRDB. The expression profiling of these miRNAs was validated in clinical specimens of 20 ED patients and control groups in GSE182053. Then a miRNA–hub CPRGs regulatory network was constructed in Cytoscape. The biological functions of miRNAs were conducted in the miRNA Enrichment Analysis and Annotation Tool (miEAA 2.0) database with the threshold of p < 0.05 (https://ccb-compute2.cs.uni-saarland.de/mieaa2/).Hub CPRGs-associated miRNAs were predicted in miRWalk database    was emplThe analytic process of this research was depicted in To reveal the biological functions and associated pathways of significant CPRGs, the function enrichment analysis was performed based on GO, KEGG and Reactome terms . In GO aIn KEGG analysis, shared pathways contained PI3K-Akt signaling pathway, HIF signaling pathway, and ECM-receptor interaction . And extTo analyze the interplays among these significant CPRGs, a PPI network was constructed. It consisted of 245 nodes and 504 interactions . Then gePPI network provided an interactive landscape in these CPRGs. To find the core role in this network, six topological ranking algorithms were utilized to identify the most corresponding components. After comparative analysis, 17 genes exhibited great connectivity . FurtherThe expressed pattern of 17 genes in GSE2457 was exhibited in a boxplot. The result showed that seven of 17 genes remained significant differences between ED and control groups . In the Considering miRNAs could contribute to the process in the interaction of ED and CP/CPPS, miRNAs related to hub CPRGs were predicted first. After validation in clinical specimens, 29 of 862 miRNAs were obtained. Then a co-regulatory network with hub CPRGs as the core components miRNAs as edges was generated . ConsistSince CPRGs were screened from ED-related expression matrix and CP/CPPS-related gene sets progressively, to enhance authority and preciseness, hub CPRPs were validated further in external CP/CPPS and ED-related cellular gene sets simultaneously . After pThe subpopulation distribution of NQO1 in corpus cavernosum was explored in MHA. The result showed that seven types of cells with 11 subtypes existed in human corpus cavernosum for clustering analysis. They consisted of corpus cavernosum endothelial cell, vessel endothelial cell, PI16-positive fibroblast, APOC1-positive fibroblast, COMP-positive fibroblast, pericyte, corpus cavernosum smooth muscle cell, vessel smooth muscle cell, Schwann cell, macrophage and T cell . NQO1 waConsidering immune response was enriched in the biological functions of CPRGs and related miRNAs, disease association of NQO1 was utilized in CTD. In male urogenital disease, apart from ED and prostatitis, NOQ1 was associated with testicular and male infertility . In immuHigh morbidity and prevalence of ED and CP/CPPS in men have been noticed in recent years . The coeThe initial analysis identified 173 upregulated and 190 downregulated shared genes in ED and CP/CPPS. Since both were caused by various etiological factors, to distinguish their heavy interconnection, functional enrichment analysis was conducted first. Obviously, apoptosis, oxidative stress, inflammatory response related to interleukin, and smooth muscle cell proliferation contributed to the predominant functions in these conditions. In a rat model of prostatitis, except for impaired erectile function, CP/CPPS could enhance oxidative stress and calcium imbalance and promote transformation from contractile to synthetic state in corpus cavernosum smooth muscle cells . InflammA total of 363 significant CPRGs were heterogeneous gene sets. Cluster analysis in PPI network showed different roles of these genes. It was notable that module two and three focused on immune metabolic process, including 21 genes and 40 interactions. Actually, CP/CPPS was more likely to be considered as an autoimmune disease. Many autoantigens have been identified in the pathogenesis of CP/CPPS . Chen etin vitro and in vivo demonstrated that defects in chemotaxis of monocytes and neutrophils were noticed in MAPK6-deficient cells. MAPK6 was essential to produce several cytokines like IL-8 and activating protein 1 H dehydrogenase family and encodes a cytoplasmic 2-electron reductase. Similar to LPL, NQO1 manifests a protective process against inflammatory stimuli and oxidative injury in multiple systems including endothelial and vascular smooth cells . The finvia the bioinformatics was unavoidable. In addition, due to limited eligible datasets related to ED and CP/CPPS, recapitulating the shared genetic alternations wasn’t persuasive enough. And different types of diabetes were used in the analysis of associated miRNAs. Considering the predominant roles of hub CPRGs in ED ad CP/CPPS, more experimental verification and prospective studies will be conducted in our further research.This study could provide new views into the genetic patterns of the shared transcriptional signature in ED and CP/CPPS. However, some limitations were exposed in the present analysis. This study performed relevant molecular excavation based on cell, animal, and human samples with validation, but approach bias via multi-omics analysis. A hub gene signature consisting of COL1A1, MAPK6, LPL, NFE2L2, and NQO1 as well as corresponding regulatory network were well screened and validated. NQO1 was regarded as a key in the genetic links of the two conditions. These findings laid the groundwork for the molecular mechanism of ED with CP/CPPS, and paved the way to fueling the clinically oriented research.We identified the genetic profiles underlying interaction between ED and CP/CPPS


Clerodendrum is a diversified genus with a wide range of economic and pharmacological properties. Limited studies were conducted on the genus's putative anticancer properties and the mechanisms of action based on biological networks remains unknown. This study was aimed to construct the possible compound/target/pathway biological networks for anticancer effect of Clerodendrum sp. using docking weighted network pharmacological approach and to investigate its potential mechanism of action.  Cancer is a second leading cause of death in the world, killing approximately 3500 per million people each year. Therefore, the drugs with multitarget pharmacology based on biological networks are crucial to investigate the molecular mechanisms of cancer drugs and repurpose the existing drugs to reduce adverse effects. Clerodendrum sp. Compounds were retrieved from public databases and screened using eight molecular descriptors. The cancer-associated gene targets were retrieved from databases and the function of the target genes with related pathways were examined. Cytoscape v3.7.2 was used to build three major networks: compound-target network, target-target pathway network, and compound-target-pathway network.  A total of 194 natural Clerodendrum sp. involves 6 compounds, 9 targets, and 63 signaling pathways, resulting in multicompounds, multitargets, and multipathways networks. Additionally, molecular dynamics (MD) simulations were used to estimate the binding affinity of the best hit protein-ligand complexes. Conclusion. This study suggests the potential anticancer activity of Clerodendrum sp. which could further contribute to scavenger novel compounds for the development of new alternative anticancer drugs. Our finding indicates that the anticancer activity of  Cancer is a neoplasmic disease that regulates uncontrolled cell division and leads to abnormal growth of cell mass. In 2018, the World Cancer Report estimated about 1.16 million new cases with 784,800 deaths and 2.2.6 million in 5-year prevalent cases in India. The National Cancer Institute had listed eight categories for the cancer treatment which include chemotherapy, radiation, surgery, targeted therapy, stem cell transplant, and medicines and immunotherapy , 4. TherWith the development of computational approach, disease networks constructed through network biology are suggested as powerful tools for screening out drugs targets. Network pharmacology developed by Hopkins enhances high rate of clinical success with less side effects, and around 40% of the current drugs discoveries were contributed by this approach . This apClerodendrum sp. reported to inhibit cancer activity but its efficiency and mechanism remain unclear until today [Clerodendrum to be effective against cancer. The genus Clerodendrum consists of 580 species that are widely distributed in tropical and subtropical regions of the world that comprises of small trees, shrubs, and herbs [Clerodendrum were isolated and identified till date. Many species of this genus were used as folk medicines by various tribes of African and Asian continents for the treatment of life-threatening diseases, anticancer, antitumor, antidiabetic, antihypertensive, and antidiarrhoel activities [C. thomsoniae, C. indicum, C. panniculatum, C. inerme, C. japonicum, and C. speciosum are cultivated for their aesthetic values. C. inerme, C. thomsonia, and C. splendens are among the most sought for cultivation in gardens, for covering fences and walls.The practices of natural products from plants are widely accepted as potential new lead source towards the discovery of new alternative anticancer drug. The secondary metabolites extracted from plants were considered as the primary source of drugs in Indian and other ancient systems of medicine in the world due to its higher structural diversity, metabolism in the body with low toxicity, and complexity than synthetic drugs . These bil today . In thisnd herbs . Many rend herbs –17. Moretivities , 19. BesClerodendrum sp. using molecular docking, network pharmacology, and molecular simulations analysis, which could further provide basis for subsequent studies and clinical applications. The detail flowchart of this study was depicted in Even though there are many studies on pharmacological effects of the genus but the anticancer activity of the genus based on in silico analysis and network pharmacology were elucidated till date. Therefore, this study was aimed to explore the active compounds, potential targets, and biological pathways of the Clerodendrum sp. were retrieved through extensive literature survey [https://www.accelrys.com/). Further, the three dimensional (3D) structures were converted to.pdb format. The dataset of compounds was further analysed, and hydrogen was added using CHARMm based on smart minimizer that generates 1500 steps of Steepest Descent followed by conjugate gradient algorithms with a convergence gradient of 0.001 kcal mol. The details of bioactive compounds retrieved from Clerodendrum sp. are listed in The bioactive natural compounds (NCs) of e survey –23. The Additionally, 43 approved drugs molecules related to cancer were collected from Drug Bank and selected as reference to analyse the NCs library. The molecular descriptors of NCs and drugs were calculated using the PaDEL-Descriptor software.The principal component analysis (PCA) was conducted on the NCs and drug library by using the BioVinci tools to visualize the distribution of libraries in the chemical space. The PCA analysis was performed with 8 molecular descriptors: ALogP, Molecular Weight, Number H-Donors, Number-H Acceptors, Number Rotatable Bonds, Number of Rings, Number of Aromatic Rings, and Molecular Fractional Polar Surface Area.https://www.openmolecules.org/propertyexplorer/applet.html).The ADMET study refers to the pharmacokinetics approach of a molecule where absorption, distribution, metabolism, excretion, and toxicity of the compounds could be analysed. The ADME and toxicity properties of the selected NCs were predicted using PreADMET server and Osiris Property Explorer (Homo sapiens' were selected. The information of the collected protein targets is listed in The protein targets associated with human cancer were collected from four resources: (i) Therapeutic Target Database (TTD) , (ii) DrHomo sapiens.” This database constructs nodes and edges of network to represent proteins and protein-protein associations. To ensure high confidence information, the minimum score was set to >0.9 and excluded the disconnected proteins in the networks. The potential target proteins and protein pathways involved in cancer were recorded in an excel table and imported into the Cytoscapev3.7.2 to obtain target pathway network.The PPI data was obtained from STRING 11.0  with species restricted to “Homo sapiens' for GO (Gene Ontology) enrichment analysis and KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathway annotation [All the potential target genes were uploaded to DAVID  database. The identifier was selected as ‘OFFICIAL GENE SYMBOL', and species were selected as ‘notation .The bioactive NCs were docked to target protein using PyRx tool . In thisNetwork Pharmacology approach was used to predict the polypharmacological potency of NCs to identify potential anticancer drugs . The thrClerodendrum NCs and potential cancer targets. In this study, NVIDIA RTX 1060 GPU accelerated GROMACS 2021 software; running over Linux Ubuntu 20.04 LTS operating system was used. The topology of protein and ligands were generated using Charmm36 force field and SwissPARAM server [+ and Cl− ions. The energy was minimized by the steepest descent minimization algorithm with maximum 50,000 steps. Position restrains were applied to receptor and ligand of the each systems for 100 ps throughout heating (300 K) utilizing NVT  together with leap-frog integrator, 2 fs time step, and LINCS holonomic constraints. After NVT, NPT  equilibration was conducted at 300K temperature for 100 ps using 2 fs time step. Finally, 10 ns MD production run was generated without any restrain with 2 fs time step, and structures were recorded at each 10 ps coordinates. The trajectories files of root mean square deviation (RMSD), root mean square fluctuation (RMSF), Radius of gyration (Rg), and a number of hydrogen bond analysis (H-bonds) were calculated after completion of MD simulations for further analysis.MD simulation was conducted to analyse the stability of protein-ligand complexes between M server . The solClerodendrum sp. were screened to create a compound library and evaluated with the eight molecular descriptors such as molecular weight (MW), number of hydrogen bond acceptors (HBAs), number of hydrogen bond donors (HBDs), total polar surface area (TPSA), and the drug-like properties of the NCs and drugs. In this study, it was found that out of 194, 126 natural products satisfied the eight physiological conditions and the details are provided in Clerodendrum and reported drug libraries were further evaluated using PCA to visualize its allocation in the chemical space. The eight molecular descriptors were used to generate the PCA model. We found that the distributions of NCs (Red sphere) are analogous to the 3D space occupied by the reported compounds (Blue sphere) and specify the resemblance of drug like assets in NCs with potential anticancer activity. The variances of PCA1, PCA2, and PCA3 are -1.98, -1.45, and -3.27, respectively . The following pathways with largest number of genes involved were cancer pathways , PI3K-Akt signalling pathway , proteoglycan in cancer , prostate cancer , Focal adhesion . The comparative analysis of 10 KEGG pathways with the strongest correlation revealed that among the 54 potential targets genes, the genes repeatedly associated with these pathways were MAPK1, PIK3CA, HRAS, EGFR, TP53, PRKCA, SRC, PDPK1, TGFBR2, TGFBR1, ERBB2, CASP3, BRCA2, XIAP, FGFR3, and CDK2 which are depicted in KEGG pathway annotation showed that 54 out of 60 (90.0%) potential targets were enriched and involve 71 pathways, and 63 of these pathways were significantly correlated with target genes  to understand the mechanism of action between NCs of  targets . The C-TP ≤ 0.05) were obtained by placing cancer-targeted genes in DAVID for KEGG pathway analysis. We constructed the T-P network by combining the pathways with cancer-related gene information. This network analyses the interaction of cancer targets and relationship between pathways and targets  and 1ry0 cancer target along with PG2 the co-crystallized ligand as the standard. The MD trajectories of Scutellarein-1ry0 and 17-hydroxyteuvincenoneG-1ry0 complexes were compared with co-crystallize ligand prostaglandin D2 (PG2)-1ry0 and values of RMSD, RMSF, Rg, and H-bond were recorded. The complex with a lesser RMSD value could be more stable as compared to higher RMSD values.G formed stable complexes with 1ry0 as compared to co-crystallize ligand PG2. The backbone RMSF of each residue was calculated to access the amino acid residues contributing to the complex structural fluctuations. The average RMSF values of Scutellarein-1ry0, 17-hydroxyteuvincenoneG-1ry0 and PG2-1ry0were 0.14 nm, 0.23 nm, and 0.57 nm, respectively. From the graph G and PG2. This suggests that Scutellarein was more stable and rigid than the 17-hydroxyteuvincenoneG structure and PG2.The average RMSD values for Scutellarein-1ry0 and 17-hydroxyteuvincenoneG-1ry0 complexes were found to be 0.29 nm and 0.34 nm, respectively, which are significantly stable as compared to the native co-crystal ligand PG2 (0.56 nm). The Scutellarein-1ry0and17-hydroxyteuvincenoneG-1ry0 complexes had a lower RMSD value that range from 0.06 nm to 0.59 nm, 0.07 nm to 0.76 nm, while PG2-1ry0 complexes range from 0.06 nm to 0.98 nm . It indiG and PG2, which indicates that Scutellarein had a compact and stable complex with 1ry0 during the MD simulation period. Additionally, the H-bonds indicate a crucial role in molecular recognition and determine the stability of the drug-protein complex structure. In G and PG2 forms a stable protein-ligand complex with 1ry0 cancer target protein and does not depict any conformational change in protein structure during the simulation process.The analysis of Rg is considered as root mean square distances from each atom of the system to its centre of mass. As depicted in Clerodendrum sp. were evaluated against 60 reported human cancer proteins. All the compounds were initially screened based on molecular descriptors and PCA analysis was evaluated to determine the relationship between statistically meaningful conformations sampled during the trajectory. ADMET profiling of compounds was considered as significant features for drug development [Some of the developed cancer therapies have resulted in drug resistance against the synthetic drugs . Therefoelopment . The parClerodendrum compounds in treating cancer. PPI networks were constructed with 52 nodes and 149 edges and indicated 22 top hub genes with the highest degree in MAPK1, TP53, HSP90AA1, SRC, PIK3CA, HRAS, EGFR, ESR1, ERBB2, PRKCA, AURKA, BRCA1, AR, PGR, JAK2, PDPK1, PPP2CA, TYMS, TOP2A, AURKB, CDK2, and TERT.The possible mechanism of action and signaling pathways associated with the 60 cancer genes were elucidated with enrichment analysis. The GO enrichment analysis of cancer proteins recorded 29 charts, 45 charts, and 161 charts for CC, MF, and BP analysis. KEGG pathway analysis was performed to examine the signaling pathways and functions of the identified target genes . The anaClerodendrum sp. compounds in the treatment of cancer by analysing network interaction between C-T, T-P, and C-T-P. The network between the C-T was evaluated using degree and betweenness centrality, which indicates the number of related nodes in the network. The C-T network suggested that 6 compounds L51 (Scutellarein), L2 (17-hydroxyteuvincenone G), L54 (Teuvincenone A), L10 (Acacetin), L55 (Teuvincenone E), and L50 (Scutellarein 7-glucuronide) had potential pharmacological activities against cancer (G showed significant cytotoxicities activities against the growth of human promyelocyticleukemia (HL-60) and human lung adenocarcinoma epithelial (A-549) tumor cell lines [E had remarkable in-vitro cytotoxicity activity against human cell lines [Clerodendrum sp. in the treatment of cancer (The docking weighted network pharmacology approach was employed to explore the polypharmacological effects of t cancer . This stll lines . Teuvincll lines , and acall lines  and breall lines . The ninf cancer . TherefoClerodendrum compounds against cancer.The network analysis of T-P and C-T-P supports different pathways such as Pathway in cancer, PI3K-Akt signaling pathway, Proteoglycans in cancer, MAPK signaling pathway, Focal adhesion, and Prostate cancer as potential signaling pathways to mediate the significant effects of G had favourable conformational stability, flexibility, and binding energy when docked with 1ry0 as compared to the co-crystallized structure of the standard 1ry0-PG2 complex. Therefore, Scutellarein and17-hydroxyteuvincenoneG could be proposed as effective compounds in inhibition of protein target for further in-vitro and in-vivo anticancer studies. Many studies suggest that modulation of multi-targets rather than single targets could lead to discovering effective drugs [MD simulation could determine the underlying dynamics of protein-ligand interactions . Based ove drugs . Hence, Clerodendrum compounds. The result of Network pharmacology analysis revealed that 6 active compounds exert their anti-cancer activity with 9 targets in 63 pathways. These results suggested that the identified compounds might contribute to regulate with different cancer related genes and signaling pathways with potential applications in cancer treatment. Further in-vivo experimental studies are still in demands to validate our findings as this study was performed based on data analysis and contributes to scavenger new source of compounds and the development of new anti-cancer drugs.A total of 58 compounds were screened based on molecular descriptors, PCA analysis, and ADME/toxicity. The 60 cancer target genes were analysed with GO annotation, KEGG pathway, and PPI interactions. The selected NCs and cancer targets were analysed with network-related tools to confirmed and reveal the potential anti-cancer activity and molecular mechanism of


Arginylation, the ribosome-independent transfer of arginine to protein/peptide, was discovered nearly six decades ago . DespiteIn a certain sense, the lack of understanding of arginylation even leads to a false impression that this phenomenon may be unimportant. However, arginylation is an exceptionally widespread process that has been found in all eukaryotes examined . Such a Waken the Silent Majority: Principles and Pathogenic Significance of Non-Acetyl Acylation and other Understudied Post-Translational Modifications,” several papers directly relevant to the intriguing phenomenon of arginylation are included to showcase the diverse functions of this PTM and the evolutionary root of arginyltransferase1 (ATE1) (In this Research Topic “1 (ATE1) , the mai1 (ATE1) .Chen and Kashina, a concise and balanced summary of many different types of PTMs on both the N- and C-termini of proteins are presented for their biochemical mechanisms and potential physiological roles. These include arginylation, which is mostly an N-terminal modification. In the original research paper “Arginylation regulates G-protein signaling present in the retina” by Fina et al., the researchers found that several components in the G-protein signaling complexes in retina are subjected to arginylation, which may in turn affect the retinal function. In another research paper “Protein Posttranslational Signatures Identified in COVID-19 Patient Plasma” by Vedula et al., researchers used comprehensive proteomic approaches and identified significant alterations of arginylation  signatures in the plasma of COVID-19 patients. While the exact physiological meaning of these changes still awaits further clarification, this finding nevertheless highlights the potential involvement of arginylation in virus-induced pathological conditions. Finally, new clues for interpreting the role of the arginylation enzyme ATE1 was provided in the original research “Regulation of Mitochondrial Respiratory Chain Complex Levels, Organization, and Function by Arginyltransferase 1” by Jiang et al. (contributed by my own research group). In this study, a small fraction of ATE1 was found located inside mitochondria and is essential for the proper function of mitochondria in respiration. Intriguingly, homologues of eukaryotic ATE1 can be traced back to alpha-proteobacteria, relatives of the ancient ancestor of mitochondria. This connection between ATE1 and mitochondria may constitute a new angle for understanding the diverse functions of ATE1 in cellular metabolism (In the review paper “Post-translational Modifications of the Protein Termini” by tabolism , stress tabolism , and oxytabolism .Overall, while arginylation is still a poorly understood process, the papers presented in this Research Topic will help to shorten the gap. Hopefully with more research and further advancements of techniques including proteomic study tools, a more comprehensive picture of arginylation will soon be on the horizon.


