Reactome Pathway Enrichment Analysis Research Articles

Downregulation of ST3GAL5 is associated with muscle invasion, high grade and a poor prognosis in patients with bladder cancer.

In patients with bladder cancer (BC), the association between ST3 β-galactoside α-2,3-sialyltransferase 5 (ST3GAL5) expression and clinical outcomes, particularly regarding muscle-invasive disease, high tumor grade and prognosis, remain unknown. In the present study, the expression of ST3GAL5 and its association with clinical outcomes in patients with BC was analyzed using various public bioinformatics databases. The difference in ST3GAL5 expression between BC and healthy bladder tissues was also evaluated using data from the Oncomine database, The Cancer Genome Atlas and Gene Expression Omnibus database. The differences in ST3GAL5 expression between muscle invasive BC (MIBC) and non-muscle invasive BC (NMIBC), and high- and low-grade BC were also analyzed. Furthermore, genes that were positively co-expressed with ST3GAL5 in patients with BC were identified from the intersection between the Oncomine, Gene Expression Profiling Interactive Analysis 2 and UALCAN databases. Enrichment analysis by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Reactome pathway enrichment analyses and a gene-concept network was performed using R package. Gene set enrichment analysis was also performed to assess the signaling pathways influenced by the high and low expression of ST3GAL5 in BC. The results indicated that ST3GAL5 expression was significantly lower in BC tissues compared with normal bladder tissues (P<0.05). Furthermore, ST3GAL5 expression in MIBC and high-grade BC was significantly lower compared with NMIBC and low-grade BC (P<0.05), respectively. The results from Kaplan-Meier survival analysis result demonstrated that ST3GAL5 downregulation was associated with poor survival in patients with BC (P<0.05). Taken together, these findings suggested that ST3GAL5 may be considered as an anti-oncogene in BC, could represent a potential predictive and prognostic biomarker for BC and may be a molecular target for tumor therapy.

ASR488, a novel small molecule, activates an mRNA binding protein, CPEB1, and inhibits the growth of bladder cancer.

Due to a lack of mechanistic insights, muscle-invasive bladder cancer (MIBC) remains incurable and is one of the most lethal types of cancer in the United States. The present study investigated changes in the molecular signatures of MIBC cells (TCCSUP and HT1376) after treatment with a novel small molecule, ASR488, to gain knowledge of the mechanisms that inhibited MIBC cell growth. ASR488 treatment initiated apoptotic signaling in MIBC cells. Pathway enrichment analysis was used to analyze the changes in function of differentially expressed genes. Gene Ontology analysis, as well as Kyoto Encyclopedia of Genes and Genomes analysis, was also performed. These analyses along with reactome pathway enrichment analyses indicated that the genes upregulated in the ASR488-treated cells are involved in focal adhesion, neurotrophin signaling, p53 signaling, endoplasmic reticulum functioning in terms of protein processing, and pathways related to bladder cancer. The genes downregulated in ASR488-treated MIBC cells were mainly involved in DNA replication, mismatch repair, RNA degradation, nucleotide excision repair and TGFβ signaling (P<0.05). Furthermore, reverse transcription-quantitative PCR analysis revealed an increase in transcripts of the most upregulated genes in ASR 488-treated MIBC cells: CPEB1 (36-fold), IL11 (30-fold), SFN (20.12-fold) and CYP4F11 (15.8-fold). In conclusion, the analysis of biological functions of the most differentially expressed genes revealed possible mechanisms that may be associated with the aggressiveness of MIBC.

Validation of the Key Active Ingredients and Anti-Inflammatory and Analgesic Effects of Shenjin Huoxue Mixture Against Osteoarthritis by Integrating Network Pharmacology Approach and Thin-Layer Chromatography Analysis.

