scholarly journals Integrative Network Analysis of Differentially Methylated and Expressed Genes for Biomarker Identification in Leukemia

2019 ◽  
Author(s):  
Robersy Sanchez ◽  
Sally A. Mackenzie
Keyword(s):  
Gene Expression ◽  
Signaling Pathway ◽  
Cytosine Methylation ◽  
Complex Disease ◽  
Lymphoblastic Leukemia ◽  
Integrated Analysis ◽  
Ras Signaling ◽  
Protein Protein Interaction ◽  
Diagnosis And Prognosis ◽  
Ppi Networks

AbstractGenome-wide DNA methylation and gene expression are commonly altered in pediatric acute lymphoblastic leukemia (PALL). Integrated analysis of cytosine methylation and expression datasets has the potential to provide deeper insights into the complex disease states and their causes than individual disconnected analyses. Studies of protein-protein interaction (PPI) networks of differentially methylated (DMGs) and expressed genes (DEGs) showed that gene expression and methylation consistently targeted the same gene pathways associated with cancer: Pathways in cancer, Ras signaling pathway, PI3K-Akt signaling pathway, and Rap1 signaling pathway, among others. Detected gene hubs and hub sub-networks are integrated by signature loci associated with cancer that include, for example, NOTCH1, RAC1, PIK3CD, BCL2, and EGFR. Statistical analysis disclosed a stochastic deterministic dependence between methylation and gene expression within the set of genes simultaneously identified as DEGs and DMGs, where larger values of gene expression changes are probabilistically associated with larger values of methylation changes. Concordance analysis of the overlap between enriched pathways in DEG and DMG datasets revealed statistically significant agreement between gene expression and methylation changes, reflecting a coordinated response of methylation and gene-expression regulatory systems. These results support the identification of reliable and stable biomarkers for cancer diagnosis and prognosis.

scholarly journals Interplay between PI3K/mTOR Signaling and IRE1a-XBP1 Promotes Survival of Pre-B NRASG12D all Cells Providing a Therapeutic Vulnerability for the "Undruggable" Driver RAS

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 47-48
Author(s):  
Iris Appelmann ◽  
Azam Salimi ◽  
Michael Huber ◽  
Mirle Schemionek ◽  
Margherita Vieri ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Signaling Pathway ◽  
Research Funding ◽  
Mtor Signaling ◽  
Ras Signaling ◽  
Genetic Ablation ◽  
Downstream Targets ◽  
Pharmacological Inhibition ◽  
Viable Cells

