Akt Pathway represented with 13 branches, the Chromatin Pathway and the DDR Pathways dominated. After eHx, the ATM main pathway and two of its branches  dominated, as well as the Hypoxia Pathways. Further, 14 ISPs demonstrated a strong inverse regulation, with the Hedgehog and the Brca1 Main Pathways as chief activators after nHx, and the ATM Pathway(G2_M Checkpoint Arrest) as the dominating constraining response after eHx.Despite numerous studies addressing normal liver regeneration, we still lack comprehensive understanding of the biological processes underlying failed liver regeneration. Therefore, we analyzed the activity of 271 intracellular signaling pathways (ISPs) by genome wide profiling of differentially expressed RNAs in murine liver tissue biopsies after normal hepatectomy  and extended hepatectomy . Comprehensive, genome-wide transcriptome profiling using RNAseq was performed in liver tissue obtained from mice  harvested 1, 8, 16, 32, and 48 h after operation (n = 3 per group) and the OncoFinder toolkit was used for an unsupervised, unbiased identification of intracellular signaling pathways (ISP) activity. We observed that the normal regenerative process requires a transient activation and silencing of approximately two dozen of ISPs. After nHx, the  The liver has the exceptional ability to regenerate after injury or surgical resection of tissue. It is widely recognized that this regenerating process is governed by an intricate interplay of hundreds of genes, which together form dozens of interwoven networks of signaling pathways. These pathways regulate biological processes, such as cell cycle arrest, cell cycle progression, apoptosis, inflammation, angiogenesis, etc. The entire process of liver regeneration is broadly defined by three distinct phases: an initiation phase, a proliferation phase, and a termination phase. Traditionally, it is thought that during the initiation phase, key signaling pathways induced by TNF-α and IL-6 drive cell proliferation in several hepatic cell types . Then, gLimits to physiological liver regeneration are experienced in the clinic. Following extended hepatectomy that leaves behind a marginal liver remnant, liver failure may develop, a syndrome known as the small-for-size syndrome (SFSS). The SFSS is typified by metabolic liver dysfunction and represents the most frequent cause of postoperative death due to liver surgery . ExtendeWith the development of reliable surgical mouse models, which reflect normal and extended liver hepatectomy in humans, and the advent of appropriate bioinformatics tools to analyze genome wide gene expression profiling, comprehensive categorization has now become feasible. To identify the intracellular signaling pathways (ISP) involved in normal and extended liver regeneration, we applied the OncoFinder algorithm for the functional annotation of the primary next generation sequencing genome-wide expression data. The advantage of OncoFinder over alternative tools, such as Metacore and Ingenuity Pathway Analysis (IPA), is that it calculates the pathway activation strength (PAS), so that differences between the two surgical procedures can be quantified ,6.Here, we analyzed the expression profiles of >20,000 genes and determined how they interact together in 271 IPA-defined intracellular signaling pathways. Our analyses of more than 12 million data points demonstrate that liver regeneration is a highly orchestrated flowing process, in which many signaling pathways operate simultaneously, either additively or inversely. We also show that the distinct stages of normal and failed regeneration are clearly discernable by a discrete activation and deactivation of a small number of signaling pathways. The five time points we studies in our nHx and eHx models were clearly demarcated by only a limited number of pathways, which may reflect normal and abnormal regeneration processes—the latter leading to liver failure and/or delayed regeneration.All animal experiments were performed in accordance with Swiss Federal Animal Regulations and approved by the Veterinary Office of Zurich. Animals aged 10–12 weeks were kept on a 12-h day/night cycle with free access to food and water. C57Bl/6 mice were obtained from Harlan .Animal surgery was performed as described by our team . In shorTo study uncompromised liver regeneration, normal hepatectomy (68%) was performed, whereas extended hepatectomy (86%) was completed to induce experimental SFSS. Following 68% hepatectomy, injury is negligible, with ALT <100 U/L 1 day post-operation and serum bilirubin not elevated. After 86% hepatectomy, liver starts to gain weight very slowly, if at all, with its strongest gains toward 48 h. This time point coincides with the hepatocellular mitotic peak, which follows cell cycle entry around 16–20 h post 68% hepatectomy [p-value ≤ 0.05). Venn diagrams were constructed using Venny 2.1 (http://bioinfogp.cnb.csic.es/tools/venny/). All data were deposited to the European Nucleotide Archive Total liver RNA was prepared by DNA Column Clean-up  and purified, enriched, and fragmented following the protocol of Illumina TruSeq . RNA deeFor the functional annotation of the primary gene expression data, we applied our original algorithm termed OncoFinder ,8. It enp < 0.05), and second, the value of CNR must differ from 1 considerably, thus being inferior of 0.66 or exceeding 1.5. The discrete value of ARR (activator/repressor role) reflects the functional role of a protein n in the pathway [Here, the case-to-normal ratio (CNRn) is the ratio of expression levels for a gene n in the sample under investigation to the same average value for the control group of samples. The Boolean flag of BTIF  equals to one for genes with significantly altered expression, and to zero for non-significantly affected genes. The applied significance criteria were as follows: differential gene had to meet simultaneously the two conditions, first, gene expression level for the sample must lie outside the tolerance interval p < 0.0, and sec pathway .https://www.qiagen.com/us/shop/genes-and-pathways/pathway-central/), which were used for OncoFinder, as described previously [The intracellular signaling pathways (ISPs) knowledge base developed by SABiosciences was used to determine structures of ISPs  for each pathway of the entire group of samples were calculated using Wilcoxon rank-sum test and Benjamin-Hochberg method, respectively. Principal component analyses were performed using MADE4 package . HierarcFocusing on differentially expressed pre-miRNAs present in our datasets, we predicted their putative mRNA targets considering only experimentally validated miRNA–mRNA interactions using the Ingenuity Pathway Analysis (IPA) suite , which specifically uses TarBase , miRecor2FC = 1|; p-value ≤ 0.05), i.e., genes that are uniquely expressed after either nHx or eHx. As demonstrated in Differential expression analyses revealed a total of 11,546 differentially expressed candidate genes  12,000 protein without strong homology to any previously reported proteins and expressed ubiquitously in all normal tissues [After both nHx and eHx, we observed a distinctive and sequential activation of unique candidate genes, with only a minor overlap of genes over time C,D. We d tissues . To put  tissues ,8.The normalized gene expression levels of our experimental groups were processed using the OncoFinder algorithm to calculate individual regulatory pathway activation strengths (PAS) profiles of 271 ISPs ,8. The Pincreased activities of which the major part  overlapped, the latter indicating common intracellular activities. In the nHx group, one unique ISP was activated  pathways displayed ocedures , p15–20.ocedures . In additivities . Of thosdiminished activities. Of those, only one ISP was exclusively down after nHx, whereas three were distinctively lower after the extended procedure  ISPs presented with augmented activities , p20–25.rocedure . Taken trocedure , whereasrocedure C.ATM Pathway (G2_M checkpoint arrest) and the CD40 Pathway (cytokine expression) are markedly silenced , whereas the Circadian Main Pathway is activated (PAS: 0.119250412). After 32 h, normal liver regeneration is predominantly dictated by the activation of the Hedgehog Main Pathway (PAS=0.261337874) and the BRCA1 Main Pathway (PAS: 0.292340978). The ATM Pathway (G2_M checkpoint arrest) is the most silenced pathway 48 h after surgery (PAS = −0.651298809). During the early phase after extended hepatectomy, the Cytokine Main Pathway, the ErbB Family Main Pathway, and the Mitochondrial Apoptosis Pathway are the most activated ISPs , followed by the IL10 Pathway 16 h after surgery (PAS = 0.109013662). In contrast to nHx, the Hedgehog Main Pathway is markedly silenced (PAS = −0.141280757). Likewise, 48 h after eHx, the ATM Pathway (G2_M checkpoint arrest) is most significantly activated (PAS=0.282117965), as well as the cAMP Pathway (Cytokine Production) and the p53 Signaling (Negative) Main Pathways .Additional ISPs, which may potentially determine the outcome of liver regeneration, are those that are inversely regulated after the two surgical procedures. These pathways are activated after 68% hepatectomy and silenced after 86%, or vice versa. We identified a total of 33 common pathways with opposite signs for the calculated PAS values , p29–34.ATM Pathway and the p53 Main Pathway showed clear positive PAS values, also peaking at 32 h , a pathology characterized by hyper-bilirubinemia, diminished (or failed) liver function, and, as such, is the most frequent cause of death due to liver surgery. Earlier, we demonstrated that p21 activation mediates a transient barrier to the progression and completion of the cell cycle, thereby inhibiting liver regeneration and deteriorating survival . To compHow all the liver-expressed genes interact together and affect biological relevant processes was studied using OncoFinder, software designed to quantify pathway activation strengths according to gene expression levels ,8. We obHedgehog Pathway -6, and IL-1 by activated macrophages [cAMP Pathway. In the liver, cAMP-responsive signaling plays an important role, particularly in regulating hepatocyte proliferation as observed after nHx [A closer look at the identified ISPs revealed that both procedures recruit pathways that traditionally have been linked to liver regeneration. The most pronounced common pathways activated after both nHx and eHx include the  Pathway A-1 and fansition A-2. In arophages . The mosfter nHx . In addifter nHx . Most PAfter nHx ,8. More nHx, the Akt Pathway represented with 13 branches, the Chromatin Pathway and the DDR Pathway—with 3 branches each—dominated  detected after extended hepatectomy  dominated. Both pathways may be induced by severe (DNA) damage inflicted by extended hepatectomy, dramatically increased blood pressure, or both, which retain the cells in the G2 phase. In addition, five branches of the HIF1-Alpha Main Pathway  prevailed. These pathways, which are closely associated with the VEGF Main Pathway, may reflect the immediate early hypoxic conditions after extended liver hepatectomy. Both nHx and eHx rapidly induced hypoxia-associated ISPs, an observation, which may reflect the overshoot of oxygen-poor blood delivered from the portal vein, and probably