BackgroundShenjin Huoxue Mixture (SHM), a classic traditional herb mixture has shown significant clinical efficacy against osteoarthritis (OA). Our previous experimental study has confirmed its anti–inflammatory and analgesic effect on acute soft tissue injury in rats, with the compound of glycyrrhizinate in SHM identified and the content of paeoniflorin in SHM determined by high-performance liquid chromatography (HPLC). However, the components and its pharmacological mechanisms of SHM against OA have not been systematically elucidated yet. Thus this study aimed to predict the key active ingredients and potential pharmacological mechanisms of SHM in the treatment of OA by network pharmacology approach and thin-layer chromatography (TLC) validation.MethodsThe active ingredients of SHM and their targets, as well as OA-related targets, were identified from databases. The key active ingredients were defined and ranked by the number of articles retrieved in PubMed using the keyword “(the active ingredients [Title/]) AND Osteoarthritis[Title/] ”, and validated partially by TLC. The pharmacological mechanisms of SHM against OA were displayed by GO term and Reactome pathway enrichment analysis with Discovery Studio 3.0 software docking to testing the reliability.ResultsFinally, 16 key active ingredients were identified and ranked, including quercetin validated through TLC. Inflammatory response, IL-6 signaling pathway and toll-like receptor (TLR) cascades pathway were predicted as the main pharmacological mechanisms of SHM against OA. Especially, 12 out of 16 key active ingredients, including validated quercetin, were well docked to IL-6 proteins.ConclusionOur results confirmed the anti–inflammatory and analgesic effect of SHM against OA through multiple components, multiple targets and multiple pathways, which revealed the theoretical basis of SHM against OA and may provide a new drug option for treating OA.

Network Pharmacology Study of Heat-Clearing and Detoxifying Traditional Chinese Medicine for Alzheimer's Disease.

This study aims to explore the possible homologous mechanism of 7 frequently‐used herbs for heat-clearing and detoxification in traditional Chinese medicine (HDTCM) for treating Alzheimer's disease (AD), one of the most common types of dementia, based on network pharmacology. Herbs that satisfied the criteria of containing chlorogenic acid, relating to AD and aligning with HDTCM, were simultaneously collected to determine whether they have anti-AD effect based on a survey of the literature. Herb-ingredient-target-disease networks were constructed by collecting information from the TCMSP and GeneCards public databases. The common targets of the herbs and AD were identified for conducting a Gene Ontology (GO) analyses and a Reactome pathway enrichment analysis. The results showed that PTGS1, IL-6, CASP3, and VEGFA were the predicted key gene targets. The IL-4 and IL-13 signaling pathway, the ESR-mediated signaling pathway, and the extranuclear estrogen signaling pathway were the significant pathways associated with the 7 herbs. This study revealed that the analogous anti-AD mechanism of the 7 herbs of HDTCM may be associated with anti-inflammation, which is a common effect of the chlorogenic acid and quercetin components.

Impacts of a Proliferation-Inducing Ligand on Current Therapeutic Monoclonal Antibody-Induced Cytotoxicity Against Human Multiple Myeloma Cells