Differentially reactive antigens were compared to gene expression data from an alternate public GBM data set from OncoDB, and were analyzed using the Reactome pathway browser. Protein array analysis identified approximately 350–800 differentially reactive antigens, and revealed different antigen profiles in the glioblastomas and meningiomas, with approximately 20–30%-similar and 10–15%-similar antigens in preoperative and postoperative sera, respectively. Seroreactivity did not correlate with OncoDB-derived gene expression. Antigens in the preoperative glioblastoma sera were enriched for signaling pathways, such as signaling by Rho-GTPases, COPI-mediated anterograde transport and vesicle-mediated transport, while the infectious disease, SRP-dependent membrane targeting cotranslational proteins were enriched in the meningiomas. The pre-vs. postoperative seroreactivity in the glioblastomas was enriched for antigens, e.g., platelet degranulation and metabolism of lipid pathways; in the meningiomas, the antigens were enriched in infectious diseases, metabolism of amino acids and derivatives, and cell cycle. Antibody profiling in both tumor entities elucidated several hundred antigens and characteristic signaling pathways that may provide new insights into molecular pathology and may be of interest for the development of new treatment strategies.Studies on tumor-associated antigens in brain tumors are sparse. There is scope for enhancing our understanding of molecular pathology, in order to improve on existing forms, and discover new forms, of treatment, which could be particularly relevant to immuno-oncological strategies. To elucidate immunological differences, and to provide another level of biological information, we performed antibody profiling, based on a high-density protein array (containing 8173 human transcripts), using IgG isolated from the sera of  In previous work, we have shown that the immunome provides biologically meaningful information in cancer [Glioblastomas are the most aggressive type of brain tumor with poor prognosis, with an incidence of 3.19–4.17 cases per 100,000 person-years . The stan cancer ,7,8 and While glial-derived glioblastoma is the most serious form of malignant brain tumor, meningiomas are generally slow-growing benign tumors that arise from the arachnoid cap cells of the leptomeninges, the soft coverings of the brain and spinal cord. The current state of knowledge on characteristics and therapy options was recently reviewed ,12. WhilAlthough glioblastomas and meningiomas are vastly different, the discovery of the genetic and epigenetic signatures has provided insight into their biology, and has enabled the identification of novel biomarker candidates and potential therapeutic targets for glioblastomas and refractory meningiomas. We present here our immunological approach to elucidating another layer of biological information, which employed antibody profiling based on a high-density protein array, using IgG purified from sera of preoperative and postoperative glioblastomas and meningiomas, compared to cancer-free controls, in order to (I) identify differentially reactive antigens (DIRAGs) for both tumor groups, which (II) were also analyzed using pathway analysis, to gain insights into the underlying biological processes, as shown in n = 12 preoperative, and n = 16 postoperative) and from patients with meningiomas , and from 27 cancer-free controls, which were probed on AIT’s 16 k protein microarray that included human proteins with n = 6124 annotated human genes and 8173 different annotated human transcripts, recombinantly expressed from 15,312 cDNA E. coli clones. Fluorescence data obtained from microarray images were analyzed for differentially reactive antigens (DIRAGs) between preoperative and postoperative glioblastomas and meningiomas, and were compared to cancer-free controls. Higher reactive proteins within the case groups were subjected to the Reactome pathway browser, to examine the underlying disease pathways and altered pathways in pre-surgery vs. controls and in pre-surgery-vs.-post-surgery patients. In addition, antibody reactivity data in glioblastomas were compared to public gene expression data from OncoDB, as summarized in To identify and study tumor-associated antibody signatures in glioblastomas and meningiomas, serum IgG was probed on high-density protein microarrays. IgG was isolated from pooled preoperative and postoperative sera from patients with glioblastomas  in duplicate. The median IgG concentration obtained from all 144 samples was 6.70 ± 3.54 mg/mL serum. The group mean values of the calculated serum IgG concentration were as follows: preoperative glioblastomas, 6.78 ± 2.19 mg/mL; preoperative meningiomas, 6.70 ± 2.37 mg/mL; postoperative glioblastomas, 6.76 ± 1.12 mg/mL; postoperative meningiomas, 5.85 ± 1.48 mg/mL; and cancer-free controls, 7.99 ± 4.95 mg/mL.https://www.estimationstats.com/ accessed on 6 August 2022) to analyze potential differences in serum IgG concentrations, using the median difference for four comparisons with the common healthy controls [p = 0.0128; two-sided permutation t-test), as shown in t-test), as shown in We applied the estimation statistics web tool (controls . The unpp < 0.05) differentially reactive antigens (DIRAGs) for respective class comparison: (I) pre/postoperative glioblastomas (GBM-pre/GBM-post) and pre-/postoperative meningiomas (MEN-pre/MEN-post) vs. healthy control—see contrasts (a–d) in n = 8254 remaining features after preprocessing and filtering, exploratory analysis of tumors vs. controls, for the contrasts (a) n = 246, (b) n = 308, (c) n = 375, and (d) n = 199, revealed significantly higher reactive antigens in GBM-pre, GBM-post, MEN-pre, and MEN-post, respectively. In contrast (e), n = 151 antigens were more highly reactive in GBM-pre, and n = 155 were more highly reactive in GBM-post; in (f) n = 232, the antigens were more highly reactive in MEN-pre, and n = 206 were more highly reactive in MEN-post.The following preprocessed and COMBAT and quantile-normalized  IgG profn = 206, and higher in MEN-post, n = 232—contrast (f). Visual comparison of DIRAGS, presented in volcano plots illustrating the mean antigenic reactivities of individual antigens tested in the compared sample groups, shows slightly higher fold changes in GBM contrasts  than in MEN contrasts  which have lower fold-changes in antigenic reactivities (Comparing the number of DIRAGs from (a) GBM-pre vs. controls vs. (c) MEN-pre vs. controls, in (a) 246 and in (c) 375 DIRAGs were higher reactive in cases, whereas in both contrasts the number of higher reactive DIRAGs in controls yielded very similar numbers, of 307 and 311 DIRAGS. Comparing the contrasts (a) GBM-pre vs. controls and (b) GBM-post vs. controls, an increased number of 308 DIRAGs was higher reactive in GBM-post than the 246 DIRAGS in (a); in MEN vs. controls, contrasts (c) and (d), antigenic reactivity was lower in MEN-post, with 199 DIRAGS in (d), compared to 375 in MEN-pre, of contrast (c). The comparison of the number of pre- and post-operations in GBM—contrast (e)—resulted in about 150 DIRAGS in both directions. The numbers of DIRAGS in GBM were lower than in meningioma, where we found higher reactive DIRAGS in MEN-pre, tivities B. The cop-values and fold changes derived from the protein array analysis were in a moderate range, which was consistent with our previous studies performed on other cancers, and also on inflammatory (ulcerative colitis) and autoimmune (rheumatoid arthritis) diseases [The top 10 differentially reactive proteins, based on the mean change in reactivity between classes of these antigens, are summarized in the diseases ,10. The n = 246 significantly higher reactive DIRAGs compared to healthy controls  were found also higher reactive in post-surgery GBMs compared to pre-surgery GBMs (contrast (e)). The DIRAGs higher reactive in GBM-pre and GBM-post vs. controls, from contrasts (a) and (b), as well as those from contrast (e), from both higher and less reactive in either group, and the intersection of these protein lists, are provided in The preoperative IgG reactivity of the glioblastomas showed lastomas B—left ren = 375 significantly higher reactive DIRAGs  of preoperative vs. postoperative meningiomas showed n = 206 significantly higher DIRAGs in preoperative meningiomas, and n = 232 in postoperative meningiomas. Of 375 DIRAGs with higher reactivity in MEN-pre vs. healthy (contrast (c)), and 232 with higher reactivity in MEN-pre compared to MEN-post (contrast (f)), n = 101 (101/375 = 27%) overlapped. Thirty-five (n = 35)—18% of the more reactive DIRAGs (n = 199)—in postoperative meningiomas compared to controls (contrast (d)) were also more reactive compared to preoperative meningiomas (206 higher in MEN-post vs. (f)). A comparison of the antigens that were more reactive in the case groups vs. controls, as derived from preoperative contrasts (a) and (c) vs. postoperative contrasts (b) and (d), revealed an overlap of 59 DIRAGs in (a) and (b) for GBM, and a comparable number of 56 overlapping DIRAGs in (c) and (d) for MEN. Comparison of overlapping antigens from GBM contrasts (a) and (e), n = 49 and n = 13, and (b) and (e), n = 49 and n = 13, with numbers from MEN contrasts (c) and (f), n = 101 and n = 12, and (d) and (f), n = 8 and n = 35, show comparable dynamics in numbers, but a higher number (n = 101) of overlapping DIRAGs in (c) and (f1) (see Meningioma serum-IgG before surgery showed (f1) see .When comparing the higher reactive GBM-pre and MEN-pre antigens from contrasts (a) and (c), we found an overlap of 73 antigens . Comparing the antigens from post-operative contrasts (b) and (d), which showed higher reactivity in GBM-post and in MEN-post, we found an overlap of 30 antigens —GBM-pre vs. healthy, proteins showing higher seroreactivity in GBM-pre were enriched in pathways signaling by Rho GTPases, COPI-mediated anterograde transport, RHO(D) GTPase cycle, vesicle-mediated transport, and pathways in the context of HIV elongation arrest and recovery. Signaling by Rho GTPases and vesicle-mediated transport pathways had the highest numbers, 29 and 24, of affected genes/antigens, respectively.http://oncodb.org/download/expression/expression.zip; http://oncodb.org/cgi-bin/genomic_normal_expression_search.cgi accessed on 30 August 2022)—of gene expression in glioblastomas (n = 148) vs. normal (n = 200), was carried out systematically for the selected top pathways. The search is described below, and also in the following sections, for the pathways found in