required for the early phase of liver regeneration through Hif2a [Among the unique ISPs activated after extended hepatectomy, the gh Hif2a . Interesgh Hif2a . Indeed,gh Hif2a .ATM Pathway (G2_M checkpoint arrest) is of particular interest. Earlier, we observed that liver dysfunction after eHx resulted from a deficiency in cell cycle progression caused by a transient activation of p21 just before hepatocyte division, rather than from parenchymal injury [ATM Pathway (G2_M checkpoint arrest) with p53 and p21 as dominant cell cycle checkpoints, to be the most differentially activated pathway—thus confirming our earlier data. Therefore, a deficiency in cell-cycle progression after extended hepatectomy and concomitant liver failure might be overcome by counteracting this pathway. Our data suggest this can be achieved by stimulation of the Akt-associated pathways, which are explicitly activated early after nHx but not after eHx, and interfere with the ATM pathway at the level of p53, the activator of p21. The pre-miRNA identified in the eHx samples also indicated a strong reciprocal regulation of these pathways. Our comprehensive ISP analyses thus reveals potential intervention points to treat failed liver regeneration.Fourteen ISPs demonstrated a strong inverse regulation after nHx and eHx (l injury . OncofinJNK Pathway, the NF-κB, and the ERK Pathway—and the ATM Pathway via the p53-p21 axis (CD40-, the BRCA1, and the Ubiquitin-Proteasome Pathways are unexpectedly involved in the normal regeneration process, whereas the IL10-, the cAMP-, and the ATM Pathways are defining the ceased regeneration process. The importance of miRNAs governing the molecular principles underlying liver regeneration should also be envisaged. Liver-specific signaling networks are tightly controlled by miRNAs that regulate key hepatic functions during liver injury and disease. Several miRNA affect hepatocyte proliferation, including miR-21, miR-29a, and miR-382, which target genes at important signaling crossroads, such as the crucial PI3K/AKT-signaling mediator PTEN [Taken together, a timely—but transiently—activation and silencing of approximately two dozen of ISPs warrant a normal regenerative process, culminating in full recovery of small liver remnants. The most affected ISPs are revolving around Akt-mediated signaling—which is tightly associated with several pathways, including the p21 axis B. Togethp21 axis  after 86tor PTEN . Still, Our analyses recapitulated current knowledge on liver regeneration processes by retrieving the Hedgehog-pathway the Hypoxia-pathways, and unveiled several novel p21-connected networks not earlier associated with liver regeneration. Overall, nHx is associated with an early silencing and a late activation of a very distinct set of ISPs, whereas an early activation and late silencing of its own specific assortment of ISPs characterize eHx.


In recent years, with the increasing awareness of health concerns and environment protection needs, there is a growing interest for consumers to choose plant-based food diets compared with those made from animal origin. Pumpkin seed is an excellent dietary source for protein, oil, and some essential micronutrients. Raw pumpkin seed may have a compromised flavor, color, as well as digestibility. Therefore, the objective of present study is to study the influence of roasting  on the phenolics content, flavonoids content, antioxidant property, fatty acids, and volatile matter composition, as well as protein profile of pumpkin seeds. Our results indicated that, total phenolic compounds, total flavonoids content, as a consequence, total antioxidant capacity increased as the roasting temperature increased. Maillard reaction products and lipid peroxidation products were identified, especially from those pumpkin seeds roasted at high temperature. In the meantime, the composition and content of fatty acids did not change significantly after roasting. The results of electrophoresis and particle size analysis showed that the optimum roasting temperature was 160°C to obtain protein with better nutritional quality. The findings of this study may contribute to the utilization of pumpkin seed component in plant-based diets with increased nutritional quality. C. pepo, C. moschata, C. mixta, C. maxima, and C. stilbo  seeds and hulls have been investigated and it indicated that p-hydroxybenzoic acid was the dominant phenolic acids in the hull-less seeds with green skin. Besides, there are also caffeic, ferulic, and vanillic acids  on the phenolics content, flavonoids content, antioxidant property, fatty acids, and volatile matter composition, as well as protein profile of pumpkin seeds. The findings of this study may contribute to understand the relationship between roasting and nutritional quality of pumpkin seed, as well as the utilization of pumpkin seed component in plant-based diets.Cucurbita pepo L.) were provided by Haichuansanxin Food Company . They were kept in vacuum pouches at −4°C for subsequent research. The nutritional composition of the used pumpkin seeds was 34.25% proteins, 46.15% fats, 4.39% moisture, 4.52% ash, and 3.01% carbohydrates. Methanol HPLC grade, 2,2-diphenyl-1-picrylhydrazyl (DPPH) aluminum chloride, gallic acid and rutin, p-hydroxybenzoic, epicatechin, caffeic, p-coumaric, ferulic were purchased from Sinopharm Chemical Reagent Co., Ltd. . All other reagents were analytical grade and obtained from Chemical Reagent Co., Ltd. .Pumpkin seeds . Both raw pumpkin seeds and roasted ones were grounded into flours using a YF-1000 blender . The flours were then passed through a 60-mesh screen and stored in a −80°C freezer for further use.The phenolic compounds in roasted pumpkin seed flours were extracted in reference to the method of Bhinder . MethanoFolin-Ciocalteu (FC) method was used to measure the total phenol content of pumpkin seeds according to method published by Saavedra et al.  with somThe concentrations of flavonoids in pumpkin seeds were determined by sodium nitrite-aluminum chloride complexation spectrophotometry following the procedure reported by Shen et al. . The absDPPH free radical assay was used to evaluate the antioxidant activity following by the method of Sánchez-Moreno et al. . The absPhenolic acids were determined with Agilent 1100 HPLC equipped with an autosampler , UV-visible detector at 280 nm, C18 column . Mobile phases A and B were 1% acetic acid and chromatographic methanol, respectively. The gradient elution procedure was as follows: from 0 to 10 min, 80% A; from 10 to 25 min, 80–60% A; from 25 to 35 min, 50% A; from 35 to 40 min, 50–30% A; from 40 to 45 min, 90% A. Phenolic acids were identified by comparing the retention times of mixed standard chromatogram and the relative content were calculated through a normalization procedure.The composition of fatty acids in pumpkin seeds were measured according to the method of Zhang et al.  using a The composition of volatile matters was investigated using Pegasus BT gas chromatography time of flight mass spectrometer . The followings are the chromatographic conditions of GC-MS. The initial DB-FFAP (30 m × 0.25 mm × 0.25 μm) column temperature was 50°C, holding for 2 min, then increased to 150 at 3°C/min, holding for 1 min and increased to 250 at 5°C/min. The injection port and the ion source temperature were both 250°C. Electron impact ion was used (70 eV) to scan a mass ranging from 33 to 450 amu. According to the area normalization method, the contents of volatile compounds were expressed as relative percentages. The volatile compounds were identified by computer and matched with NSIT and Wiley Library. The relative percentage content was calculated by peak area normalization.Pumpkin seed protein was extracted by alkali dissolution and acid precipitation method . The pumThe protein components of roasted pumpkin seeds were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The concentration of electrophoresis gel was 12.5% and that of concentrated gel was 4%. The pumpkin seed protein dissolved in the pH 7.0 phosphate buffer solution whose content was 5 mg/mL determined by microplate was mixed with the sample buffer  at the volume ratio of 4:1. The mixed sample was soaked in boiling water for 10 min and was loaded (10 μL). The gels run at the voltage of 120 V with Tris-Glycine buffer . After electrophoresis, the SDS-PAGE gel was stained with Coomassie brilliant blue G-250 for 2 h, and compare with a protein maker by ChemiDocXRS+ gel imaging analysis system  after decolorization. The protein marker purchased from Epizyme Biotechnology Co., Ltd  consists of 11 protein bands ranging from 10 to 250 kDa.The particle size of pumpkin seed protein in pure water (1 mg/mL) was measured after 0 h and 4 h using Nano Brook Omni particle size and zeta potential analyser  to analyse the stability of the protein from pumpkin seed roast at different temperatures.p < 0.05 were considered significantly different.The assay results were expressed as average value ± standard deviation of three replicates. Comparisons among the pumpkin seeds from each treatment were performed by ANOVA using IBM SPSS Statistics 26.0. Results with Cucurbita pepo determined by Peiretti et al. . Therefore, the increase of total phenol content is one of the reasons for the enhancement of antioxidant capacity of roasted pumpkin seeds. Otherwise, the generation of Maillard reaction greatly improves the antioxidant properties. Jogihalli et al. (S) are considered to have the ability of chelating metals and scavenging oxygen free radicals (Similarly, a higher increase was discovered in antioxidant of pumpkin seeds . The anti et al.  considerradicals –32. Noosradicals  also fouThe liquid chromatogram of mixed standards samples and the relative percentage of different phenolic acids in roasted pumpkin seeds are revealed in As shown in the A number of volatile compounds could be identified in roasted seeds, including heterocyclic compounds, aldehydes, ketones, alcohols, acids, esters, and sulfur compounds. Twenty-nine volatile matters with higher relative concentration in roasted pumpkin seeds were listed in The following pyrazines were identified in the roasted pumpkin seeds: pyrazine, 2-methylpyrazine, 2-ethylpyrazine, 2,5-dimethylpyrazine, 2,6-dimethylpyrazine, 2,3-dimethylpyrazine, 2-ethyl-5-methylpyrazine, 3-ethyl-2,5-dimethylpyrazine, and 2,3,5-trimethylpyrazine. It can be seen from the table that the concentration of pyrazines in the pumpkin seeds increase significantly with the increase of temperature. They have been reported as typical Maillard reaction products and the pyrazines were considered to be the important factor of the characteristic aroma of pumpkin seeds oil , 42. In There were two main aldehydes in the headspace of the pumpkin seeds. Benzaldehyde is considered to be the degradation product of amino acid phenylalanine ; hexanalAs shown in After 4 h, the particle size of each pumpkin seed solution increased , which sIn conclusion, roasting at certain temperature can increase the sensory and nutritional attributes of pumpkin seed. After roasting, the concentrations of total phenols, total flavonoids, and antioxidant properties of pumpkin seeds were improved, which indicated that roasting enhanced the biological activity and antioxidant properties of pumpkin seeds. A large number of pyrazine compounds were produced in roasted pumpkin seeds, contributing to strong roasted food aroma. The main fatty acids components of pumpkin seeds were C16:0, C18:0, C18:1, and C18:2 and roasting temperature has no apparent influence on concentrations of saturated and unsaturated fatty acids. Although the properties of pumpkin seed protein increased after roasting, the result of protein electrophoresis and particle size showed that 160°C was better than 200°C. In addition, the effect of roasting on the structure and functionality of pumpkin seed protein needs to be further confirmed. A detailed understanding between structure change after roasting and functionality of protein will enable researchers to develop pumpkin seed protein-based food products for different purposes.