A proliferation inducing ligand (APRIL) is a natural ligand for B cell maturation antigen (BCMA) and transmembrane activator and CAML interactor (TACI), two receptors overexpressed in human multiple myeloma (MM) patient cells. Specifically, BCMA is highly expressed in plasma cells of all MM patients and BCMA-based immunotherapies has recently shown impressive response rates in patients with relapsed and refractory diseases. APRIL, mainly secreted by myeloma-supporting bone marrow (BM) accessory cells, i.e., macrophages, osteoclasts (OC), promotes MM cell progression in vitro and in vivo. It further induces survival and function of regulatory T cells (Treg) via TACI, but not BCMA, to support an immunosuppressive MM BM microenvironment (Leukemia. 2019;33:426). Here, we study effects of APRIL in current immunotherapies in MM and determine whether APRIL influences antibody-dependent cellular cytotoxicity (ADCC) induced by therapeutic anti-BCMA (J6M0) or anti-CD38 (daratumumab) mAbs via FcR-expressing immune effector cell-dependent mechanisms. Using anti-human IgG1 to detect J6M0 binding to the cell membrane BCMA, we first showed that APRIL, in a dose-dependent manner (31-500 ng/ml), competed with J6M0 for binding to BCMA. Such effects were inhibited by the blocking anti-APRIL monoclonal antibody (mAb) (Apry-1-1), as confirmed by flow cytometry and confocal microscopy. APRIL still inhibited J6M0 binding to BCMA at 4°C, arguing against that APRIL induces shedding of BCMA receptor. Using PE labeled anti-FLAG to detect APRIL-FLAG bindings to MM cell surface BCMA, J6M0 (0.25-4 µg/ml) did not alter APRIL binding to BCMA following 2h or 1d incubation. High concentrations of J6M0 (&amp;gt;10 µg/ml) only blocked ~50% of APRIL (0.2 µg/ml)-induced NFκB activity as determined by specific DNA binding assays, indicating that APRIL-induced signaling cascade via BCMA or TACI in MM cells is not completely blocked by J6M0. In parallel, data analysis using mRNA-seq identified 594 or 355 differentially expressed genes (Log2-Fold-change &amp;gt; 1.5 and adjusted p &amp;lt; 0.05) in APRIL- and BCMA-overexpressed RPMI8226 MM cell transfectants, respectively, when compared with control parental cells. KEGG and Reactome pathway enrichment analysis further defined that these differentially expressed genes are enriched in cell adhesion, migration, chemokine signaling pathways, and JAK/STAT signaling pathways, in addition to proliferation and survival in MM cells. We next asked whether overnight treatment with APRIL in MM cell lines decreased their baseline lysis by FcR-expressing effector cells, i.e., NK, monocytes. In a dose-dependent manner, APRIL (10-200 ng/ml) downregulated baseline MM cell lysis mediated by these effector cells. Importantly, in a similar fashion, ADCC was decreased against all APRIL-treated vs control MM cell lines induced by J6M0 or daratumumab. Conversely, blocking anti-APRIL mAbs reverted APRIL-suppressed cytotoxicity against MM cells induced by J6M0 or daratuzumab. These results were validated by decreased J6M0-induced NK cell degranulation following co-incubation with APRIL-treated vs control MM cells. In contrast, anti-APRIL neutralizing mAbs specifically blocked APRIL-inhibited NK cell membrane CD107a expression. Furthermore, co-cultures with MM-supporting OCs or macrophages decreased ADCC against MM cells by NK cells; conversely the neutralizing anti-APRIL mAb significantly blocked APRIL-reduced MM cell lysis by J6M0- or Daratumumab. Finally, APRIL reduced J6M0-induced patient MM cell lysis when freshly isolated BM mononuclear cells from MM patients (n=10) were incubated with NK cells from the same individual. Anti-APRIL mAbs still blocked APRIL blockade in J6M0-induced autologous patient MM cell lysis. Taken together, our data further indicate that therapies directed at the APRIL/BCMA and APRIL/TACI axes may simultaneously target MM cells and counteract APRIL-reduced MM cell lysis induced by therapeutic mAbs targeting MM cells. These results thus support combination strategies of blocking APRIL mAbs with BCMA- or CD38-directed immunotherapies to further overcome MM cell-induced immunosuppressive BM microenvironment, thereby enhance Disclosures Munshi: Abbvie: Consultancy; Abbvie: Consultancy; Celgene: Consultancy; Takeda: Consultancy; Takeda: Consultancy; Oncopep: Consultancy; Janssen: Consultancy; Janssen: Consultancy; Oncopep: Consultancy; Amgen: Consultancy; Amgen: Consultancy; Adaptive: Consultancy; Adaptive: Consultancy; Celgene: Consultancy. Anderson:Gilead Sciences: Other: Advisory Board; Janssen: Other: Advisory Board; Sanofi-Aventis: Other: Advisory Board; OncoPep: Other: Scientific founder ; C4 Therapeutics: Other: Scientific founder .

Identification of Marker Genes and Pathways in Patients with Primary Biliary Cholangitis.

