scholarly journals Mechanism Analysis of Coix Seed in Gastric Cancer Treatment Based on Biological Network Modules

2020 ◽  
Vol 15 (5) ◽  
pp. 1934578X2092752
Author(s):  
Fengbin Zhang ◽  
Xiaoyan Liu ◽  
Bingjie Huo ◽  
Bing Li ◽  
Ruixing Zhang
Keyword(s):  
Gastric Cancer ◽  
Target Genes ◽  
Biological Network ◽  
Interaction Network ◽  
Mechanism Analysis ◽  
Protein Protein Interaction ◽  
Network Analyses ◽  
Analysis Methods ◽  
Coix Seed ◽  
Modular Analysis

Coix seed, the mature seed of Coix lacryma-jobi L., is a traditional herb widely used in various cancer adjuvant treatments; however, its mechanism is unknown. The aim of this study was to reveal the multitarget mechanisms of Coix seed in the treatment of gastric cancer (GC) by biological network and modular analysis methods. Forty-one ingredients and 482 targets of Coix seed and 165 GC-related genes were obtained from databases. Twelve on-target genes ( AICDA, CASP3, EP300, ERBB2, FGFR2, IL12A, IL12B, IL1B, LOX, TJP1, TP53, and TRIB3) of Coix seed overlapped with GC-related genes. Using compound-target and protein–protein interaction network analyses, we discovered the core targets of Coix seed. Markov cluster algorithm-based modular analysis identified 5 potential module targets of Coix seed for GC. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis demonstrated the vast actions of Coix seed, which involve pathways in cancer, the cell cycle, receptor signal transduction, deoxyribonucleic acid damage response, transcriptional regulation, apoptosis, and cell connections. This study elucidated the potential mechanisms of Coix seed on GC, which may lead to the development of an effective drug. Additionally, this study showed the feasibility of network and modular analysis methods to investigate traditional Chinese medicinal herbal mechanisms and may provide a new angle for further research in the field of anticancer mechanisms and multitarget drugs.

scholarly journals Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses

2020 ◽  
Author(s):  
Basavaraj Vastrad ◽  
Chanabasayya Vastrad
Keyword(s):  
Gastric Cancer ◽  
Regulatory Network ◽  
Target Genes ◽  
Characteristic Curve ◽  
Interaction Network ◽  
Microarray Dataset ◽  
Gene Expression Omnibus ◽  
Hub Genes ◽  
Clinical Prognosis ◽  
Protein Protein Interaction

AbstractThe high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a protein protein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes. The pathways and GO functions of the up and down regulated genes were mainly enriched in pyrimidine deoxyribonucleosides degradation, extracellular structure organization, allopregnanolone biosynthesis and digestion. FN1, PLK1, ANLN, MCM7, MCM2, EEF1A2, PTGER3, CKB, ERBB4 and PRKAA2 were identified as the most important genes of GC, and validated by TCGA database, The Human Protein Atlas database, receiver operating characteristic curve (ROC) analysis and RT-PCR. Bioinformatics analysis might be useful method to explore the molecular pathogensis of GC. In addition, FN1, PLK1, ANLN, MCM7, MCM2, EEF1A2, PTGER3, CKB, ERBB4 and PRKAA2 might be the most important genes of GC.

Bioinformatics Analysis Reveals Functions of MicroRNAs in Rice Under the Drought Stress

2021 ◽  
Vol 15 (8) ◽  
pp. 927-936 ◽  
Author(s):  
Yan Peng ◽  
Yuewu Liu ◽  
Xinbo Chen
Keyword(s):  
Drought Stress ◽  
Target Genes ◽  
Hot Spot ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Promising Tool ◽  
Differentially Expressed Mirnas ◽  
Aba Biosynthesis

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Method: In this study, we integrated miRNAs and genes transcriptome data of rice under the drought stress. Some bioinformatics methods were used to reveal the functions of miRNAs in rice under drought stress. These methods included target genes identification, differentially expressed miRNAs screening, enrichment analysis of DEGs, network constructions for miRNA-target and target-target proteins interaction. Results: (1) A total of 229 miRNAs with differential expression in rice under the drought stress, corresponding to 73 rice miRNAs families, were identified. (2) 1035 differentially expressed genes (DEGs) were identified, which included 357 up-regulated genes, 542 down-regulated genes and 136 up/down-regulated genes. (3) The network of regulatory relationships between 73 rice miRNAs families and 1035 DEGs was constructed. (4) 25 UP_KEYWORDS terms of DEGs, 125 GO terms and 7 pathways were obtained. (5) The protein-protein interaction network of 1035 DEGs was constructed. Conclusion: (1) MiRNA-regulated targets in rice might mainly involve in a series of basic biological processes and pathways under drought conditions. (2) MiRNAs in rice might play critical roles in Lignin degradation and ABA biosynthesis. (3) MiRNAs in rice might play an important role in drought signal perceiving and transduction.