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.MP: conceptualization, investigation, methodology, software, data curation, writing – original draft, and writing – review and editing. DL: investigation. BJ: formal analysis, investigation, and writing – review and editing. JC: project administration, funding acquisition, and writing – review and editing. All authors: contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Background: Glaucoma is a leading cause of irreversible blindness. Remodeling of the scleral extracellular matrix (ECM) plays an important role in the development of glaucoma. The aim of this study was to identify the key genes and pathways for the ECM remodeling of sclera in glaucoma by bioinformatics analysis and to explore potential therapeutic agents for glaucoma management.Methods: Genes associated with glaucoma, sclera and ECM remodeling were detected using the text mining tool pubmed2ensembl, and assigned Gene Ontology (GO) biological process terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using the GeneCodis program. A protein-protein interaction (PPI) network was constructed by STRING and visualized in Cytoscape, module analysis was performed using the Molecular Complex Detection (MCODE) plugin, and GO and KEGG analyses of the gene modules were performed using the Database of Annotation, Visualization and Integrated Discovery (DAVID) platform. The genes that clustered in the significant module were selected as core genes, and functions and pathways of the core genes were visualized using ClueGO and CluePedia. Lastly, the drug-gene interaction database was used to explore drug-gene interactions of the core genes to find drug candidates for glaucoma.Results: We identified 125 genes common to “Glaucoma”, “Sclera”, and “ECM remodeling” by text mining. Gene functional enrichment analysis yielded 30 enriched GO terms and 20 associated KEGG pathways. A PPI network that included 60 nodes with 249 edges was constructed, and three gene modules were obtained using the MCODE. We selected 13 genes that clustered in module 1 as core candidate genes that were associated mainly with ECM degradation and cell proliferation and division. The HIF-1 signaling pathway, FOXO signaling pathway, PI3K-Akt signaling pathway and TGFB signaling pathway were found to be enriched. We found that 11 of the 13 selected genes could be targeted by 26 existing drugs.Conclusions: The results showed that VEGFA, TGFB1, TGFB2, TGFB3, IGF2, IGF1, EGF, FN1, KNG1, TIMP1, SERPINE1, THBS1, and VWF were potential key genes involved to scleral ECM remodeling. Furthermore, 26 drugs were identified as potential therapeutic agents for glaucoma treatment and management. Glaucoma is a progressive optic neuropathy characterized by progressive degeneration of retinal ganglion cells and optic nerve head (ONH) axons Currently, lowering of intraocular pressure (IOP)  is the only available option to delay the development and progression of glaucoma Retinal ganglion cell axons converge at the ONH, pass through the laminar cribrosa, enter the scleral canal and exit the eye in vivo experiment, mice with microfibril deficiency were shown to have increased susceptibility to glaucomatous damage Stiffening of the sclera leading to scleral rigidity is one of the primary structural changes in glaucoma The discovery of new drug therapies using conventional approaches can be time-consuming and costly, whereas repurposing an existing drug to treat a condition beyond its original intent may be a more effective and less expensive alternative http://pubmed2ensembl.ls.manchester.ac.uk/), a publicly available resource that links over 2,000,000 articles in PubMed to nearly 150,000 genes from 50 species in Ensembl Homo sapiens (GRCh37)” was selected as the species dataset and “filter on MEDLINE: PubMed ID” was set to constrain the query result. The unduplicated genes were extracted and the intersection of gene hits from the three gene sets was retrieved as the text mining genes (TMGs).Text mining was performed using pubmed2ensembl (http://genecodis.cnb.csic.es/) to perform an enrichment analysis of the TMGs related to scleral ECM remodeling in glaucoma. GeneCodis is a web‑based server for functional analysis of gene lists that integrates different sources of information We used GeneCodis (https://string-db.org/cgi/input.pl) is an online database resource that covers approximately 24.6 million proteins and more than 3.1 billion interactions originating from 5090 organisms The Search Tool for the Retrieval of Interacting Genes , an online tool for gene functional analysis http://www.geneontology.org) database contains terms for the functional classification for genomic data under three main categories: biological processes, cellular component, and molecular function http://www.genome.ad.jp/kegg/) is a knowledge base for systematic analysis, annotation, and visualization of gene functions The GO functional and KEGG pathway enrichment analyses of significant module genes were performed using Database for Annotation, Visualization and Integrated Discovery (DAVID)  is a web resource that consolidates disparate data sources that describe drug-gene interactions and gene druggability Using the text mining strategy described in the methods section Figure , we obtaThe GO biological process terms and KEGG pathway enrichment analyses using GeneCodis (with P=1.00E-07 as the cutoff) to identified the most enriched terms closely related to the pathology of scleral ECM remodeling in glaucoma. Thirty significantly enriched GO biological process annotations of 97 unique genes were identified. Among them, the five most enriched terms were “extracellular matrix organization” (P=3.47306E-27), “platelet degranulation” (P=2.44362E-19), “cytokine-mediated signaling pathway” (P=3.99419E-18), “response to drug” (P=3.82E-14), and “positive regulation of cell population proliferation” (P=1.45E-13), for 31, 20, 25, 22, and 27 TMGs, respectively Table .The KEGG pathway enrichment analysis identified 20 significant pathways that involved 64 TMGs. The five most significantly enriched pathways were “AGE-RAGE signaling pathway in diabetic complications” (P=1.04E-22), “Proteoglycans in cancer” (P=3.04E-19), “Pathways in cancer” (P=1.88327E-16), “HIF-1 signaling pathway” (P=1.17E-12), and “Relaxin signaling pathway” (P= 1.34E-12), involving 23, 26, 34, 16, and 17 TMGs, respectively Table .A PPI network was constructed for the 64 target genes using STRING with confidence score >0.900. The network had a total of 60 nodes with 249 edges Figure . ModularThe GO enrichment analysis showed that the three modules were related primarily to ECM degrading, cell proliferation and division which play crucial role in scleral ECM remodeling Figure A,C,D. ThTGFB1, TGFB2, TGFB3, VEGFA, IGF2, IGF1, EGF, FN1, KNG1, TIMP1, SERPINE1, THBS1 and VWF, as core candidate genes of the PPI network. The enrichment analysis indicated that these genes were significantly enriched in platelet alpha granule lumen, HIF-1 signaling pathway, and AGE-RAGE signaling pathway in diabetic complication  were predicted to be involved in drug-gene interactions. The primary connection among drugs, genes and pathways are shown in Figure We used the 13 core genes as potential targets in a druggs Table . Eleven Glaucoma is the leading cause of irreversible blindness globally. Reduction of IOP is the only proven method to treat glaucoma TGFB1, TGFB2, TGFB3, VEGFA, IGF2, IGF1, EGF, FN1, KNG1, TIMP1, SERPINE1, THBS1 and VWF, that were involved in the HIF-1 signaling pathway, TGFB signaling pathway, FOXO signaling pathway, and PI3K-Akt signaling pathway.In the present study, we identified 125 genes that might be involved in scleral ECM remodeling associated with glaucoma using text mining strategy , a glycoprotein that functions to bridge platelets with an exposed collagen surface, is associated with the severity of organ fibrosis Transforming growth factor β (TGFB) belongs to a family of fibrogenic cytokine that includes TGFB1, TGFB2 and TGFB3 VEGF-A expression and promote fibrinogenesis via the HIF-1α-VEGF pathway in bronchiolitis obliterans The HIF-1 signaling pathway, one of the enriched KEGG pathways, has been shown to promote scleral myofibroblast transdifferentiation by regulating the actin cytoskeleton pathway, as well as ECM remodeling via the ECM receptor interaction pathway in vivo animal experiments Potential drugs identified by the drug-gene interaction search were classified as mainly TGFB inhibitors, VEGFA inhibitors, IGF inhibitors, fibrinolytic agents, antineoplastic agents, or immunomodulating agents. The TGFB inhibitors were mainly of hyaluronidase, lerdelimumab and fresolimumab. Hyaluronidases are enzymes that regulate the remodeling of ECM. Hyaluronidases have been shown to inhibit the growth of pulmonary fibrosis and decrease TGFB production and collagen deposition in mice VEGFA, including ranibizumab, bevacizumab, aflibercept, carvedilol, dalteparin sodium, phenytoin and vandetanib. Ranibizumab, a monoclonal antibody fragment against VEGF-A, inhibits vascular permeability and has antiproliferative and antimetabolic effects on various cell lines. Several studies have indicated that ranibizumab may prevent scarring after glaucoma filtering surgery through the VEGF pathway More than a quarter of identified drugs target in vivo experiment demonstrated that dusigitumab inhibited tumor growth of mouse embryonic fibroblast EGF and TGFA in gastric mucosal cells THBS1 expression in human thyroid carcinoma FTC-133 cells through the JNK/ATF-2 pathway Dusigitumab is a human antibody of IGF1 and IGF2. An Scleral ECM remodeling also is a key factor in the pathogenesis of myopia. In myopic human eyes, the sclera was found to be thinner, and the scleral ECM was decreased, compared with those in healthy eyes VEGFA, TGFB1, TGFB2, TGFB3, IGF2, IGF1, EGF, FN1, KNG1, TIMP1, SERPINE1, THBS1 and VWF, that may be involved in the scleral ECM remodeling associated with glaucoma. These genes were enriched in the HIF-1 signaling pathway, FOXO signaling pathway, PI3K-Akt signaling pathway and TGFB signaling pathway. We also identified 26 potential drugs that may be help to guide future glaucoma therapies. The absence of experimental validation is a limitation of this study, and further experimental studies are required to verify the results.In conclusion, we identified 13 hub genes, Supplementary tables.Click here for additional data file.