Primary biliary cholangitis (PBC) is an autoimmune liver disease characterized by cholestasis and cirrhosis, and in which hepatic failure may occur. This study explores the changes in the gene expression profiles of liver tissues during the pathogenesis of PBC. Array dataset GSE79850 was downloaded from the Gene Expression Omnibus database. GeneSpring software was used to analyze differentially expressed genes (DEGs) in liver tissues from PBC patients compared with those from controls. Gene ontology (GO) annotation, the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome pathway enrichment analyses were performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID) software. Cytoscape software was used to construct a protein-protein interaction (PPI) network. Plug-ins Molecular Complex Detection and iRegulon were used for clustering analysis and transcription factors related to key genes with PBC. A total of 77 DEGs, including 47 up- and 30 downregulated genes, were identified. The PPI network was established with 74 nodes and 356 protein pairs. The C-C motif chemokine ligand 5 (CCL5), interleukin 7 receptor (IL7R), and TNF receptor superfamily member 1A (TNFRSF1A) were identified as hub genes in the PPI network and may, therefore, be marker genes for PBC. Further, the upregulated genes CCL5 and IL7R, and downregulated TNFRSF1A were included in immune system processes as a GO term in the category Biological Processes. In conclusion, CCL5, IL7R, TNFRSF1A, and the immune response pathway may have crucial roles in PBC. These genes and pathways may be potential targets for treating PBC.

Profiling of differentially expressed genes in cadmium-induced prostate carcinogenesis

The aim of the present study was to investigate the genetic signatures of cadmium-transformed prostate epithelial (CTPE) cells and to identify the potential molecular signaling involved in their malignant transformation. The dataset contained normal prostate epithelial (RWPE-1) and CTPE cells. To further examine the biological functions of the identified differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome pathway enrichment analyses were performed. In total, 2357 DEGs were identified, including 1083 upregulated genes and 1274 downregulated genes. GO, KEGG, and Reactome pathway enrichment analyses indicated that upregulated genes were significantly enriched in ECM-receptor, focal adhesion, TGFβ signaling, and syndecan interactions, while downregulated genes were mainly involved in cell cycle regulation, arachidonic acid metabolism, oxidative phosphorylation, and folate biosynthesis (p < .05). The top upregulated (SATB1 (p < .0001), EYA2 (p < .0001) and KPNA7 (p < .0027)) and downregulated (PITX2 (p < .0007), PDLIM4 (p < .0020) and FABP5 (p < .0007)) genes were further validated via qRT-PCR analysis. In conclusion, the present study profiled DEGs in RWPE-1 and CTPE cells and identified gene pathways that may be associated with malignant transformation and tumor progression.

LncADeep: an ab initio lncRNA identification and functional annotation tool based on deep learning.

To characterize long non-coding RNAs (lncRNAs), both identifying and functionally annotating them are essential to be addressed. Moreover, a comprehensive construction for lncRNA annotation is desired to facilitate the research in the field. We present LncADeep, a novel lncRNA identification and functional annotation tool. For lncRNA identification, LncADeep integrates intrinsic and homology features into a deep belief network and constructs models targeting both full- and partial-length transcripts. For functional annotation, LncADeep predicts a lncRNA's interacting proteins based on deep neural networks, using both sequence and structure information. Furthermore, LncADeep integrates KEGG and Reactome pathway enrichment analysis and functional module detection with the predicted interacting proteins, and provides the enriched pathways and functional modules as functional annotations for lncRNAs. Test results show that LncADeep outperforms state-of-the-art tools, both for lncRNA identification and lncRNA-protein interaction prediction, and then presents a functional interpretation. We expect that LncADeep can contribute to identifying and annotating novel lncRNAs. LncADeep is freely available for academic use at http://cqb.pku.edu.cn/ZhuLab/lncadeep/ and https://github.com/cyang235/LncADeep/. Supplementary data are available at Bioinformatics online.

Identification of key genes associated with bladder cancer using gene expression profiles.