other contrasts comparing antigenic reactivities deduced from our 16 k protein array analysis. OncoDB was searched for the corresponding gene expression data (using a cut-off of FDR < 0.05), to capture genes overexpressed either in GBM tissue or in normal tissue.It has been shown that in the context of antigenicity, overexpression of Rho-GTPases, or altered expression of proteins associated with these signaling pathways, could lead to increased antigenic IgG reactivity. A very effective search—using ONCODB expression data  were significantly overexpressed. On the other hand, 11 of these antigens  were found to be significantly higher expressed in normal tissue, using the ONCODB-GBM expression data.neutrophil degranulation and n-linked glycosylationasparagine  pathways showed the highest number of antigens—21 and 15, respectively. By comparative analysis with gene expression data from the OncoDB GBM dataset of the 21 antigens that are more reactive in healthy individuals, and are presented in the neutrophil degranulation pathway, 13  were found higher expressed (FDR < 0.05) in GBM, and 5  were found higher expressed (FDR < 0.05) in normal tissue.In testing the antigens which were more reactive in healthy sera compared to the GBM pre-sera of contrast (a), COPI-mediated anterograde transport was used in addition to significant signaling pathways, which is also found in the significant pathways identified by antigens with higher reactivity in GBM-pre, but covers different proteins. The asparagine N-linked glycosylation pathway, TUBA1A, COG4, ALG3, DDOST, GMPPB, GLB1, were found higher expressed (FDR < 0.05) in GBM, and DYNC1H1, DCTN1, TUBB2A, GBF1, MVD, SPTAN1, and ARF1 were found higher expressed (FDR < 0.05) in normal tissue.Of the 15 antigens that were higher in healthy tissue, and presented in the The mRNA-splicing major and axon guidance pathways showed the highest number of antigens, which were more highly reactive in GBM-post, as compared to the seroreactivities of healthy individuals (contrast (b)): of 16 antigens found to be higher reactive in GBM-post, and present in the mRNA-splicing major pathway, SART1, PQBP1, RBM17 and POLR2A in healthy tissue, and 8 antigens  were more strongly expressed in GBM tissue. Of 28 antigens present in the axon guidance pathway, 9  were overexpressed in healthy individuals, and 13  were overexpressed in GBM tissue.Hemostasis and G2/M transition showed the most antigens higher reactive in healthy sera, compared to GBM-post. Of 28 hemostasis antigens higher reactive in healthy, 10  were overexpressed in GBM, and 14  were overexpressed in normal tissue. Of the 17 G2/M transition pathway antigens, 5 were overexpressed in the OncoDB GMB tissue samples  and 7  were higher expressed in normal tissue.Platelet degranulation and metabolism of lipids were the major pathways for antigens, which were higher reactive in GBM-pre vs. GBM-post (contrast (e)), presenting 7 and 15 DIRAGs, respectively. Of the 7 antigens present in the platelet degranulation pathway , two genes (TAGLN2 and MAGED2) were overexpressed in GMB vs. normal tissue; four genes  were higher expressed in normal tissue, while ALB was not differentially expressed in the OncoDB dataset. Out of 15 metabolism of lipid antigens, 8  were overexpressed in GMB, but PLEKHA5 and FASN were overexpressed in normal tissue.In contrast (c), MEN-pre vs. healthy, in addition to COPI-mediated anterograde transport and N-linked glycosylation pathways also found in the GBM contrasts, disease and signaling by receptor tyrosine kinases pathways were found in 51 and 31 present DIRAGs higher reactive in MEN-pre. Asparagine N-linked glycosylation pathways and metabolism of amino acids and derivatives pathways were those found within the antigens that were higher reactive in healthy subjects, compared to MEN-pre. A direct comparison with expression data was not performed for the MEN contrasts, because no corresponding expression data were available in OncoDB.Comparison of signaling pathways in contrast (d), MEN-post vs. healthy, showed that COPI-mediated anterograde transport and ER-to-Golgi anterograde transport were the most prominent pathways of DIRAGs higher, which were higher reactive in MEN-post than in controls. COPI-mediated anterograde transport was also demonstrated, in addition to contrast (c), but ER-to-Golgi anterograde transport was found higher reactive in healthy sera, compared to MEN-pre.Similar to comparing the pathways found to be significant in different contrasts, such as (c) MEN-pre vs. healthy and (d) MEN-post vs. healthy, as above, a direct analysis of the contrast (f) MEN-pre vs. MEN-post placed the infectious disease pathway at the top of the signaling pathways, with 34 DIRAGS identified in MEN-pre as more highly reactive, followed by L13a-mediated translational silencing of ceruloplasmin expression and GTP hydrolysis, and joining of the 60S ribosomal subunit pathways (each presented by 11 antigens). SRP-dependent cotranslational protein targeting to the membrane pathway (10 antigens) has also been found in pathways of contrast (c), similar to the infectious disease pathway. Eukaryotic translation initiation and cap-dependent translation initiation are found on both sides of higher reactive antigens. Both pathways were presented by the same antigens of our data, thereof 11 antigens were higher reactive in MEN-pre , and a different set of 9 antigens  were higher reactive in MEN-post.To analyze signaling pathways enriched from gene expression data, we filtered the OncoDB gene expression data, using a cut-off of log2 fold change > 1 and FDR < 0.05, and identified 2164 genes that were overexpressed in GBM and, vice versa, 2960 genes overexpressed in normal tissue. We then performed a Reactome pathway analysis for both gene lists. Of the genes overexpressed in GBM, 119 pathways, and for genes overexpressed in normal controls, 44 pathways, were found using an FDR < 0.1 cut-off. The 25 most important pathways are shown in FDR-Expr”, which depicts the FDR-values from gene-expression Reactome pathway analysis): thus, differential antigenic reactivity in MEN-pre vs. MEN-post shows a high overlap with pathways associated with genes found overexpressed in GBM vs. normal. Of the 44 pathways derived from overexpressed genes in normal vs. GBM, only 4 pathways (FDR < 0.1) intersected with the contrasts: ion homeostasis (a); interaction between L1 and Ankyrins (b); unblocking of NMDA receptors, glutamate binding and activation, and L1CAM interactions (e).Looking up these pathways from  in the lThe formation and presence of tumor-associated antibodies is a well-known accompaniment to cancer cell transformation and disease progression. Because antibodies have excellent molecular stability, and are potentially formed before tumor clinical manifestation, they offer potential biomarkers. In addition to their potential diagnostic or prognostic value, previous work has demonstrated the possibility of elucidating a novel omics layer of analytics and biological information from antibody profiles, using pathway analysis; therefore, we performed antibody profiling on a 16 k protein array displaying antigenic proteins derived from expression clones (covering 8173 different human transcripts), to identify TAA signatures and pathways of preoperative and postoperative glioblastomas and meningiomas vs. healthy controls.The IgG concentrations in the sample groups were reduced in postoperative GBM patients (not significant) and in postoperative MEN patients. These differences were compensated for by using adjusted IgG concentrations on the protein arrays: thus, 110 samples from preoperative and postoperative tumors and healthy controls were probed on 16 k protein microarrays, and higher reactive DIRAGs were examined using pathway analysis in the Reactome pathway browser. In addition, findings for GBM were compared with corresponding gene expression data from the OncoDB data repository. Tumor-associated antibodies could be of diagnostic interest for minimally invasive early detection applications, and could also provide insights into tumor characteristics and pathogenesis. We found 246 DIRAGs and 375 DIRAGs in pre-surgery glioblastomas and meningiomas samples, respectively, compared to healthy controls A.Gahoi et al. used a similar protein microarray-based approach, to analyze cerebrospinal fluid (CSF) samples from patients with low-grade glioma (LGG) and glioblastoma multiforme (GBM), and identified the antigenic response of NOL4 and KALRN in GBM, while UTP4 and CCDC28A were found as putative tumor-associated antigens in LGG: among these antigens, we only identified UTP4 in our lists of DIRAGs .TM arrays, which presented > 17,000 proteins recombinantly expressed in S. cerevisiae. While no in-depth comparative study was performed, STUB1 and YWHAH, which were dysregulated in grade II glioma patients, were found in our study in the lists of DIRAGs: STUB1 (in contrast (e)—higher in GBM-pre compared to GBM-post, and in contrast (d)—higher in MEN-post vs. healthy) and YWHAH (in contrast (b)—higher in GBM-post vs. healthy, and in contrast (f)—higher in MEN-post compared to MEN-pre) [Syed et al. independently performed another similar study on HuProtMEN-pre) . Using tMEN-pre) .A study focusing on detection of the glioblastoma peptidome, for discovering novel tumor-associated antigens for immunotherapy, exploited the HLA-bound peptides from HLA-A*02(+) glioblastomas, and investigated a subset of 10 glioblastoma-associated peptide antigens in more detail: of those, 2 (derived from proteins BCAN and FABP7) were found higher reactive only in MEN-post when compared to MEN-pre .In another study, Pallasch et al. used SEREX technology, and found that the antigens GLEA1, GLEA2 and PHF3 and occurrence of autoantibodies were associated significantly with prolonged survival of glioblastoma patients . Interesp < 0.05) overlapping between pre-surgery meningiomas and glioblastomas: these 73 were enriched in the pathways of signaling by Rho GTPases, Miro GTPases and RHOBTB3 (n = 17) and COPI-mediated anterograde transport (n = 8), as well as some other pathways with lower antigens present (data not shown); these overlapping antigens may indicate a more general role for the affected tissue, when these are also found in other contrasts, e.g., in postoperative MEN samples.The intersection of the obtained protein lists showed 73 significant higher reactive DIRAGs  autoantigens for diagnostic applications, conceivable therapeutic targets could also be identified.Findings of the Reactome pathway