Aldehyde dehydrogenase 1A3 (ALDH1A3) has been implicated in the survival and proliferation of prostate cancer cells.We retrospectively reviewed our patients with advanced disease on adjuvant hormonal therapy after prostatectomy. Time to castration resistance stage was documented. And Immunohistochemistry analysis for ALDH1A3 was performed for those patient samples on tissue microarray. Bioinformatics anslysis was used for RNA sequencing data of both primary prostate cancer and metastatic castration resistance prostate cancer (mCRPC) from online datasets. Crispr-Cas9 was used to knock out ALDH1A3 in prostate cancer luminal cells, and morphologic analysis as well as the Gene Set Enrichment Analysis (GSEA) were facilitated to discover the mechanisms of the resistance phenotype.We found that the patients with ALDH1A3 low expression had shorter time to progression to castration resistance compared with those of higher expression group on adjuvant hormonal therapy after radical prostatectomy. The ALDH1A3 knockout cells gradually acquired resistance to androgen deprivation therapy, a few cells have been found in knockout group showing as that the spindle-like luminal cells in charcoal stripped medium. Furthermore, PI3K pathway activation has been confirmed by Western blot. The PI3K pathway inhibitor BEZ235 has been demonstrated that the acquired ADT resistance by ALDH1A3 down regulation could be rescued by PI3K pathway inhibitor.These results suggested a novel function for ALDH1A3 in development of mCRPC, and indicated PI3K pathway inhibitor has the potential in the treatment of a subgroup of mCRPC patients. Androgen deprivation therapy (ADT) is the standard of care for advanced prostate cancer or progression after localized definitive treatment. However, most patients eventually progress to a condition known as castration-resistant prostate cancer (CRPC), characterized by lack of response to ADT. Despite the several treatment options for this stage of disease, the impact on overall survival is less than optimal and, most importantly, there is no reliable biomarker to predict the response of the treatment or resistance. As a result, no standard guidance is available to optimally sequence approved treatments for individual patients. Since 2005, the next-generation sequencing (NGS) technologies  have madThe aldehyde dehydrogenase family 1 member A3 (ALDH1A3) catalyzes the oxidation of retinal to the pleiotropic factor retinoic acid using nicotinamide adenine dinucleotide (NAD+). The level of ALDHs enzymatic activity has been regarded as a cancer stem cell (CSC) marker and seems to correlate with tumor aggressiveness  which haWe found, surprisingly, that ALDH1A3 was down regulated in metastatic castration resistant prostate cancer from previous sequencing data . CombingThe protocol to generate the tissue microarrays (TMAs) in this cohort has been described in our previous report . We retrThree datasets .The RNA sequencing data were downloaded from SU2C database. The median value of RPKM for ALDH1A3 was used as cut-off value, any sample which is higher than the median value was determined as ALDH1A3escribed . The GenThe human prostate cancer cell line  were purchased from the Cell Bank Type Culture Collection of the Chinese Academy of Sciences  and maintained in RPMI medium with 10% fetal bovine serum within a humidified atmosphere containing 5% CO2 at 37 °C.http://crispr.mit.edu/), targeting the first exon. The sequence of the guide is as follows—ALDH1A3: 1- AGTTATGGCTACCACCAACG; 2-TAGTCTGCGGCGCACCGGCT; green fluorescent protein (GFP): GGCGAGGAGCTGTTCACCG. Then, we ligated the guide to the LentiCrispr-V2 system followed by Sanger sequencing validation [We designed the guide RNA for ALDH1A3 from , Phospho-Akt  and glyceraldehyde 3-phosphate dehydrogenase  were used in Western Blot assay in accordance with the manufacturer’s instructions.p < 0.05 was considered to be statistically significant. All the statistical calculations were performed using GraphPad Prism v6.0 software .Differences in vitro experiment like cell numbers between groups were subjected to Student’s t test. Our earlier work has demonstrated that ALDH1A3 highly expressed in human prostate, which had a strong correlation with primary prostate cancer luminal signature and could be a potential biomarker of AR signaling pathway. Then we moved on to investigate its expression in the castration resistant prostate cancer. We retrospectively reviewed 79 patients with advanced disease who underwent radical prostatectomy followed by adjuvant hormonal therapy in our center. It was indicated that negative expression of ALDH1A3 predicted shorter time progression to castration resistance on adjuvant hormonal therapy . The ALDH1A3 ranking the most significant changes in the whole list confirmed the results. The Gene Set Enrichment Analysis (GSEA) finally correlated ALDH1A3 signature with several biologic event. We found the ALDH1A3 signature had significant positive correlation with ERG signature and prostate cancer luminal signature, respectively   Fig. a, b, andion Fig. c, d.FigBased on the above results, we aimed to investigate the mechanisms of negative expression of ALDH1A3 in mCRPC samples. We designed small guide RNA targeting the functional exon of ALDH1A3 to knock out this gene on cell level to see the phenotype changes. After validation of the knock out efficiency Fig. , we pickBased on the above GSEA results, the ALDH1A3 signature negatively correlated with PI3K-AKT-mTOR signaling pathway. We speculate that the ALDH1A3 loss could activate the PI3K pathway. In order to validate this hypothesis, we did Western blot assay to test the PI3K pathway activation to compare the ALDH1A3 wild type cells and knockout cells. The blotting showed that both in LnCaP and VCaP cells, phospho-AKT had been elevated in ALDH1A3 knockout group Fig. , 5. NextOur previous study has demonstrated that ALDH1A3 is specifically expressed in luminal compartment in human prostate epitheliums. From the TCGA data of 333 primary prostate cancer, ALDH1A3 correlated with AR signaling pathway and corresponding luminal signature. It is also suggested that ALDH1A3 has a potential to be a predictor of survival in primary prostate cancer patients. In present study, with our single center follow up database, we performed IHC analysis on tissue microarray for patients with advanced disease upon adjuvant hormonal therapy after radical prostatectomy. The results showed that ALDH1A3 low-expression patients indicated shorter time to progression to castration resistance. The phenotype that we showed at the beginning has implications to understand the mechanisms of this prostate specific gene in the development of cancer progression. From the metastatic prostate cancer samples database, the RNA sequencing data demonstrated that ALDH1A3 was down regulated in mCRPC group compared with the primary prostate cancer. Next-generation sequencing (NGS) analysis has made it possible to reclassify different subtypes in a specific cancer by molecular changes. It indeed could provide benefits for clinical practice in oncology, such as diagnosis, prognosis, and treatment decisions. For example, patients with cancers of unknown primary (CUP), traditionally, are generally assumed to have a poor prognosis with a treatment in cytotoxic chemotherapy guided by histologic features and the pattern of metastatic spread. A new study showed that NGS may provide an opportunity for CUP patients to benefit from individualized therapies according to the targetable genomic alterations identified by tumor molecular profiling . In thatThanks to the RNA sequencing data, we found that the PI3K pathway signature had been highly correlated with ALDH1A3 signature. Then we speculated the PI3K signaling pathway activation might be due to ADT resistance. And we also confirmed this hypothesis by showing the up-regulation of phospho-AKT upon ALDH1A3 knockout. Furthermore, PI3K signaling pathway inhibitor BEZ235 could rescue the ADT resistance following ALDH1A3 knockout. The PI3K/AKT/mTOR pathway is altered in almost 50% of mCRPC through either PTEN inactivation or/and aberrant activation in PIK3CA/B . It’s beIn conclusion, the NGS provides multiple new opportunities and tools to accelerate and facilitate the entire process of drug testing toward accelerated drug positioning and approval for precise and personalized medicine. It also allows researchers to discover some hidden pattern of the complex cancer. Such strategies include the development of inhibitors with a higher potency against their intended target, like ADT and Abiraterone, and the use of combination therapies incorporating inhibitors of parallel or alternative signaling pathways mediating acquired resistance, like the mTOR inhibitor BEZ235 in the treatment of PI3K-AKT-mTOR pathway activation. In this paper, we’ve investigated alterations in the targeted gene leading to ADT resistance to mCRPC. Based on the RNA sequencing and experimental results, we found that PI3K pathway alteration or activation might be the cause of the resistance. We, then, rescued the ADT resistance by PI3K pathway inhibitor-BEZ235. The acquired resistance to ADT therapy by some patients with low level of ALDH1A3 could be overcome by combination therapy with PI3K pathway inhibitor, which will provide a new potential approach to the treatment of mCRPC.Additional file 1 : Table S1: A differential expression gene list as ALDH1A3 signature.Additional file 2 : Figure S1: Original data of western blot (ALDH1A3) in Fig. ot ALDH1A in Fig. Additional file 3 : Figure S2: Original data of western blot (GAPDH) in Fig. Additional file 4 : Figure S3: Original data of western blot (ALDH1A3) in Fig. Additional file 5 : Figure S4: Original data of western blot (p-AKT) in Fig. Additional file 6 : Figure S5: Original data of western blot (GAPDH) in Fig.