The aim of the present study was to further investigate the molecular mechanisms of bladder cancer. The microarray data GSE52519 were downloaded from Gene Expression Omnibus, comprising 9 bladder cancer and 3 normal bladder tissue samples. Differentially expressed genes (DEGs) were identified using Limma package analysis. Subsequently, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes and Reactome pathway enrichment analyses were performed for down- and upregulated DEGs. Transcription factors and genes associated with cancer from DEGs were identified. Protein-protein interaction (PPI) networks were constructed using STRING, and pathway enrichment analysis was also conducted for genes in the core sub-network that was identified using BioNet. In total, 420 downregulated and 335 upregulated DEGs were identified. Functional and pathway enrichment analyses identified that a number of DEGs, including AURKA, CCNA2, CCNE1, CDC20 and CCNB2, were enriched in the cell cycle. Furthermore, a total of 12 upregulated proto-oncogenes were identified, including AURKA and CCNA2. In the PPI sub-network, a number of DEGs (e.g., CCNB2, CDC20, CCNA2 and MCM6) with higher degrees were enriched in the KEGG pathway of the cell cycle. In conclusion, the DEGs associated with the cell cycle (e.g., CDC20, CCNA2, CCNB2 and AURKA) may serve pivotal roles in the pathogenesis of bladder cancer.

Identification of key genes and pathways associated with obesity in children.

The present study aimed to identify potential key genes and pathways in obese children in order to explore possible molecular mechanisms associated with child obesity. The array dataset GSE29718 was downloaded from the Gene Expression Omnibus database. Subcutaneous adipose tissue samples derived from 7 obese children and 8 lean children were selected for the analysis. Differentially expressed genes (DEGs) in samples from obese children compared with those from lean children were analyzed by the limma package. Gene ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes and Reactome pathway enrichment analyses for up and downregulated genes were performed. A protein-protein interaction (PPI) network was constructed with Cytoscape software and important genes associated with obesity were determined using IRegulon. A total of 199 DEGs (79 up and 120 downregulated genes) were identified in the samples of obese children compared with those from lean children. The PPI network was established with 103 nodes and 147 protein pairs. Matrix metalloproteinase 9 (MMP9) and acetyl-CoA carboxylase β (ACACB) were identified as hub genes in the PPI network and may therefore be marker genes for child obesity. In addition, upregulated DEGs were enriched in Reactome pathways associated with the immune system. Besides, MMP9 was upregulated in immune system processes as a GO term in the category Biological Processes. The results of the present study indicated that MMP9, ACACB and immune system pathways may have a significant role in child obesity.

Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile.

The present study aimed to screen for potential genes and subnetworks associated with pancreatic cancer (PC) using the gene expression profile. The expression profile GSE 16515 was downloaded from the Gene Expression Omnibus database, which included 36 PC tissue samples and 16 normal samples. Limma package in R language was used to screen differentially expressed genes (DEGs), which were grouped as up- and downregulated genes. Then, PFSNet was applied to perform subnetwork analysis for all the DEGs. Moreover, Gene Ontology (GO) and REACTOME pathway enrichment analysis of up- and downregulated genes was performed, followed by protein-protein interaction (PPI) network construction using Search Tool for the Retrieval of Interacting Genes Search Tool for the Retrieval of Interacting Genes. In total, 1,989 DEGs including 1,461 up- and 528 downregulated genes were screened out. Subnetworks including pancreatic cancer in PC tissue samples and intercellular adhesion in normal samples were identified, respectively. A total of 8 significant REACTOME pathways for upregulated DEGs, such as hemostasis and cell cycle, mitotic were identified. Moreover, 4 significant REACTOME pathways for downregulated DEGs, including regulation of β-cell development and transmembrane transport of small molecules were screened out. Additionally, DEGs with high connectivity degrees, such as CCNA2 (cyclin A2) and PBK (PDZ binding kinase), of the module in the protein-protein interaction network were mainly enriched with cell-division cycle. CCNA2 and PBK of the module and their relative pathway cell-division cycle, and two subnetworks (pancreatic cancer and intercellular adhesion subnetworks) may be pivotal for further understanding of the molecular mechanism of PC.