analyses have been described, and also linked to gene expression data from the OncoDB, and are discussed in the following paragraphs, for the different GBM contrasts: (a) GBM-pre vs. healthy; (b) GBM-post vs. healthy; and (e) GBM-post vs. GBM-pre.signaling by Rho GTPases and vesicle-mediated transport pathways, we found the highest number, 29 and 24, of affected antigens.From contrast (a), GBM-pre vs. healthy, among antigens with higher reactivity in GBM Rho GTPases comprise 20 members, and belong to the Ras superfamily of small GTPases: this vast group of proteins has more than 150 members, and the involvement of Rho GTPases in cancer has been controversial, as the identification of the first members of this branch of the Ras superfamily of small GTPases. Initially, no direct involvement in cancer progression was observed, until numerous observations revealed dysregulation of Rho-regulated signaling pathways in cancer. Finally, point mutants in the Rho GTPases Rac1, RhoA and Cdc42 in human tumors have confirmed that Rho GTPases serve as oncogenes in several human cancer types [er types . The inver types . AlteratThe vesicle-mediated transport pathway was found to be enriched when 24 antigens were higher reactive in GBM than in healthy IgG. In respect of that pathway, extracellular vesicles have been studied and published in the context of GBM, and are released from glioblastomas to then modulate the tumor microenvironment. The extracellular vesicles released by tumor microenvironment cells could also modulate glioblastoma cells, and GBMs utilize different communication pathways. EV-mediated communication has unique features, compared to the other communication pathways mentioned, as it allows delivery of the vesicle cargo, not only in the tumor environment—when both tumor cells and the surrounding cells can communicate via EVs—but also in remote locations. Functional aspects, such as modulation of the tumor microenvironment by GBM-derived EVs on monocytes, macrophages, microglia, T cells, endothelial cells, astrocytes and glioma stem cells, were reviewed by Matarredona and Pastor [d Pastor . The resCOPI-mediated anterograde transport pathway at the forefront of the pathway analysis: this shows that this signaling pathway could be affected and disrupted, due to antigenic reactivity. Twenty-one antigens representing the neutrophil degranulation pathway were higher reactive in healthy individuals. When we analyzed the gene expression data set, this pathway was also enriched highly significant (p < 10−6). Sippel et al. studied immunosuppression in patients with GBM and in normal donors, and found that peripheral cellular immunosuppression in patients with GBM is associated with degranulation of neutrophils and elevated levels of circulating serum arginase I (ArgI) [p= 0.0025) enriched for genes overexpressed in GBM, and links to antitumor immunity.Comparing antigenic reactivities in GBM-pre to healthy sera, 10 antigens with higher reactivity in healthy sera put the I (ArgI) : the autn = 15 antigens, which are also more reactive in healthy subjects, and overrepresent the asparagine N-linked glycosylation pathway. As reviewed by Mereitir et al. [A similar link to tumor immunity could be the r et al. , in the r et al. ,28.mRNA-splicing major and axon guidance pathways were found to be the top pathways with higher reactive antigens in GBM-post, when compared to healthy sera (contrast (b)). mRNA splicing major: pre-mRNA splicing occurs within the “spliceosome”, with approximately 150 proteins present in spliceosomes, of which only a subset has been characterized. Several papers have shown that the spliceosome is affected in GBM. Fuentes-Fayos found that the dysregulation of the splicing machinery drives the development/aggressiveness of glioblastomas, when the expression of relevant spliceosome components and splicing factors has been aberrantly expressed [axon guidance pathway, the control of axonal growth and navigation is involved in the interaction with various dysfunctional GBM pathways that control tumor cell proliferation, migration and invasion, as well as tumor angiogenesis or immune response [The xpressed . Recentlxpressed : this waxpressed . In addixpressed . Anotherxpressed . In respresponse . In thisresponse . Xue et response . Similarresponse .hemostasis and G2/M transition pathways were found to be higher reactive in healthy sera compared to reactivities in GBM-post, for contrast (b). Hemostasis: brain vasculature functions are subverted during the development of brain tumors. Vascular perturbations are thought to contribute to disease progression and comorbidities, including thrombosis and hemorrhage; however, better understanding of these molecular linkages is needed, to pave the way to more effective (targeted) therapy, prophylaxis, adjunctive use of anticoagulants, and other agents able to modulate interactions between brain tumors and the coagulation system [G2/M transition pathways are often dysregulated in cancer, and cell cycle dysregulation is a hallmark of tumor cells [Antigens overrepresented in n system . These an system . The expn system : this, an system ,41,42,43or cells ,45,46. Ior cells ,48, and or cells ,50,51,52platelet degranulation and the metabolism of lipids pathways. Any publication is currently found in PubMed when platelet degranulation and glioblastoma are searched. Although several publications related to cancer can be found in the literature, only one study examined the platelet proteome, and found it to be unaltered in patients with brain tumors, but impaired in lung cancer [metabolism of lipids pathway: Shakya et al. have shown a difference in gene expression in associated genes for glioblastoma stem cell niches and non-stem cell niches [Pathway analysis of GBM-post vs. GBM-pre—contrast (e)—generally showed a lower number of antigens enriched in pathways. The two main pathways, with 7 and 15 antigens, that were more reactive in GBM-pre were the g cancer : therefol niches . The roll niches , and actl niches , which cl niches . Lipid ml niches ,57,58,59l niches .COPI-mediated anterograde transport and asparagine N-linked glycosylation pathways, which were also found in the GBM contrasts, the infectious disease and the signaling by receptor tyrosine kinases pathways were higher reactive in MEN-pre, when compared to healthy sera. Antigens higher reactive in healthy vs. MEN-pre were enriched for the asparagine N-linked glycosylation and the metabolism of amino acids and derivatives pathways. In the list of DIRAGs from the class comparison of higher reactive in MEN-post compared to controls, COPI-mediated anterograde transport and ER-to-Golgi anterograde transport were top of the identified pathways. Dai et al. have published KEGG pathways in meningioma from gene expression analysis, and found the AGE-RAGE signaling pathway in diabetic complications, the PI3K-Akt signaling pathway, ECM-receptor interaction and cell-adhesion molecules under the top pathways [Antigens found enriched in meningiomas analyses have been similarly analyzed using the Reactome pathway browser, and are described in the Results section. In addition to the pathways . A direcasparagine N-linked glycosylation, COPI-mediated anterograde transport, MHC class II antigen presentation, transcriptional regulation by E2F6, regulation of expression of SLITs and ROBOs, having antigens enriched in GBM and MEN contrasts. Selective autophagy in GBM, and SUMOylation of DNA methylation proteins were found in several GBM contrasts, while cap-dependent translation initiation, ER-to-Golgi anterograde transport, infectious disease metabolism of amino acids and derivatives, selenoamino acid metabolism, and SRP-dependent cotranslational protein targeting to membrane have been present in multiple MEN contrasts: thus, when we compare pre- and post-operative vs. healthy with itself, it is not unexpected to find several pathways in different contrasts, reflecting the common etiology of the disease, but also the difference between both tumors. While a class comparison analysis to delineate differentially reactive antigens between GBM and MEN is technically feasible, and the number of DIRAGs has been indicated in Comparing the Reactome pathways from the different contrasts in our results, we find multiple pathways in multiple contrasts, like Antibody profiling data using highly-multiplexed-by-array-based platforms is sparse, and a biological interpretation has been performed in very few studies. While direct comparison of study results is difficult, we found several antigens, from published work, matching our data, and made a conclusive description of antigenic reactivities in the context of expression data. The findings described have the potential to support both diagnostic and therapeutic development, particularly with regard to immuno-oncology therapy design and regimen. A broader application and analysis of antigen reactivity as a sole analysis, or in combination with other molecular analytes or omics layers, can be performed easily, and with a very small amount of 10–20 µL of serum or plasma: consequently, this technique has a significant advantage over other omics. As we have demonstrated in our work, antibody testing reflects another biological layer of disease pathology that may help improve diagnostics, reveal more biological detail and potential disease subsets, and allow future stratification and monitoring of treatment response.n = 48). Both meningioma and glioblastoma patients were operated on at the Vienna General Hospital . Clinical data, sample collection and storage were previously described in detail [Serum from newly diagnosed preoperative and postoperative glioblastoma (GBM) and meningioma (MEN) patients without any prior treatment or surgery were collected. The cohort was appended with age- and gender-matched serum from cancer-free controls (n detail . We had n = 28) consisted of 12 pre-surgery and 16 post surgery sera [n = 55) consisted of 26 pre-surgery and 29 post surgery sera [serum samples were collected after overnight fasting on the day of surgery, and 3–4 weeks after the surgery, and were stored at −80 °C, according to the Institutional Review Board protocols approved by Medical University of Vienna. This study was carried out in accordance with the Good Scientific Practice recommendations of the ethics committee of the Medical University of Vienna (190/2011). All subjects gave written informed consent, in accordance with the Declaration of Helsinki.The GBM sample set . The serum was diluted 1:10 with kit buffer, and