Background Activating RAS mutations drive around 30% of pre-B cell acute lymphoblastic leukemias (pre-B ALL) and are particularly common in relapsed ALL with a consecutively poor outcome. Recently published data demonstrated the critical role of the unfolded protein response (UPR) network, namely its IRE1α-XBP1 axis, for the survival of pre-B ALL cells: High expression of XBP1 confers a poor prognosis in pre B-ALL. However, the mechanism of XBP1 activation has not yet been elucidated in RAS mutated pre-B ALL. In this study, we aimed at identifying the molecular mechanism underlying pro-survival IRE1α-XBP1 signaling in RAS mutated pre-B ALL. Methods For a TET-ON inducible NRASG12D model in conditional Xbp1 knockout mice, we used interleukin 7 (IL-7)-dependent murine Mx1-Cre;Xbp1fl/fl pre-B cells transduced with a TET-ON inducible NRASG12D. We performed in vitro cell cycle and apoptosis assays with propidium iodide (PI) and annexin-V/PI. Furthermore, Western Blot and RT-qPCR were applied to analyze target gene expression. In a second approach, we focused on the signaling events following the blockade of RAS downstream targets using the MEK inhibitor PD0325901 and the dual PI3K/mTOR inhibitor BEZ235. We then assessed the efficacy of small molecule inhibition of IRE1α by MKC-8866 on XBP1 inactivation in RAS-mutated pre-B ALL cells either as a single treatment and in combination with the above mentioned drugs. Results We found the expression of Xbp1 significantly increased at the mRNA level with induction of NRASG12D. To determine the significance of Xbp1 in NRASG12D-driven pre-B ALL, we genetically deleted the IRE1α target Xbp1 using Cre-mediated deletion of Xbp1fl/fl in our mouse model of pre-B ALL. Genetic loss of Xbp1 significantly induced apoptosis (2.0-fold, p<0.0001) and caused cell cycle arrest (induction of G0/1, 1.7-fold, p=0.0003) along with an increase in the expression of CDK inhibitors, p21CIP1 and p27KIP1 at the protein level. Genetic ablation of Xbp1 abrogated IL-7 receptor (IL-7R) signaling by reducing the phosphorylation levels of STAT5-Y694 and JAK1-Y1022/Y1023. In an additional approach, we revealed that IL-7-deprived pre-B ALL cells reduce the mRNA expression of Xbp1s, indicating that Xbp1 acts as a downstream linchpin of the IL-7 receptor signaling pathway. Both IL-7-deprivation and genetic loss of Xbp1 increased the phosphorylation levels of ERK1/2-T202/Y204, AKT-S473 and the protein levels of NRASG12D and MAPK negative regulator DUSP6. Pharmacological inhibition of XBP1 activation using MKC-8866 resulted in similar effects on the expression of RAS downstream targets. We therefore tested MKC-8866 in combination with MEK inhibition by PD0325901 as a potential therapeutic strategy against pre-B ALL, which proved non-efficient. As a second option with therapeutic implications, we focused on the PI3K pathway which acts downstream of both the IL-7R and RAS signaling pathways. Strikingly, we observed that genetic ablation of Xbp1 (viable cells after 72 h, BEZ: 71.9 ± 9.0 vs BEZ+ Mx1-Cre;Xbp1fl/f: 10.0 ± 4.9) or pharmacological inhibition of its production with MKC-8866 (viable cells after five days, BEZ: 58.0 ± 6.8 vs BEZ+ MKC-8866: 13.3 ± 7.4) sensitizes pre-B ALL to dual inhibition of PI3K/mTOR with BEZ235. By applying the Bliss formula, we were able to show that BEZ235 in combination with MKC-8866 synergistically reduces the viability of RAS-mutated pre-B ALL cells. Gene expression analysis indicated that BEZ235 in combination with MKC-8866 fully blocked IL-7R signaling and caused an aberrant activation of Ras-Erk signaling. Targeting PI3K/mTOR signaling along with XBP1 inactivation increased expression of NRASG12D and its target DUSP6. In addition, we showed that combined therapy increased expression levels of p19Arf in RAS-mutated pre-B ALL, implicating cell senescence mediated by activated RAS signaling. Conclusion Our work strongly supports the hypothesis that XBP1 induces its positive effects on progression of pre-B ALL cells through the IL-7R signaling pathway. IL-7R signaling through its downstream effector XBP1 counteracts the RAS signaling pathway to promote leukemogenesis in pre-B ALL cells. Active XBP1 prevents the cytotoxic effects of BEZ235 in pre-B ALL cells, and hence targeting XBP1 in combination with dual PI3K/mTOR inhibition by BEZ235 appears as a promising targeted strategy against the "undruggable" driver RAS in NRASG12D-mutated pre-B ALL. Disclosures Brümmendorf: Janssen: Consultancy; Merck: Consultancy; Novartis: Consultancy, Other: travel, accommodation, expenses, Research Funding; Takeda: Consultancy; Pfizer: Consultancy, Honoraria, Other: Travel, Accommodation, Expenses, Research Funding.

scholarly journals NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis

2019 ◽  
Vol 47 (W1) ◽  
pp. W234-W241 ◽  
Author(s):  
Guangyan Zhou ◽  
Othman Soufan ◽  
Jessica Ewald ◽  
Robert E W Hancock ◽  
Niladri Basu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Visual Analytics ◽  
Regulatory Networks ◽  
Meta Analysis ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Perform Gene Expression ◽  
And Performance

Abstract The growing application of gene expression profiling demands powerful yet user-friendly bioinformatics tools to support systems-level data understanding. NetworkAnalyst was first released in 2014 to address the key need for interpreting gene expression data within the context of protein-protein interaction (PPI) networks. It was soon updated for gene expression meta-analysis with improved workflow and performance. Over the years, NetworkAnalyst has been continuously updated based on community feedback and technology progresses. Users can now perform gene expression profiling for 17 different species. In addition to generic PPI networks, users can now create cell-type or tissue specific PPI networks, gene regulatory networks, gene co-expression networks as well as networks for toxicogenomics and pharmacogenomics studies. The resulting networks can be customized and explored in 2D, 3D as well as Virtual Reality (VR) space. For meta-analysis, users can now visually compare multiple gene lists through interactive heatmaps, enrichment networks, Venn diagrams or chord diagrams. In addition, users have the option to create their own data analysis projects, which can be saved and resumed at a later time. These new features are released together as NetworkAnalyst 3.0, freely available at https://www.networkanalyst.ca.

scholarly journals Outcomes of Children With BCR-ABL1–Like Acute Lymphoblastic Leukemia Treated With Risk-Directed Therapy Based on the Levels of Minimal Residual Disease

2014 ◽  
Vol 32 (27) ◽  
pp. 3012-3020 ◽  
Author(s):  
Kathryn G. Roberts ◽  
Deqing Pei ◽  
Dario Campana ◽  
Debbie Payne-Turner ◽  
Yongjin Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
Minimal Residual Disease ◽  
Kinase Inhibitors ◽  
Residual Disease ◽  
Lymphoblastic Leukemia ◽  
Remission Induction ◽  
Ras Signaling ◽  
Abl Tyrosine Kinase ◽  
Minimal Residual