This study aimed to explore the mechanism of Modified Danggui Sini Decoction in the treatment of knee osteoarthritis via a combination of network pharmacology and molecular docking.  The main chemical components and corresponding targets of Modified Danggui Sini Decoction were searched and screened in TCMSP database. The disease targets of knee osteoarthritis were summarized in GeneCards, OMIM, PharmGkb, TTD, and DrugBank databases. The visual interactive network of “drugs-active components-disease targets” was drawn by Cytoscape 3.8.1 software. The protein-protein interaction network was constructed by STRING database. Then, GO function and KEGG pathway enrichment were analyzed by Bioconductor/R, and the pathway of the highest degree of correlation with knee osteoarthritis was selected for specific analysis. Finally, molecular docking was used to screen and verify core genes by AutoDockTools software. κB signaling pathway. It mainly involved inflammatory reaction, regulation of apoptotic signaling pathway, cellular response to regulation of inflammatory response, cellular response to oxidative stress, and other biological processes. The molecular docking results showed that ESR1-wogonin, MAPK1-quercetin, RELA-wogonin, RELA-baicalein, TP53-baicalein, TP53-quercetin, and RELA-quercetin have strong docking activities.  Seventy-one main components of Modified Danggui Sini Decoction and 116 potential therapeutic targets of knee osteoarthritis were selected. The KEGG pathway and the GO function enrichment analysis showed that the targets of Modified Danggui Sini Decoction in the treatment of knee osteoarthritis were mainly concentrated on PI3K-Akt signaling pathway, TNF signaling pathway, IL-17 signaling pathway, apoptosis signaling pathway, Toll-like receptor signaling pathway, Th17 cell differentiation signaling pathway, HIF-1 signaling pathway, and NF- Modified Danggui Sini Decoction has the hierarchical network characteristics of “multicomponent, multitarget, multifunction, and multipathway” in the treatment of knee osteoarthritis. It mainly regulates the proliferation and apoptosis of chondrocytes by regulating the PI3K-Akt signaling pathway and establishes cross-talk with many downstream inflammatory-related pathways to reduce the overall inflammatory response. Meanwhile, HIF-1 expression was used to ensure the normal function and metabolism of knee joint under hypoxia condition, and the above processes play a key role in the treatment of knee osteoarthritis. Knee osteoarthritis (KOA) is a common degenerative bone and joint disease, which is caused by the imbalance of degradation synthesis coupling of chondrocytes, extracellular matrix, and subchondral bone under the action of mechanical and biological factors . Among tModified Danggui Sini Decoction is a classic prescription of Traditional Chinese Medicine (TCM) in treating KOA. It is composed of Danggui nourishing blood and Guizhi warming meridians, which is combined as the monarch medicine. Baishao helps Danggui to nourish blood and harmonize nutrient, and Xixin helps Guizhi to warm and dredge blood vessels. It is supplemented with Tongcao, Niuxi, and Duzhong to invigorate kidney and bone, leading meridians to the affected areas. The whole prescription is used for warming yang and dispersing cold, nourishing blood and unblocking pulse, warming without dryness, tonifying without stagnation, and playing the effect of “warming meridians, dispersing cold, nourishing blood, and unblocking pulse” . PreviouNetwork pharmacology, based on the discipline concept of “multigene, multitarget, and multidisease,” coincides with the medication thinking of TCM and has become a new mode which is suitable for the systematic development of TCM. Based on the network pharmacology, the chemical components of Modified Danggui Sini Decoction were scientifically screened and systematically predicted, and the “drugs-active components-disease targets” interaction network was established. Combined with GO function analysis, KEGG pathway enrichment analysis, and molecular docking technology, the mechanism and scientific connotation of Modified Danggui Sini Decoction in the treatment of KOA were revealed, providing an objective experimental basis for clinical application of TCM treatment of KOA, and providing new ideas and methods for the treatment of orthopedic and traumatology related diseases guided by TCM theory.https://tcmspw.com/) Database [Chinese Pharmacopoeia [Homo sapiens” in UniProt (https://www.uniprot.org/) database.Choose TCMSP  network platform [Homo sapiens,” the highest reliability (score >0.9) was selected by comprehensive scoring, the discrete targets were hidden, the network diagram of protein-protein interaction (PPI) was constructed, and TSV format file was exported. The TSV file was imported into the software of Cytoscape 3.8.1, and the topological analysis was carried out by CytoNCA plug-in. With the values of betweenness, closeness, degree, eigenvector, and local average connectivity-based method and network greater than the median value, the core gene network was obtained.The obtained potential therapeutic targets were imported into the STRING  platform and R language to analyze the GO function and KEGG pathway enrichment of the potential targets for the treatment of KOA. Through the related scripts, the tables of GO function analysis and KEGG pathway enrichment analysis were derived by R language. In GO function analysis, the top 10 items of biological process (BP), cellular component (CC), and molecular function (MF) were selected for visualization. In KEGG pathway enrichment analysis, the top 30 items were selected for visualization. The barplot was used to draw the histogram, and the bubble was used to make the bubble diagram.Go function analysis and KEGG pathway enrichment analysis were performed using Bioconductor (https://www.ncbi.nlm.nih.gov/) platform and converted into the 3D structure by ChemBio3D software, and the energy optimization of MM2 was carried out to complete the preparation of small molecule ligands. The 3D structure of the candidate target proteins was downloaded from PDB (http://www.rcsb.org/) database, and then the protein receptors were prepared after the water molecules and ligands were removed by PyMOL2.4.0 software. Autodocktools software was used to read the receptor files, which were converted to PDBQT format after hydrotreating ion modification. The ligand files were also converted to PDBQT format for saving and then converted into the 2D structure to draw the active pockets. Finally, AutoDock vina software will be used for molecular docking, and the lowest free energy model is selected for visual analysis.The core genes were selected to find the related drug components in the compound regulatory network as small molecular ligands. The 2D structure information of drug chemical components was downloaded from PubChem , and the top 10 items of BP, CC, and MF were selected for visualization , and the top 30 items were listed for visual analysis (Through KEGG pathway enrichment analysis, a total of 150 related signal pathways of Modified Danggui Sini Decoction in the treatment of KOA were obtained (analysis . In the analysis . The redβ-sitosterol were selected as the top active components for molecular docking with Jun, TP53, ESR1, MAPK1, and RELA in turn. The binding energy between drug component ligands and target receptors is an important indicator to evaluate the binding capacity. It is generally considered that the docking affinity is stronger when the binding energy is less than −5.0 kcal/mol, and the docking activity is extremely strong when the binding energy is less than −7.0 kcal/mol [In order to further verify the prediction results of the network, and to elaborate the mechanism and scientific connotation of Modified Danggui Sini Decoction as a classic Chinese medicine prescription in the treatment of KOA, quercetin, kaempferol, wogonin, baicalein, and kcal/mol . From thAs a cultural treasure inherited for thousands of years, TCM has accumulated rich clinical experience, especially in the field of Traditional Chinese Medicine prescriptions. With the advancement of the modernization of Chinese herbal medicine, many studies have applied network pharmacology to explore the pharmacological mechanism of herbal medicine and prescription –19, and The classical compatibility theory of TCM emphasizes that the four parts of monarch, minister, adjuvant, and messenger are combined to achieve synergy and minimize toxic and side effects integrally. Among them, the “messenger” mainly provides the effects of guiding the active ingredients to reach the target organs and harmonizing the actions of these agents , 21. In β-sitosterol. At present, a considerable number of studies have proved that quercetin can significantly inhibit articular chondrocyte apoptosis and delay cartilage degeneration by reducing oxidative stress and endoplasmic reticulum stress, so as to achieve the purpose of treating KOA [β-sitosterol is one of the main components of cell membrane and has an estrogen-like effect. It is known to be effective for hypercholesterolemia, heart disease, immune system regulation, and cancer prevention [In this study, the top five chemical components with the highest degree were quercetin, kaempferol, wogonin, baicalein, and ting KOA –24. In ating KOA . Wogoninting KOA . Baicaleting KOA . β-sitosevention , 29, butβ-sitosterol has the value of research and development in anti-KOA treatment.Therefore, the main active components and efficacy of Modified Danggui Sini Decoction are similar to the results of network pharmacology analysis. Meanwhile, it is speculated that κB signaling pathway. It mainly involves inflammatory reaction, regulation of apoptosis signaling pathway, cell response to chemical stress, cell response to oxidative stress, and other biological processes.KEGG pathway and GO function enrichment analysis showed that the targets of Modified Danggui Sini Decoction in the treatment of KOA mainly concentrated on PI3K-Akt signaling pathway, TNF signaling pathway, IL-17 signaling pathway, apoptosis, Toll-like receptor signaling pathway, Th17 cell differentiation, HIF-1 signaling pathway, and NF-κB, mTOR, and P53 pathways. TNF in the tumor necrosis factor signaling pathway is an inflammatory mediator with many biological effects. TNF-α can induce the production of IL-6 and activate the protease that decomposes cartilage and synovium [κB in its downstream signaling pathway, and induce apoptosis of articular chondrocytes [κB signaling pathway, a variety of upstream signal factors, including TNF, can activate IKK, thus express downstream genes of NF-κB, including MMP-9, P65, and P50, and then produce a cascade of inflammatory reactions and accelerate the decomposition and destruction of articular cartilage [Among them, the PI3K-Akt signaling pathway is an important signal transduction pathway for regulating cell proliferation, differentiation, and apoptosis and promoting related tissue regeneration . Akt cansynovium . Activatdrocytes . As a hydrocytes . In the artilage . In addiartilage . Thus, MAt present, among the many regulatory pathways involved in KOA, the specific mechanism of some signaling pathways is still unclear, and there may be more complex interactions between the pathways, which jointly participate in the proliferation and apoptosis of chondrocytes, as well as the synthesis and degradation of extracellular matrix. Recent studies have found that the PI3K-Akt-mTOR signaling pathway also plays an important role in the pathogenesis of KOA. mTOR, as another serine/threonine protein kinase downstream of PI3K-Akt, is closely related to cell apoptosis, autophagy, cell survival, and structural reorganization , 37.In conclusion, the main active components and efficacy of Modified Danggui Sini Decoction are similar to the results of network pharmacology analysis. Meanwhile, it also points out the direction for the follow-up study on the mechanism of Modified Danggui Sini Decoction in the treatment of KOA. This study is only searched through the databases. It did not take into account the clinical dosage, decocting conditions, and other factors brought by the impact. Thus, the next step requires further experimental verification and clinical research.