isolation was performed according to the manufacturer’s instructions. Concentration was determined by duplicate measurements, using A280 spectrophotometry (Epoch Take3 system). The IgG concentration was adjusted to 0.4 mg/mL, with the buffer provided in the kit, and stored at −20 °C until the slide processing.IgG from serum was purified using the Melon Gel™ IgG Spin Purification Kit . The serum was diluted 1:10 with kit buffer, and isolation was performed according to the manufacturer’s instructions. Concentration was determined by duplicate measurements, using A280 spectrophotometry (Epoch Take3 system). The IgG concentration was adjusted to 0.4 mg/mL, with the buffer provided in the kit, and stored at −20 °C until the slide processing.Escherichia coli—cDNA expression clones and technical controls. These represent n = 6124 annotated human genes, and 8173 different human transcripts —cDNA expression clones derived from the UniPex expression library . Production, purification and spotting of recombinant proteins has been previously described in detail [E.coli lysate and elution buffer) were spotted using 48-pin contact printing with a NanoPrintTM LM210 device on SU8 epoxy-dip-coated slides. The slides were vacuum-sealed, and stored at 4 °C until processing. The quality control of the microarray slides included incubation with an anti-His Tag antibody, visual inspection and a qualification experiment—showing high reproducibility, as published [AIT’s 16 k protein microarray was used for antibody profiling studies. This array comprises proteins expressed from n detail ,65. BrieTM  for 30 min at RT with agitation in glass tanks, followed by three washes with 1X PBS pH 7.4 0.1% Triton X-100  for 5 min each. The slides were rinsed with Milli-Q® water, and spin-dried at 900 rpm for 4 min. Sample dilution of 400 µL ) was applied to each clean gasket slide , placed in clean and dust-free hybridization chambers (Agilent G253A), and closed. Air bubbles were removed, and the chambers were placed in a hybridization oven, and incubated for 4 h at RT with 12 rpm. After the incubation slides were opened, the slides were arranged in glass carriers, and washed three times in glass tanks with PBST for 5 min at RT with stirring, rinsed with Milli-Q® water, and spin-dried. For IgG detection, the slides were incubated in a 1:10,000 dilution of Alexa Fluor 647 goat anti-human IgG  for 1 h at RT with agitation in a dark chamber. Final washing comprised three washes with PBST, Milli-Q® rinse and spin drying (900 rpm for 4 min).For slide probing, 16 k slides were equilibrated to room temperature, and blocked with DIG Easy HybThe spin-dried slides were sorted into the slide carriers, and scanned with a Tecan LS 200 Microarray scanner. The TIFF images were loaded in GenePix Pro 6.0, the .gal file was manually aligned, and spots of insufficient quality were flagged. Data were extracted as raw .gpr files, and were further processed in RStudio  and BRB All data preprocessing and differential reactivity analysis steps were performed using RStudio (R version R 4.0.4 and R 4.1.3). Raw fluorescence intensities were loaded into the RStudio environment via the “read.maimages” functions of the limma package , and medp < 0.05, and a fold change cut-off of FC = 1.25. The results lists were sorted and filtered for (significant) DIRAGs higher reactive in the respective case group, and were used as subsets for paired analysis of pre- and post-surgery samples. The intersection of higher reactive DIRAGs was conducted via the JVenn tool [n = 8254 features remained for t-tests (genefilter package). The DIRAGs were sorted and filtered, for their respective p-value (p < 0.05) and fold-change antigenic reactivities between classes.Differentially reactive antigens (DIRAGs) were elucidated via t-tests (genefilter package ) with a enn tool . After dp < 0.05, BH correction method), and the top 10 metabolic pathways were extracted as .txt files.Differential reactivity analysis result lists were sorted and filtered by fold change and proteins with higher reactivity in each case group, and were analyzed via ReactomePA—an R package for Reactome pathway analysis , using Rhttp://oncodb.org/index.html accessed on 30 August 2022 [p-values and FDR-adjusted p-values. Expression data were compared with antibody reactivities based on gene symbols and pathways using gene-subsets selected at a cut-off of log2 fold change >1 and FDR < 0.05, as given in the results text.OncoDB (ust 2022 ) is an o


Complex structural variants (CSVs) are genomic alterations that have more than two breakpoints and are considered as the simultaneous occurrence of simple structural variants. However, detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy. As a result, there has been limited progress for CSV discovery compared with simple structural variants. Here, we systematically analyzed the multi-breakpoint connection feature of CSVs, and proposed Mako, utilizing a bottom-up guided model-free strategy, to detect CSVs from paired-end short-read sequencing. Specifically, we implemented a graph-based pattern growth approach, where the graph depicts potential breakpoint connections, and pattern growth enables CSV detection without pre-defined models. Comprehensive evaluations on both simulated and real datasets revealed that Mako outperformed other algorithms. Notably, validation rates of CSVs on real data based on experimental and computational validations as well as manual inspections are around 70%, where the medians of experimental and computational breakpoint shift are 13 bp and 26 bp, respectively. Moreover, the Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types, including two novel types of adjacent segment swap and tandem dispersed duplication. Further analysis of these CSVs also revealed the impact of sequence homology on the formation of CSVs. Mako is publicly available at https://github.com/xjtu-omics/Mako. EML4-ALK and CD74-ROS1. Though less frequently reported, compared with simple SVs, these multiple breakpoint rearrangements were considered as punctuated events, leading to severe genome alterations at once Computational methods based on next-generation sequencing (NGS) have provided an increasingly comprehensive discovery and catalog of simple structure variants (SVs) that usually have two breakpoints, such as deletions (Dels) and inversions (Invs) However, due to the lack of effective CSV detection algorithms, most CSV-related studies screen these events from the “sea” of simple SVs through computational expensive contig assembly and realignment, clustering of incomplete breakpoints, or even targeted manual inspection In this study, we proposed a bottom-up guided model-free strategy, implemented as Mako, to effectively discover CSVs all at once based on short-read sequencing. Specifically, Mako uses a graph to build connections of mutational signals derived from abnormal alignment, providing the potential breakpoint connections of CSVs. Meanwhile, Mako replaces model fitting with the detection of maximal subgraphs through a pattern growth approach. Pattern growth is a bottom-up approach, which captures the natural features of data without sophisticated model generation, allowing CSV detection without pre-defined models. We benchmarked Mako against five widely used tools on a series of simulated and real data. The results show that Mako is an effective and efficient algorithm for CSV discovery, which will provide more opportunities to study genome evolution and disease progression from large cohorts. Remarkably, the analysis of subgraphs detected by Mako highlights the unique strength of Mako, where Mako is able to effectively characterize the CSV breakpoint connections, confirming the completeness of a CSV event. Moreover, we systematically analyzed the CSVs detected by Mako on three healthy samples, revealing a novel role of sequence homology in CSV formation.i.e., signal graph creation and subgraph detection . dist). Secondly, Mako applies a pattern growth approach to detect the maximal subgraphs as potential CSVs at the whole-genome scale. Meanwhile, the attributes of the subgraph are used to measure the complexity, and CSV types are determined by the edge connection types of the corresponding subgraphs  clipped portion with minimum 10% size fraction of the overall read length; 2) split reads with high mapping quality; 3) discordant read-pairs. As a result, one group of signal nodes is created by clustering clipped-reads or split-reads at the same position on the genome, which is filtered by pos value for each node, and backtracking is only allowed for nodes involved in the current subgraph. Of note, pattern growth via adjacent edges is conditional to the distance constrain (minDist) because these edges are derived from the reference genome instead of alternatives. For example, Mako detects the maximal subgraph ACBD by visiting nodes A, C, B, and D, while the edge between D and E is constrained because of the larger distance . The parameter minFreq is used to measure the frequency of detected subgraphs, and Mako uses minFreq = 1 to avoid missing subgraphs of rare CSVs or incomplete ones. The detected CSV subgraph provides the connections between multiple breakpoints of a CSV, and the attributes of the subgraph are used to measure the complexity of CSVs. Accordingly, Mako defines the boundary of CSVs using the leftmost and rightmost pos values of the nodes and utilizes the number of identical node types multiplied by the number of i.e., A, C, B, and D, and two paired edges  and aligns them to the reference genome with BWA-MEM In this study, we use both simulated and real CSVs to benchmark the performance of different callers. We follow the workflow introduced by the Sniffles In terms of the real data, we are not aware of any public CSV benchmarks due to the breakpoint complexity and underdeveloped methods https://github.com/primer3-org/primer3) is used to design PCR primers, where primers are selected within the extended distance but 200 bp outside of the boundaries of the breakpoints defined by Mako (https://users.soe.ucsc.edu/~kent/) search is performed at the same time to ensure all primer candidates have only one hit in the human genome. Afterward, we select amplification products with the expected product size and bright electrophoretic bands for Sanger sequencing  sequencing and HiFi contigs. We first apply VaPoR K-mer-based breakpoint examination based on haplotype-aware HiFi contigs, from which we calculate the difference between the K-mer breakpoints and predicted breakpoints  