scholarly journals Decoding the molecular mechanism of parthenocarpy in Musa spp. through protein–protein interaction network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Suthanthiram Backiyarani ◽  
Rajendran Sasikala ◽  
Simeon Sharmiladevi ◽  
Subbaraya Uma
Keyword(s):  
Candidate Genes ◽  
Protein Interaction ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Auxin Signaling ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
The Difference

AbstractBanana, one of the most important staple fruit among global consumers is highly sterile owing to natural parthenocarpy. Identification of genetic factors responsible for parthenocarpy would facilitate the conventional breeders to improve the seeded accessions. We have constructed Protein–protein interaction (PPI) network through mining differentially expressed genes and the genes used for transgenic studies with respect to parthenocarpy. Based on the topological and pathway enrichment analysis of proteins in PPI network, 12 candidate genes were shortlisted. By further validating these candidate genes in seeded and seedless accession of Musa spp. we put forward MaAGL8, MaMADS16, MaGH3.8, MaMADS29, MaRGA1, MaEXPA1, MaGID1C, MaHK2 and MaBAM1 as possible target genes in the study of natural parthenocarpy. In contrary, expression profile of MaACLB-2 and MaZEP is anticipated to highlight the difference in artificially induced and natural parthenocarpy. By exploring the PPI of validated genes from the network, we postulated a putative pathway that bring insights into the significance of cytokinin mediated CLAVATA(CLV)–WUSHEL(WUS) signaling pathway in addition to gibberellin mediated auxin signaling in parthenocarpy. Our analysis is the first attempt to identify candidate genes and to hypothesize a putative mechanism that bridges the gaps in understanding natural parthenocarpy through PPI network.

scholarly journals Exploring Heat-Response Mechanisms of MicroRNAs Based on Microarray Data of Rice Post-meiosis Panicle

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yan Peng ◽  
Xianwen Zhang ◽  
Yuewu Liu ◽  
Xinbo Chen
Keyword(s):  
Heat Stress ◽  
Target Genes ◽  
Expression Profiles ◽  
Time Lag ◽  
Interaction Network ◽  
Biological Processes ◽  
Functional Identification ◽  
Protein Protein Interaction ◽  
Heat Response ◽  
Protein Protein Interaction Network

To explore heat response mechanisms of mircoRNAs (miRNAs) in rice post-meiosis panicle, microarray analysis was performed on RNA isolated from rice post-meiosis panicles which were treated at 40°C for 0 min, 10 min, 20 min, 60 min, and 2 h. By integrating paired differentially expressed (DE) miRNAs and mRNA expression profiles, we found that the expression levels of 29 DE-miRNA families were negatively correlated to their 178 DE-target genes. Further analysis showed that the majority of miRNAs in 29 DE-miRNA families resisted the heat stress by downregulating their target genes and a time lag existed between expression of miRNAs and their target genes. Then, GO-Slim classification and functional identification of these 178 target genes showed that (1) miRNAs were mainly involved in a series of basic biological processes even under heat conditions; (2) some miRNAs might play important roles in the heat resistance (such as osa-miR164, osa-miR166, osa-miR169, osa-miR319, osa-miR390, osa-miR395, and osa-miR399); (3) osa-miR172 might play important roles in protecting the rice panicle under the heat stress, but osa-miR437, osa-miR418, osa-miR164, miR156, and miR529 might negatively affect rice fertility and panicle flower; and (4) osa-miR414 might inhibit the flowering gene expression by downregulation of LOC_Os 05g51830 to delay the heading of rice. Finally, a heat-induced miRNA-PPI (protein-protein interaction) network was constructed, and three miRNA coregulatory modules were discovered.

scholarly journals Potential Molecular Target Prediction and Docking Verification of Hua-Feng-Dan in Stroke Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Ping Yang ◽  
Haifeng He ◽  
Shangfu Xu ◽  
Ping Liu ◽  
Xinyu Bai
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Target Genes ◽  
Target Prediction ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Core Network ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Highly Correlated