Stemazole exerts potent pharmacological effects against neurodegenerative diseases and protective effects in stem cells. However, on the basis of the current understanding, the molecular mechanisms underlying the effects of stemazole in the treatment of Alzheimer’s disease and Parkinson’s disease have not been fully elucidated. In this study, a network pharmacology-based strategy integrating target prediction, network construction, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and molecular docking was adopted to predict the targets of stemazole relevant to the treatment of neurodegenerative diseases and to further explore the involved pharmacological mechanisms. The majority of the predicted targets were highly involved in the mitogen-activated protein kinase (MAPK) signaling pathway. RAC-alpha serine/threonine-protein kinase (AKT1), caspase-3 (CASP3), caspase-8 (CASP8), mitogen-activated protein kinase 8 (MAPK8), and mitogen-activated protein kinase 14 (MAPK14) are the core targets regulated by stemazole and play a central role in its anti-apoptosis effects. This work provides a scientific basis for further elucidating the mechanism underlying the effects of stemazole in the treatment of neurodegenerative diseases. Neurodegenerative diseases, which comprise a type of chronic and progressive disease characterized by progressive degeneration of the structure and function of the nervous system , have beUnfortunately, despite tremendous effort and expenditures, the existing clinical treatments for neurodegenerative diseases result in only temporary and limited symptomatic relief ,8, and tRecently, a novel small molecule with the ability to regulate stem cells has shown potential for the treatment of neurodegenerative diseases. Stemazole (ST) was discovered by a high-throughput screen . We prevThese studies have indicated that stemazole is a promising drug candidate. However, the regulatory mechanism underlying the effects of stemazole against AD and PD has not been systematically elucidated. Studies of the molecular targets and relevant signal pathways will provide a better understanding of the effects of stemazole in the treatment of neurodegenerative diseases.Network pharmacology is an innovative method to study the mechanisms of drugs at the systemic level . It encoUsing the network pharmacology strategy, our study systematically investigated the potential targets and molecular mechanisms underlying the effects of stemazole against neurodegenerative diseases. First, we predicted the molecular targets of stemazole through chemical similarity analysis, pharmacophore model screening, and reverse docking. Pathological targets were identified using various bioinformatics platforms. We then performed enrichment analysis according to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms and constructed a drug–target–pathway network. Finally, molecular docking was used to verify the interactions between stemazole and its targets.A database of targets associated with neurodegenerative diseases and the targets of stemazole was constructed. A total of 1981 and 1063 targets associated with AD and PD, respectively, were identified using the DisGeNET database v6.0 . A totalA total of 29 putative targets were uploaded to the STRING database to identify the functional partnerships and interactions between them. Protein interactions with a confidence score of 0.9 or higher were then imported into Cytoscape v3.7.1 to generate the protein–protein interaction (PPI) network, which comprised 23 nodes and 42 edges .To identify the hub nodes and essential proteins in the PPI network, the topological parameters of the node degree were calculated by Network Analyzer, and the three centralities  were determined by the CytoNCA plugin, as shown in p-value ≤0.05 were significantly enriched. The top 20 components were graphed using the OmicShare cloud platform  potential targets were significantly enriched in 53 pathways . The staThe GO terms comprised three categories: biological process, molecular function, and cellular component. As shown in Docking studies were carried out between stemazole and five select important targets, AKT1, CASP3, CASP8, MAPK8, and MAPK14. These targets were chosen because not only were they key nodes of the PPI network, but they also played an important role in KEGG signaling pathways. According to the molecular docking results in The docking results in this study demonstrate that the receptor–ligand interaction between ST and AKT1 involves both hydrophobic interactions and polar interactions. As shown in Moreover, the results in S23:Asp438OD2 (2.94 Å) and STS23:Leu474N (3.18 Å), further enhance the interaction between the ligand and the CASP8 protein.The action modes of ST and CASP8 are shown in N17:Gln117OE1 (3.33 Å), STN13:Asp112O (2.82 Å), and STN25:Met111N (2.73 Å)).According to the analysis shown in As shown in There is an urgent need to develop new treatment strategies because of the growing crisis resulting from neurodegenerative diseases and the poor efficacy of the existing approved drugs. Stemazole is a novel small molecule with neuroprotective effects, and its therapeutic efficacy in preclinical models of Alzheimer’s disease and Parkinson’s disease has been demonstrated in several studies. Stemazole also protects multiple types of stem cells from apoptosis. Here, a network pharmacology strategy was used to reveal the mechanism underlying the effects of stemazole. Therapeutic targets and the signaling pathways in which they participate were explored by reverse screening, PPI network construction, and pathway enrichment analysis. Information from various online servers and databases was integrated. The results we obtained are very reliable, as they benefitted from multiple information sources and different target identification methods. The specific interactions between stemazole and the targets were verified through molecular docking. Fifty-three signaling pathways and 29 proteins were shown to be involved. Five proteins were identified as the most probable targets. The results could provide a better understanding of the effects of stemazole on the treatment of neurodegenerative diseases and guide further studies of the development of stemazole as a stem cell drug.We proposed that stemazole plays a therapeutic role in the treatment of neurodegenerative diseases that is mediated by an anti-apoptotic pathway, and the theoretical calculations were carried out on this basis. A similar therapeutic mechanism has been observed for other active small molecules. Pieper and colleagues discovered an aminopropyl carbazole named P7C3, which was utilized in an in vivo screen . A serieThe targets of stemazole were enriched in the MAPK signaling pathway, which was indicated by the KEGG pathway enrichment analysis. Previous studies have shown that the activation of the MAPK signaling pathway is highly correlated with the occurrence and development of neurodegenerative diseases. In the pathogenesis of AD, the MAPK pathway contributes to disease progression by inducing neuronal apoptosis, the transcription and activation of β- and γ-secretases, and the phosphorylation of Amyloid-beta precursor protein (APP) and tau. The role of the MAPK signaling pathway in PD involves the induction of neuronal death and neuroinflammatory responses associated with the levels of α-synuclein and functional deficiencies in parkin and Protein/nucleic acid deglycase DJ-1 . The MAPTwo methods, centrality analysis of the PPI network and KEGG pathway analysis, were used individually to identify the core targets. According to the centrality and the node degree of the protein–protein interaction network, we identified the essential proteins, including MAPK8, AKT1, MAPK14, FYN, CASP3, ESR1, AR, and CASP8. Nodes with high centralities and node degrees often play the most important roles in the network. Among the top 20 enriched KEGG pathways, MAPK8, AKT1, MAPK14, CASP3, CASP8, TNF, and CASP9 were considered important because of their high frequency of involvement. The results of the two methods were not exactly the same. Proteins identified as central targets by both methods were selected for further analysis at the molecular level.Five targets, MAPK8, AKT1, MAPK14, CASP3, and CASP8, were selected for the molecular docking studies. Stemazole showed good affinity towards the five targets, which validated the network pharmacology results. These targets play important roles in the pathophysiology of neurodegenerative diseases. Akt1 is highly expressed in the nervous system and is critical for the survival of neuronal cells . NeuroprThe results of the network analysis provide a theoretical basis and important information that could be useful for elucidating the mechanisms underlying the therapeutic effects of stemazole and identifying potential targets, but the experimental verification of the targets and specific interactions will be necessary in the future.The experimental flow is shown in http://www.disgenet.org/) [https://www.proteinatlas.org/) [https://www.drugbank.ca/) [https://www.uniprot.org/) [http://ctdbase.org/) [https://www.kegg.jp/) [Targets associated with AD and PD were identified using the DisGeNET database v6.0 (et.org/) . Apoptosas.org/) , the Druank.ca/) , UniProtot.org/) , the Comse.org/) , and theegg.jp/) .The three-dimensional structure of stemazole was built and optimized in Gaussian 09W software  at the DAccording their theoretical basis, reverse screening methods are classified into one of three types: shape screening, pharmacophore screening, or reverse docking . Each mehttp://lilab-ecust.cn/pharmmapper/) [http://cpi.bio-x.cn/drar/) [http://cpi.bio-x.cn/dpdr/) [http://targetnet.scbdd.com/) [http://lilab-ecust.cn/chemmapper/) [Homo sapiens was chosen as the organism.The 3D structural file or SMILES string was submitted to the PharmMapper (mapper/) , DRAR-CPn/drar/) , DPDR-CPn/dpdr/) , TargetNdd.com/) , and Chemapper/)  servers After adding the targets together and deleting the duplicates, the obtained predicted targets were assumed to be pathological targets. Then, the therapeutic targets of stemazole relevant to its effects on AD and PD via its anti-apoptosis mechanism were preliminarily determined.http://string-db.org) [The identified targets were uploaded to the STRING database v11.0 (-db.org)  to obtai-db.org) . Network-db.org)  was util-db.org)  was usedhttps://biit.cs.ut.ee/gprofiler) [http://www.omicshare.com/). The target-pathway network was constructed in Cytoscape v3.7.1.The gene ontology and KEGG pathway enrichment analyses were carried out using the web server g: Profiler (rofiler)  and visuhttp://www.rcsb.org/) [The X-ray crystal structures of the targets (sb.org/) ,66, inclsb.org/) . The prosb.org/)  with theThe potential targets and molecular mechanisms underlying the effects of stemazole against AD and PD mediated by anti-apoptosis were systematically investigated by network pharmacology. The key pathway involved in the neuroprotective effects of stemazole is the MAPK signaling pathway, and five key targets were identified, including MAPK8, AKT1, MAPK14, CASP3, and CASP8. In summary, the presented findings may inspire and guide further pharmacological studies of the effects of stemazole against neurodegenerative diseases.