are used, akpoints ; File S1Furthermore, we manually curate detected CSVs via Dotplots created by Gepard , which iThe most important feature for a CSV is the presence of multiple breakpoints in a single event. Thus, we first examined the performances of Mako, Lumpy, Manta, SVelter, TARDIS, and GRIDSS for detecting multiple breakpoints. The results were evaluated according to the all-breakpoint match criterion on both reported and randomized CSV-type simulations. Overall, for the heterozygous A and homCSV is considered as a single event consisting of connected breakpoints, and we have demonstrated that Mako is able to detect CSV breakpoints effectively. However, the breakpoint detection evaluation only assesses the discovery of basic components for a CSV and lacks examination for CSV completeness. We then investigated whether Mako could precisely capture the entire CSV interval even with missing breakpoints. According to the unique-interval match criterion, Mako consistently outperformed other algorithms for both reported and randomly created CSVs, while SVelter and GRIDSS ranked second and third, respectively. For the reported CSVs at 30× coverage C and D, We further compared Mako with SVelter, GRIDSS, and TARDIS on the whole-genome sequencing data of NA19240 and SKBR3. Firstly, we compared the callsets of different callers , and fouHaving demonstrated the performance of Mako on simulated and real data, we surveyed the landscape of CSVs from three individual genomes. Specifically, CSVs from autosomes were selected from Mako’s callset with more than one edge connection type observed in the subgraph, leading to 403, 609, and 556 events for HG00514, HG00733, and NA19240, respectively . We systGiven 1568 detected CSVs from three genomes , we further investigated the formation mechanisms of these CSVs. Ongoing studies have revealed that inaccurate DNA repair and the 2–33 bp long microhomology sequence at breakpoint junctions play an important role in CSV formation Currently, short-read sequencing is significantly reduced in cost and has been applied to clinical diagnostics and large cohort studies To sum up, we develop Mako, utilizing the graph-based pattern growth approach, for CSV discovery with 70% accuracy and 20 bp median breakpoint shift. To the best of our knowledge, Mako is the first algorithm that utilizes the bottom-up guided model-free strategy for SV discovery, avoiding the complicated model and match procedures. Given the fact that CSVs are largely unexplored, Mako presents opportunities to broaden our knowledge of genome evolution and disease progression.https://github.com/xjtu-omics/Mako. It is free for non-commercial use by academic, government, and non-profit/not-for-profit institutions. A commercial version of the software is available and licensed through Xi’an Jiaotong University. All scripts used in this study are also included in the Github repository, and a detailed description of using these scripts and other tools is provided.Mako is implemented in Java 1.8, and it is available at Jiadong Lin: Methodology, Software, Formal analysis, Data curation, Visualization, Writing - original draft, Writing - review & editing. Xiaofei Yang: Methodology, Writing - original draft, Writing - review & editing. Walter Kosters: Methodology, Writing - original draft. Tun Xu: Data curation. Yanyan Jia: Validation. Songbo Wang: Validation, Formal analysis. Qihui Zhu: Validation. Mallory Ryan: Validation. Li Guo: Writing - original draft. Chengsheng Zhang: Validation, Writing - original draft. HGSVC: Resources. Charlse Lee: Resources, Writing - original draft. Scott E. Devine: Resources. Evan E. Eichler: Resources. Kai Ye: Conceptualization, Resources, Supervision, Project administration, Funding acquisition. All authors have read and approved the final manuscript.The authors have declared no competing interests.


Paeoniae RadixAlba  in the treatment of adjuvant-induced arthritis (AIA) rats are explained using metabolomics and network pharmacology techniques, and the research evidence for the development of anti-rheumatoid arthritis (RA) drugs is enriched. Methods: The rats were injected with Freund’s complete adjuvant (CFA) to induce arthritis. We then measured the general physical characteristics, examined their X-rays and histopathology to evaluate the pathological condition of the inflammation models, and conducted metabolomics studies on the change in urine metabolism caused by CFA. The lyophilized powder of B at a dose of 2.16 g/kg was orally administered to the rats continuously for 28 days, and the therapeutic effect was evaluated. Network pharmacology prediction shows that B contains the target action of the ingredient, and the simulation of the target molecular docking, in combination with the metabolomics analysis results, shows that B has a potential role in the treatment of AIA rats. Results: B can reduce the paw swelling and pathological changes in rats caused by CFA, reverse the levels of 12 urine biomarkers, and regulate histidine metabolism, phenylalanine metabolism, arginine, proline metabolism, pyrimidine metabolism, etc. The prediction of the active ingredient target in B indicates that it may act as an inflammatory signaling pathway in anti-RA, among them being paeoniflorin, palbinone, beta-sitosterol, kaempferol, and catechin, which are the significant active ingredients. Conclusion: The metabolomics results revealed the markers and metabolic mechanisms of urinary metabolic disorders in rats with AIA, demonstrated the efficacy of the therapeutic effect of B, and identified the key ingredients in B, providing theoretical support for the subsequent development and utilization of B.Objective: The mechanism of action and potential targets of  Paeoniae radix alba  is the dried root of Paeoniae lactiflora Pall. The total glucosides of the paeony of terpenes, such as paeoniflorin, albiflorin, oxypaeoniflorin, benzoylpaeoniflorin, and benzoyloxypeoniflorin, are the major chemical ingredients of B. B is a valuable traditional medicine that is used to cure liver disease, rheumatism, and autoimmune diseases − = 554.2615), with centroid mode at a 50–1200-m/z full scan to collect data.The MS was equipped with an electrospray ion source. In positive ion mode, the capillary voltage was 3 kV, the cone voltage was 20 V, the ion source temperature was 110 °C, the dissolvent gas temperature was 350 °C, and the flow rate was 800 L/h. The cone gas flow rate was 50 L/h, a capillary voltage in negative ion mode was 2.7 kV, and other analysis conditions were the same as for positive ion mode. Leucine enkephalin with a concentration of 1 ng/μL and a flow rate of 10 μL/min was used for real-time mass correction in positive mode ([M + H]t-test statistics (p < 0.05) difference ion for online database biological function analysis , and mass tolerances <10 ppm, and those with MS/MS fragmentation information were considered to be important biomarkers.The raw data were acquired by UPLC-MS using Progenesis QI 2.0 software  to perform peak noise reduction, matching, normalization, and alignment to obtain a matrix with the retention time, molecular formula, normalized abundance, and m/z, SIMCA-P 14.0 for principal ingredient analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) to analyze the differences between groups and determine the variable importance in projection value (VIP) (>1), combined with the student’s http://lsp.nwsuaf.edu.cn/index.php/, accessed on 20 November 2020). We selected the compounds with the pharmacokinetics parameters of oral bioavailability (OB) ≥30% and drug-likeness (DL) ≥0.18. We also utilized GeneCards  and DisGeNET  to retrieve the targets associated with RA and align them to those of the selected compounds described above for further identifying potentially acting RA targets for pathway analysis and molecular docking studies. Visualization of ingredient-target-pathway interaction was achieved using Cytoscape 3.8.0 software [B contains a compound information query from the traditional Chinese medicine systems pharmacology database and analysis platform  showed that the OPLS statistical model did not overfit . These important difference ions were considered potential biomarkers, combining MS and MS/MS structural information with HMDB and KEGG biological function analysis, including betaine, N2-succinyl-L-ornithine, phenyl pyruvic acid, pyruvic acid, and taurine. Finally, 29 potential biomarkers were found to be closely related to AIA  metabolic pathway enrichment analysis to reveal the mechanism of the metabolic differences in the rats after receiving CFA injections. The results showed that these biomarkers were involved in multiple metabolic pathways, such as taurine and hypotaurine metabolism, starch and sucrose metabolism, alpha-linolenic acid metabolism, phenylalanine metabolism, and glycolysis or gluconeogenesis, which together lead to the development of inflammatory pathological conditions  KEGG pathway analysis, and it was found that palbinone, paeoniflorin, mairin, beta-sitosterol, sitosterol, kaempferol, and (+)-catechin in B can regulate 47 targets and then act on the TNF signaling pathway, HIF-1 signaling pathway, IL-17 signaling pathway, MAPK signaling pathway, RA, and other pathways related to inflammation -catechin can bind to the corresponding targets in different numbers, and they are sorted according to the degree unDir of binding from high to low as kaempferol, beta- sitosterol, (+)-catechin, paeoniflorin, mairin, sitosterol, and palbinone.The chronic etiology of the AIA rat model is comparable to the clinical manifestations of RA, making it a classic and popular choice for pharmacological research and experimental evaluation. Synovitis and cartilage degeneration eventually develop from the initial inflammation ,19. Althp < 0.05 were found  reports  have beeThis study examined the anti-RA effects of B and investigated the metabolic processes in experimental rats with MS. B inhibited CFA-induced claw swelling in rats with RA and alleviated the pathological conditions of the spleen and thymus. The model rat’s disordered metabolism, which included histidine metabolism, phenylalanine metabolism, arginine and proline metabolism, and pyrimidine metabolism, was corrected after 28 days of continuous administration. Paeoniflorin, palbinone, beta-sitosterol, kaempferol, and catechin may be important components. In sum, this research focused on the experimental data of B’s drug development and screening projects and conducted preliminary pharmacodynamic and pharmacological studies on B.