Objective. Hua-Feng-Dan (HFD) is a Chinese medicine for stroke. This study is to predict and verify potential molecular targets and pathways of HFD against stroke using network pharmacology. Methods. The TCMSP database and TCMID were used to search for the active ingredients of HFD, and GeneCards and DrugBank databases were used to search for stroke-related target genes to construct the “component-target-disease” by Cytoscape 3.7.1, which was further filtered by MCODE to build a core network. The STRING database was used to obtain interrelationships by topology and to construct a protein-protein interaction network. GO and KEGG were carried out through DAVID Bioinformatics. Autodock 4.2 was used for molecular docking. BaseSpace was used to correlate target genes with the GEO database. Results. Based on OB ≥ 30% and DL ≥ 0.18, 42 active ingredients were extracted from HFD, and 107 associated targets were obtained. PPI network and Cytoscape analysis identified 22 key targets. GO analysis suggested 51 cellular biological processes, and KEGG suggested that 60 pathways were related to the antistroke mechanism of HFD, with p53, PI3K-Akt, and apoptosis signaling pathways being most important for HFD effects. Molecular docking verified interactions between the core target (CASP8, CASP9, MDM2, CYCS, RELA, and CCND1) and the active ingredients (beta-sitosterol, luteolin, baicalein, and wogonin). The identified gene targets were highly correlated with the GEO biosets, and the stroke-protection effects of Xuesaitong in the database were verified by identified targets. Conclusion. HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could be valuable to evaluate the antistroke effects of traditional Chinese medicines.

scholarly journals Identification of hub driving genes and regulators of lung adenocarcinoma based on the gene Co-expression network

2020 ◽  
Vol 40 (4) ◽  
Author(s):  
Zihao Xu ◽  
Zilong Wu ◽  
Jiatang Xu ◽  
Jingtao Zhang ◽  
Bentong Yu
Keyword(s):  
Lung Adenocarcinoma ◽  
Target Genes ◽  
Characteristic Curve ◽  
Interaction Network ◽  
Mapk Signaling ◽  
The Cancer Genome Atlas ◽  
Circular Rnas ◽  
Node Degree ◽  
Protein Protein Interaction ◽  
Cancer Tissues

Abstract Lung adenocarcinoma (LUAD) remains the leading cause of cancer-related deaths worldwide. Increasing evidence suggests that circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) can regulate target gene expression and participate in tumor genesis and progression. However, hub driving genes and regulators playing a potential role in LUAD progression have not been fully elucidated yet. Based on data from The Cancer Genome Atlas database, 2837 differentially expressed genes, 741 DE-regulators were screened by comparing cancer tissues with paracancerous tissues. Then, 651 hub driving genes were selected by the topological relation of the protein–protein interaction network. Also, the target genes of DE-regulators were identified. Moreover, a key gene set containing 65 genes was obtained from the hub driving genes and target genes intersection. Subsequently, 183 hub regulators were selected based on the analysis of node degree in the ceRNA network. Next, a comprehensive analysis of the subgroups and Wnt, mTOR, and MAPK signaling pathways was conducted to understand enrichment of the subgroups. Survival analysis and a receiver operating characteristic curve analysis were further used to screen for the key genes and regulators. Furthermore, we verified key molecules based on external database, LRRK2, PECAM1, EPAS1, LDB2, and HOXA11-AS showed good results. LRRK2 was further identified as promising biomarker associated with CNV alteration and various immune cells’ infiltration levels in LUAD. Overall, the present study provided a novel perspective and insight into hub driving genes and regulators in LUAD, suggesting that the identified signature could serve as an independent prognostic biomarker.

scholarly journals Unveiling Potential Active Constituents and Pharmacological Mechanisms of Pudilanxiaoyan Oral Liquid for Anti-Coronavirus Pneumonia Using Network Pharmacology

2021 ◽  
Author(s):  
Ying-Peng Tong ◽  
Xiao-Fei Shen ◽  
Qi Zhou ◽  
Chun-Xiao Jiang ◽  
Na Li ◽  
...  
Keyword(s):  
Target Genes ◽  
Inflammatory Responses ◽  
Interaction Network ◽  
In Vitro Study ◽  
Network Pharmacology ◽  
Active Components ◽  
Active Constituents ◽  
Network Analyses ◽  
Oral Liquid

AbstractThe outbreak of novel coronavirus pneumonia (COVID-19), defined as a worldwide pandemic, has been a public health emergency of international concern. Pudilanxiaoyan oral liquid (PDL), an effective drug of Traditional Chinese Medicine (TCM), is considered to be an effective and alternative means for clinical prevention of COVID-19. The purpose of this study was to identify potential active constituents of PDL, and explore its underlying anti-COVID-19 mechanism using network pharmacology. Integration of target prediction (SwissTargetPrediction and STITCH database) was used to elucidate the active components of PDL. Protein–protein interaction network analyses, gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, network construction, and molecular docking were applied to analyze the prospective mechanisms of the predicted target genes. Our results showed that the key active ingredients in PDL were luteolin, apigenin, esculetin, chrysin, baicalein, oroxylin A, baicalin, wogonin, cymaroside, and gallic acid. A majority of the predicted targets were mainly involved in the pathways related to viral infection, lung injury, and inflammatory responses. An in vitro study further inferred that inhibiting the activity of nuclear factor (NF)-кB signaling pathway was a key mechanism by which PDL exerted anti-COVID-19 effects. This study not only provides chemical basis and pharmacology of PDL but also the rationale for strategies to exploring future TCM for COVID-19 therapy.