P = 0.0197], number of cycles , and calcium channel blocker use . There was no difference among the three anti-angiogenic agents (P = 0.4969) or among cancer types (P = 0.2726) in the likelihood of proteinuria. In conclusion, SBP, number of cycles, and calcium channel blocker use were identified as significant predictors of the development of angiogenesis inhibitor-induced proteinuria. There was no difference among the three anti-angiogenic agents or among cancer types.The development of proteinuria restricts the dose of anti-angiogenic agents, thereby reducing their efficacy. Thus, this retrospective study was undertaken to identify predictive factors of the development of angiogenesis inhibitor-induced proteinuria, and to elucidate if there is a difference in the likelihood of proteinuria among anti-angiogenic agents or cancer types, to help guide future strategies to improve the safety, efficacy, and quality of life of patients receiving chemotherapy. Between April 2014 and February 2019, 124 cancer patients at our outpatient chemotherapy center who were receiving chemotherapy with bevacizumab, ramucirumab, or aflibercept were enrolled. Variables related to the development of proteinuria were extracted from the patients’ clinical records and used for regression analysis. The level of the proteinuria was evaluated based on CTCAE version 5. Multivariate ordered logistic regression analysis was performed to identify predictive factors for the development of proteinuria. The Wilcoxon/Kruskal-Wallis test was used to identify significant differences between groups. Significant factors identified included systolic blood pressure (SBP) [odds ratio (OR) = 1.031, 95% confidence interval (CI) = 1.005–1.058;  The toxicity profile of anti-angiogenic agents differs from those of conventional cytotoxic anticancer agents; use of anti-angiogenic agents is commonly associated with elevated blood pressure, proteinuria, and bleeding5. The development of proteinuria restricts the dose of anti-angiogenic agents, thereby reducing their efficacy7. However, the predictive factors for proteinuria have not been fully elucidated, and few studies have examined the differences in the development of proteinuria among anti-angiogenic agents or cancer types.Anti-angiogenic agents targeting the human vascular endothelial growth factor pathway, such as bevacizumab, ramucirumab, and aflibercept, significantly improve overall survival and progression-free survival in colorectal, lung, gastric, breast cancers and so onThus, this retrospective study was undertaken to identify predictive factors of the development of angiogenesis inhibitor-induced proteinuria and to elucidate if there is a difference in the likelihood of proteinuria among anti-angiogenic agents or cancer types to help guide future strategies to improve the safety, efficacy, and quality of life (QoL) of patients receiving chemotherapy.Between April 2014 and February 2019, this study enrolled 139 colon cancer, gastric cancer, breast cancer, and lung cancer patients who were receiving chemotherapy with anti-angiogenic agents at our outpatient chemotherapy center. The Medical Ethics Review Committee of the Kyoto Prefectural University of Medicine approved this study . All procedures were performed in accordance with the ethical standards of the Medical Ethics Review Committee of the Kyoto Prefectural University of Medicine and the 1964 Helsinki Declaration and its later amendments. No prospective studies with human participants or animals were performed by any of the authors for this article. Due to the retrospective nature of this work, informed consent was waived for the individual participants included in the study in accordance with the ethical standards of the Medical Ethics Review Committee of the Kyoto Prefectural University of Medicine.For the regression analysis of factors related to angiogenesis inhibitor-induced proteinuria, variables were extracted by manual abstraction from clinical records. Variables evaluated included factors that could potentially impact the development of proteinuria: demographic data , Eastern Cooperative Oncology Group performance status, cancer type, presence of comorbidity , laboratory test values , administration of anti-angiogenic agents , medications that affect blood pressure , and vital signs . The presence of hypertension was assessed by prescriptions for antihypertensive drugs. Creatinine clearance was estimated using the Cockcroft and Gault equation based on serum creatinine, sex, age, and weight. Clinical information was extracted before the first dose of bevacizumab, ramucirumab, or aflibercept. The level of angiogenesis inhibitor-induced proteinuria was evaluated based on the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) version 5.0.Explanatory variables were examined for multicollinearity (correlation coefficient |r| ≥ 0.7), since when correlations exist among the variables, this can lead to incorrect results of regression analyses.8. In many clinical trials, the equal or >2 proteinuria grade was the drug discontinuation criterion. Therefore, patients were divided in two groups depending the equal or >2 proteinuria grade or not. Furthermore, whether there was a difference in the development of proteinuria among these three anti-angiogenic agents or cancer types was analyzed. The Wilcoxon/Kruskal-Wallis test was used to identify significant differences between groups.Explanatory variables were selected based on correlation strength with the level of the angiogenesis inhibitor-induced proteinuria (objective variable) or clinical significance. First, univariate ordered logistic regression analysis between the outcomes and each potential explanatory variable was performed. Subsequently, a multivariate ordered logistic regression model was constructed by employing the stepwise selection procedure with the potential candidate variables. The model used a variable entry criterion of 0.25 and a variable retention criterion of 0.15. Ordered logistic regression analysis was employed, because the level of proteinuria was evaluated by a graded scale and multiple factors potentially involved as predictive factors for the development of proteinuria had to be evaluated simultaneously. Optimal cutoff thresholds were determined using receiver operating characteristic curve (ROC) analysisP < 0.05 (2-tailed) were considered significant. All analyses were performed using JMP® version 14.3.0. .For all statistical analyses, values of Of the 139 patients who received chemotherapy with bevacizumab, ramucirumab, or aflibercept, 15 were excluded from this study: 3 were discontinued with only one course due to adverse events and 12 had insufficient data. Table P = 0.0197], number of cycles , and calcium channel blockers   = 1.031, 95% confidence interval (CI) = 1.005–1.058; 1) Table , and tha1) Table . ROC cur1) Table .Table 2RP = 0.4969), and there was also no difference among cancer types .There was no difference in the development of proteinuria among the anti-angiogenic agents , and calcium channel blockers. Fibrinogen was also a predictor, as determined by univariate analysis. On ROC curve analysis of the potential factors responsible for the development of proteinuria, the cut-off value for the number of cycles was ≥13, and that of SBP was ≥135 mmHg. This study also showed that the likelihood of proteinuria was not different among anti-angiogenic agents or cancer types.12. The result of the current study is consistent with this previous finding. Thus, clinicians need to know that the incidence and severity of proteinuria increase as the number of administration cycles of anti-angiogenic agents increase, especially in patients with ≥13 cycles.Several studies have reported that the development of angiogenesis inhibitor-induced proteinuria is dose-dependent13. It has also been shown that SBP ≥130 mmHg is a risk factor for bevacizumab-induced proteinuria14; similarly, the present results showed that SBP ≥135 mmHg was a risk factor for proteinuria. Clinicians need to pay attention to blood pressure control before treatment.In the current study, the SBP cut-off value for the development of proteinuria was ≥135 mmHg. Previous studies demonstrated that high blood pressure is a major risk factor for proteinuria in the general population18. During treatment with anti-angiogenic agents, RAS inhibitors may be recommended for hypertension. Further research is needed on this issue.Furthermore, the present study found that calcium channel blocker use is a risk factor for proteinuria. On the other hand, RAS inhibitor use was neither a protective factor nor a risk factor. As in previous research, the present results suggest that RAS inhibitor administration reduces the risk of proteinuria19. However, in the present study, there was no difference in the likelihood of proteinuria among cancer types. On the other hand, univariate analysis showed that proteinuria was more likely to occur in patients with colorectal cancer, but it was not significant on multivariate analysis. In patients with colorectal cancer, special attention may be needed regarding the development of proteinuria, but further study of this issue is needed. Fibrinogen was also a predictor, as determined by univariate analysis. This was consistent with previous studies20. Clinicians also need to pay attention elevated fibrinogen levels.Previous studies suggested that angiogenesis inhibitor-induced proteinuria is more likely to develop with colorectal cancer21. On the other hand, Peng et al. showed that the risk of developing all-grade and high-grade proteinuria was substantially higher with aflibercept than with bevacizumab7.In the present study, there was no difference in the likelihood of proteinuria depending on anti-angiogenic agents. A previous study suggested that severe renal side effects may be less common with ramucirumab than with bevacizumabThere were several limitations to the current study. First, the retrospective design of the research may have decreased the reliability of the data extracted. Second, since this study was conducted at a single institute, it only analyzed a relatively small number of patients. Therefore, prospective multicenter study will be needed to confirm these results.In conclusion, SBP, number of cycles, and concomitant use of calcium channel blockers were identified as significant predictors of the development of proteinuria in cancer patients treated with bevacizumab, ramucirumab, or aflibercept. In addition, it was found that the likelihood of proteinuria was not different among anti-angiogenic agents or cancer types. However, these preliminary findings will need to be confirmed in a larger randomized controlled trial. There is a need to identify cancer patients who could develop side effects, in order to be able, in the future, to select them or/and treat them with more adequate doses of anti-angiogenic agents. Nevertheless, these findings may assist in developing chemotherapeutic strategies that can be used to improve the safety and efficacy including anti-angiogenic agents, as well as the QoL of patients.