ZhiKe GanCao Decoction (ZKGCD) is a commonly used traditional Chinese medicine in the clinical treatment of intervertebral disc degeneration (IDD). However, its active ingredients and mechanism of action remain unclear. This study aims to propose the systematic mechanism of ZKGCD action on IDD based on network pharmacology, molecular docking, and enrichment analysis.  Firstly, the common target genes between ZKGCD and IDD were identified through relevant databases. Secondly, the protein-protein interaction (PPI) network of common genes was constructed and further analyzed to determine the core active ingredients and key genes. Thirdly, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of common genes were performed. Finally, the stability of the binding between core active ingredients and key genes was verified by molecular docking analysis.  “Intersecting genes-active components” network consists of 154 active ingredients and 133 common genes. The ten key genes are AKT1, TNF, IL6, TP53, IL1B, JUN, CASP3, STAT3, MMP9, and MAPK3. Meanwhile, quercetin (Mol000098), luteolin (Mol000006), and kaempferol (Mol000422) are the most important core active ingredients. The main signal pathways selected by KEGG enrichment analysis includes AGE-RAGE signaling pathway in diabetic complications (hsa04933), TNF signaling pathway (hsa04668), IL-17 signaling pathway (hsa04657), cellular senescence (hsa04218), apoptosis (hsa04210), and PI3K-Akt signaling pathway (hsa04151), which are mainly involved in inflammation, apoptosis, senescence, and autophagy.  This study provides a basis for further elucidating the mechanism of action of ZKGCD in the treatment of IDD and offers a new perspective on the conversion of the active ingredient in ZKGCD into new drugs for treating IDD. Low back pain (LBP) is one of the most common global health problems, and it has been younger in recent years . AccordiTraditional Chinese medicine (TCM) has been used for thousands of years in Eastern countries and is widely used to treat various diseases , 10. In The emergence of network pharmacology presents a new opportunity. Recent studies have confirmed that network pharmacology has good predictive performance in the study of different drug-disease interactions –19. NetwThis study aimed to explore the main active ingredients, potential targets, and signaling pathways of ZKGCD for the treatment of IDD based on the network pharmacology approach and to provide theoretical support for clinical practice. In addition, the reliability of the results was further confirmed by molecular docking. https://tcmsp-e.com/) [https://go.drugbank.com/) [https://www.UniProt.org) [The formula of this study is ZKGCD, which contains seven herbs: Aurantii Fructus (Pinyin: ZhiKe (ZK)), Licorice (Pinyin: GanCao (GC)), Angelicae Sinensis Radix (Pinyin: DangGui (DG)), Radix salvia (DanShen (DS)), sparganii rhizome (Pinyin: SanLeng (SL)), curcumae rhizome (Ezhu(EZ)), semen pharbitidis (Pinyin: QianNiuZi (QNZ)). We used the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database (-e.com/)  to selecnk.com/)  and UniProt.org) .https://omim.org/) [https://www.genecards.org/) [http://ctdbase.org/) [https://go.drugbank.com/) [https://www.disgenet.org/) [We integrated a total of 5 databases of target genes for IDD, namely Online Mendelian Inheritance in Man (OMIM) (im.org/) , GeneCards.org/) , Comparase.org/) , DrugBannk.com/) , and Diset.org/) . FinallyThe intersection gene set was obtained based on the above two gene sets by constructing Venn diagrams, which are potential target genes for ZKGCD treatment of IDD.https://www.string-db.org/) [Homo sapiens and 0.4 moderate confidence for filter conditions. At the same time, the TSV file was obtained. Finally, the obtained TSV file was imported into Cytoscape software to visualize the PPI network of intersected genes, and the PPI network was analyzed by MCODE and CytoHubba plugin in Cytoscape to acquire clusters and key genes with 12 kinds of topological measures.In this study, we used Cytoscape software  to constdb.org/)  with HomR software to perform enrichment analysis for the intersection gene set, mainly including gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis [To further clarify the potential specific mechanism of the ZKGCD treatment IDD, we used the clusterProfiler package of analysis . On the https://www.rcsb.org/) and PubChem database (https://pubchem.ncbi.nlm.nih.gov/), respectively. And then, they were preprocessed by PyMol 2.4.0 and ChenBio3D software. Finally, we used AutoDock Vina to calculate the binding energy based on the hydrogenation reaction of proteins and small-molecule ligands.In this study, we mainly used molecular docking analysis to clarify whether there is a good stability between our selected key genes and the corresponding active ingredients. The stereo structures of key genes and active ingredients  were downloaded from the RCSB PDB database . Among them, 5 active ingredients were derived from ZK, 92 from GC, 2 from DG, 65 from DS, 5 from SL, 3 from EZ, and 22 from QNZ (Supplementary http://bioinformatics.psb.ugent.be/webtools/Venn/) and obtained the intersection gene set containing 133 drug-disease targets, which are potential target genes of ZKGCD treatment for IDD , TNF signaling pathway (hsa04668), IL-17 signaling pathway (hsa04657), cellular senescence (hsa04218), apoptosis (hsa04210), and PI3K-Akt signaling pathway (hsa04151) . ParticuP values . DetaileBinding energy is considered to be one of the key indicators to verify the stability of the conformation of the bound protein and active ingredient. At the same time, the stability of the conception increases as the binding energy decreases. For this reason, we performed molecular docking analysis on 10 key genes and the top 3 bioactive components, and the results are shown in With the increasing intensity of modern work, the incidence of IDD is increasing. Currently, the generally recognized mechanisms of IDD may be related to the enrichment of inflammatory factors, senescence, and apoptosis of nucleus pulposus cells (NPC) and degradation of extracellular matrix (ECM). However, there is a lack of effective noninvasive treatment for IDD before it progresses to surgery. Single NSAIDs are mainly used to relieve painful symptoms, but it is accompanied by a series of side effects. Since herbs taken from nature have no or very few side effects, it has been used as a supplement to western medicine. ZKGCD, a traditional Chinese medicine compound, has been used to treat musculoskeletal diseases. However, the specific therapeutic mechanism of ZKGCD is not clear, which limited the application of ZKGCD in clinical practice. This study used network pharmacology theories, molecular docking techniques, high-throughput data analysis, and a series of related tools to visualize the specific relationships among drug active ingredients, key targets, important signaling pathways, and disease.κB axis [In this study, a total of 154 active ingredients were selected, among which quercetin (Mol000098), luteolin Mol000006), and kaempferol (Mol000422) were identified as the core active ingredients. Quercetin is one of the main active components of licorice, which is a natural flavonoid with antioxidant and anti-inflammatory effects and widely exists in various plants. Several studies have shown that quercetin can delay IDD progression through multiple signaling pathways, mainly including (1) quercetin can prevent IDD by regulating p38 MAPK-mediated autophagy ; (2) queκB axis . LuteoliκB axis . In addiκB axis . The maj, and kaeκB axis –38.According to the ten key targets selected by the PPI network and topology algorithm, and the results of GO function enrichment and KEGG pathway enrichment analysis, the final results all mainly focused on the regulation of inflammatory response, oxidative stress response, reactive oxygen metabolism, and apoptotic signaling pathway. AKT1 is a serine/threonine protein kinase involved in a variety of biological processes. AKT activation depends on the PI3K pathway. Furthermore, studies have confirmed that the pathogenesis of disc lesions may be related to end-plate sclerosis, increased oxidative stress, and AGE/RAGE-mediated interactions. TNF and IL6, as typical inflammatory factors, are associated with our selected core active components and potential mechanisms  that are complementary to each other. The enrichment results also suggested that two pathways, including cellular senescence and apoptosis, may play a very important role in the treatment of IDD. On the one hand, senescence of NPC is a key factor in IDD, and delaying NPC senescence may be beneficial for alleviating IDD , 40. On In conclusion, this study systematically elucidated the potential mechanisms of ZKGCD for the treatment of IDD based on a network pharmacology approach, molecular docking technique, and GO and KEGG enrichment analysis. The results indicated that quercetin (Mol000098), luteolin (Mol000006), and kaempferol (Mol000422) were the main bioactive components, which may alleviate the occurrence and development of IDD through the AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, IL-17 signaling pathway, cellular senescence, apoptosis, and PI3K-Akt signaling pathway. This study demonstrated the characteristics of multicomponent, multitarget, and multipathway of ZKGCD and provided potential targets and a basis for the development of new drugs and experimental studies for the subsequent treatment of IDD.