scholarly journals Combined Transcriptome and Proteome Leukocyte’s Profiling Reveals Up-Regulated Module of Genes/Proteins Related to Low Density Neutrophils and Impaired Transcription and Translation Processes in Clinical Sepsis

2021 ◽  
Vol 12 ◽  
Author(s):  
Giuseppe Gianini Figueirêdo Leite ◽  
Bianca Lima Ferreira ◽  
Alexandre Keiji Tashima ◽  
Erika Sayuri Nishiduka ◽  
Edecio Cunha-Neto ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mononuclear Cells ◽  
Interaction Network ◽  
Low Density ◽  
Mitochondrial Translation ◽  
Peripheral Blood Mononuclear ◽  
Protein Coding ◽  
Protein Protein Interaction ◽  
Network Analyses ◽  
Host Defense System

Sepsis is a global health emergency, which is caused by various sources of infection that lead to changes in gene expression, protein-coding, and metabolism. Advancements in “omics” technologies have provided valuable tools to unravel the mechanisms involved in the pathogenesis of this disease. In this study, we performed shotgun mass spectrometry in peripheral blood mononuclear cells (PBMC) from septic patients (N=24) and healthy controls (N=9) and combined these results with two public microarray leukocytes datasets. Through combination of transcriptome and proteome profiling, we identified 170 co‐differentially expressed genes/proteins. Among these, 122 genes/proteins displayed the same expression trend. Ingenuity Pathway Analysis revealed pathways related to lymphocyte functions with decreased status, and defense processes that were predicted to be strongly increased. Protein-protein interaction network analyses revealed two densely connected regions, which mainly included down‐regulated genes/proteins that were related to the transcription of RNA, translation of proteins, and mitochondrial translation. Additionally, we identified one module comprising of up‐regulated genes/proteins, which were mainly related to low-density neutrophils (LDNs). LDNs were reported in sepsis and in COVID-19. Changes in gene expression level were validated using quantitative real-time PCR in PBMCs from patients with sepsis. To further support that the source of the upregulated module of genes/proteins found in our results were derived from LDNs, we identified an increase of this population by flow cytometry in PBMC samples obtained from the same cohort of septic patients included in the proteomic analysis. This study provides new insights into a reprioritization of biological functions in response to sepsis that involved a transcriptional and translational shutdown of genes/proteins, with exception of a set of genes/proteins related to LDNs and host‐defense system.

scholarly journals The Biological Role of Sponge Circular RNAs in Gastric Cancer: Main Players or Coadjuvants?

Cancers ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1982
Author(s):  
Adenilson Leão Pereira ◽  
Leandro Magalhães ◽  
Rafael Pompeu Pantoja ◽  
Gilderlanio Araújo ◽  
Ândrea Ribeiro-dos-Santos ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Target Genes ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Interaction Network ◽  
Gastric Carcinogenesis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Circular Rnas ◽  
Cancer Genome Atlas

Circular RNAs (circRNAs) are a new class of long noncoding RNAs able to perform multiple functions, including sponging microRNAs (miRNAs) and RNA-Binding Proteins (RBPs). They play an important role in gastric carcinogenesis, but its involvement during gastric cancer (GC) development and progression are not well understood. We gathered miRNA and/or RBPs sponge circRNAs present in GC, and accessed their biological roles through functional enrichment of their target genes or ligand RBPs. We identified 54 sponge circRNAs in GC that are able to sponge 51 miRNAs and 103 RBPs. Then, we evaluated their host gene expression using The Cancer Genome Atlas (TCGA) database and observed that COL1A2 is the most overexpressed gene, which may be due to circHIPK3/miR-29b-c/COL1A2 axis dysregulation. We identified 27 GC-related pathways that may be affected mainly by circPVT1, circHIPK3 and circNF1. Our results indicate that circHIPK3/miR-107/BDNF/LIN28 axis may mediate chemoresistance in GC, and that circPVT1, circHIPK3, circNF1, ciRS-7 and circ_0000096 appear to be involved in gastrointestinal cancer development. Lastly, circHIPK3, circNRIP1 and circSMARCA5 were identified in different ethnic populations and may be ubiquitous modulators of gastric carcinogenesis. Overall, the studied sponge circRNAs are part of a complex RBP-circRNA-miRNA-mRNA interaction network, and are involved in the establishment, chemoresistance and progression of GC.

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