Pathway analysis is one of the later stage data analysis steps essential in interpreting high-throughput gene expression data. We propose a set of algorithms which given gene expression data can recognize which portion of sub-pathways are actively utilized in the biological system being studied. The degree of activation is measured by conditional probability of the input expression data based on the Bayesian Network model constructed from the topological pathway.We demonstrate the effectiveness of our pathway analysis method by conducting two case studies. The first one applies our method to a well-studied temporal microarray data set for the cell cycle using the KEGG Cell Cycle pathway. Our method closely reproduces the biological claims associated with the data sets, but unlike the original work ours can produce how pathway routes interact with each other above and beyond merely identifying which pathway routes are involved in the process. The second study applies the method to the p53 mutation microarray data to perform a comparative study.We show that our method achieves comparable performance against all other pathway analysis systems included in this study in identifying p53 altered pathways. Our method could pave a new way of carrying out next generation pathway analysis. The next generation pathway analysis methods aimed at overcoming such deficiency of gene enrichment methods by organizing known gene-gene interaction relationships into topological pathways and analyze gene expression data on top of them so that the activated or suppressed state of the pathway can be computationally revealed  is compared with the prior known gene regulation relationships which are typically organized into curated molecular pathways .route(s) of the pathway such gene expression perturbation could be propagating. However, one limitation of our previous work is that the method requires preselection of the start and end of pathway routes to be analyzed. In addition, through empirical studies, we discover that our previous method tends to identify “choppy” pathway routes that are partially activated or suppressed, thus less useful if one’s goal is to find overall patterns of pathway route usages. The goal of this paper is to report the extension of our previous work [We previously published topology-based pathway analysis methods belonging to this next generation pathway analysis system –19. Specous work , 19 in wAmong existing gene set enrichment analysis methods, GSEA is one of the most popular software packages in which computing the enrichment score is done by a variation of the weighted Kolmogorov-Smirnov-like statistic . SPIA byThe rest of this paper is organized as follows. “In this section we first briefly review the methodology proposed in our previous work  for the G∗ is encoded as a Bayesian Network G which is initialized with a sequence of conditional probabilities which are designed to encode directionality of regulatory relationships encoded in the pathways, i.e., activation and inhibition relationships. The transformation process from G∗ to the corresponding Bayesian Network G is illustrated in Algorithm.1. Next we show the biological interpretation logic behind the conditional probability table for eij. Consider the activation table given in , where VB={gi|i=1…|VB|} and EB={|gi,gj∈VB}. Consider a given pathway route G∗= in GB where E∗={|gi,gj∈V∗}⊂EB.Let the pathway of interest be converted into a gene regulation network G is generated from G∗, the pathway route is ranked by conditional probability of the observed data given G normalized by P as shown in  the analysis could allow biologists to easily pinpoint which biological processes are likely to be overly activated or suppressed; and (ii) even though some expression values are flipped due to random errors from the genomic data , the whole path would still have a high score since the majority of other genes could have consistent expression observations.eij IN G∗THE REGULATION PROCESS FOR Then the score is extended to be a signed score by  which vas in the route G∗ and where GB, by using the proportion of routes that have an average of all the patients’ scores, calculated by equation =0.5, Xii.i.d.∼Bernoulli(0.5). Then Bin since Xi’s are independent. Based on this distribution, one can pick ε such that the majority of the scores generated under null hypothesis (the portion ≥1−α) is less than some threshold t, namely, P≥t)<α. Since SigScore in =α as shown in Fig. t=1, K≡0 (entirely consistent) should hold according to the equation . This indicates that independent of ε, only routes with no inconsistency are discovered if t=1, but this arrangement would be too strict.mentclass2pt{minimequation  since ε∈t∈,In case when ε, B, increases if either t or α increases. If we keep the upper bound fixed, increasing t will make α decrease while providing a better confidence level and thus resulting in a smaller false positive rate.The intuition behind this formula is the following. The formula  clearly γ is concerned, given any edge eij in the route, the marginal probability γ larger than ε. However, the inconsistency should also be penalized if mutation information is present as shown in Table γ decreases making γ∈. This also explains why the setting ε=0.1 and γ=0.25 gives a good result as such outcome has been presented in one of our previous works [γ to be the midpoint between ε and 0.5, namely, (ε+0.5)/2.As far as the hyper-parameter mentclass2pt{minimus works . In thisε using the upper bound provided by  as starting node is exponential. But since examining each possible starting node in a given pathway is independent of each other, the |VB| processes can be easily parallelized. The time complexity of this algorithm is analyzed briefly. Since the algorithm runs depth first search through the pathway graph GB, this takes O(|E|) steps. For each step, we need to build the Bayesian Network and calculate the conditional probability  in the worst case. However, in our application, our route setting makes d≤2 and n≤3 for each edge, meaning at most 3 nodes  each having at most 2 possible values are considered. In this case, calculating the probability takes O(1) time. In summary, the algorithm takes linear time O(|E|).The motivations for developing the algorithm are manifold. First, the route computation of a given pathway can be done dynamically. Second, this dynamic route computation and the generation of Bayesian network real-time allows performing the analysis comprehensively but efficiently because all small sub-segments of each long pathway route are examined independently and checked if any of sub-segments exceed the thresholds for determining significantly “activated” or “suppressed”. Third, our algorithm solution is conducive to running the analysis in parallel for speed up. The complexity of examining all possible pathway sub-segments by running process bability . For n rOur first experiment is to apply our algorithms to the microarray data set by  which air by . Since no mutation information is available for the S3 HeLa cell, m is set as a null vector. The procedure is run on all possible starting nodes in GB.The cell cycle data set by  used synr by . Log2  and DPA (pScore>0). In that regard, the accuracies of both systems can be seen quite comparable. As an alternative comparison study, APA and DPA have been compared using only 132 pathways from the newest version of KEGG, 66 for class 1  and 66 for class 0 . The results are 0.76 for APA and 0.78 for DPA making DPA outperforms APA by 0.02.We use the pathway score, given in  to rank In terms of delivering explanation for the biologists, DPA offers a far greater benefit over APA by presenting the prior knowledge in a manner that biologists are familiar with, i.e., gene regulatory relationships organized into topological pathways. One reason that previous pathway analysis tools fails to work well is because they mainly try to discover perturbed pathways by individual differentially expressed genes instead of gene to gene interactions . Both APlog(SigScore) for false positive (pathways not having p53 targets but identified) vs true positive (pathways having p53 and identified) and produce a box plot comparison, as shown in Fig. t-test[Lastly, to show the effectiveness of SigScore given in , we calcg. t-test performeWe proposed a set of algorithms which given a gene expression data set can compute and score the “perturbed” portion of biological pathways. This method identifies overly regulating routes (or "axes") of pathways by calculating the conditional probabilities of regulatory relationships encoded into Bayesian networks which are constructed from known biological pathways. Our method has been tested with two well-known, publicly available microarray data sets. In our application to the cell cycling microarray data, our method can “recognize” specific portions of pathways clearly revealing cell cycle phase transition with which biologists can easily identify the localized perturbation patterns. We demonstrated through pathway network visualization that our method can clearly reveal how activated pathway routes changes over time and if such pattern change repeats as cell cycling progresses. In our comparison study with APA, our approach demonstrates a comparable accuracy in recognizing perturbed pathways as our method algorithmically identifies isolated sub-network of the pathway as opposed to computing pathway’s perturbation status using enrichment statistics. The name DPA  originates from the novelty of our method that can deeply recognize perturbed portions of the pathways. Our method of programmatically identifying ”localized” regulating portion of the pathways could pave a new way to carry out future pathway analysis.