Purpose BCR-ABL1–like acute lymphoblastic leukemia (ALL) is a recently identified B-cell ALL (B-ALL) subtype with poor outcome that exhibits a gene expression profile similar to BCR-ABL1-positive ALL but lacks the BCR-ABL1 fusion protein. We examined the outcome of children with BCR-ABL1–like ALL treated with risk-directed therapy based on minimal residual disease (MRD) levels during remission induction. Patients and Methods Among 422 patients with B-ALL enrolled onto the Total Therapy XV study between 2000 and 2007, 344 had adequate samples for gene expression profiling. Next-generation sequencing and/or analysis of genes known to be altered in B-ALL were performed in patients with BCR-ABL1–like ALL who had available material. Outcome was compared between patients with and those without BCR-ABL1–like ALL. Results Forty (11.6%) of the 344 patients had BCR-ABL1–like ALL. They were significantly more likely to be male, have Down syndrome, and have higher MRD levels on day 19 and at the end of induction than did other patients with B-ALL. Among 25 patients comprehensively studied for genetic abnormalities, 11 harbored a genomic rearrangement of CRLF2, six had fusion transcripts responsive to ABL tyrosine kinase inhibitors or JAK inhibitors, and seven had mutations involving the Ras signaling pathway. There were no significant differences in event-free survival (90.0% ± 4.7% [SE] v 88.4% ± 1.9% at 5 years; P = .41) or in overall survival (92.5% ± 4.2% v 95.1% ± 1.3% at 5 years; P = .41) between patients with and without BCR-ABL1–like ALL. Conclusion Patients who have BCR-ABL1–like ALL with poor initial treatment response can be salvaged with MRD-based risk-directed therapy and may benefit from identification of kinase-activating lesions for targeted therapies.

scholarly journals Key pathways are frequently mutated in high-risk childhood acute lymphoblastic leukemia: a report from the Children's Oncology Group

Blood ◽  
2011 ◽  
Vol 118 (11) ◽  
pp. 3080-3087 ◽  
Author(s):  
Jinghui Zhang ◽  
Charles G. Mullighan ◽  
Richard C. Harvey ◽  
Gang Wu ◽  
Xiang Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
High Risk ◽  
B Cell ◽  
High Frequency ◽  
Lymphoblastic Leukemia ◽  
Cell Development ◽  
B Cell Development ◽  
Ras Signaling ◽  
Somatic Alterations

Abstract We sequenced 120 candidate genes in 187 high-risk childhood B-precursor acute lymphoblastic leukemias, the largest pediatric cancer genome sequencing effort reported to date. Integrated analysis of 179 validated somatic sequence mutations with genome-wide copy number alterations and gene expression profiles revealed a high frequency of recurrent somatic alterations in key signaling pathways, including B-cell development/differentiation (68% of cases), the TP53/RB tumor suppressor pathway (54%), Ras signaling (50%), and Janus kinases (11%). Recurrent mutations were also found in ETV6 (6 cases), TBL1XR1 (3), CREBBP (3), MUC4 (2), ASMTL (2), and ADARB2 (2). The frequency of mutations within the 4 major pathways varied markedly across genetic subtypes. Among 23 leukemias expressing a BCR-ABL1-like gene expression profile, 96% had somatic alterations in B-cell development/differentiation, 57% in JAK, and 52% in both pathways, whereas only 9% had Ras pathway mutations. In contrast, 21 cases defined by a distinct gene expression profile coupled with focal ERG deletion rarely had B-cell development/differentiation or JAK kinase alterations but had a high frequency (62%) of Ras signaling pathway mutations. These data extend the range of genes that are recurrently mutated in high-risk childhood B-precursor acute lymphoblastic leukemia and highlight important new therapeutic targets for selected patient subsets.

scholarly journals Integrated analysis of cancer stem cells-associated lncRNA-miRNA-mRNA network for ovarian cancer via microarray and Gene Expression Omnibus database

2020 ◽  
Author(s):  
Zheng Li ◽  
Zhijiao Wang ◽  
Yingying Zhou
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Stem Cells ◽  
Stem Cell ◽  
Cancer Stem Cells ◽  
Signaling Pathway ◽  
Gene Expression Omnibus ◽  
Integrated Analysis ◽  
Cerna Network ◽  
Geo Database

Abstract Background: Cancer stem cells (CSCs) are associated with the recurrence, metastasis and chemoresistance of epithelial ovarian cancer. Competing endogenous RNAs (CeRNAs) play an important role in maintenance of ovarian cancer stem cell-like cells (OCSCs) characteristics. To construct a ceRNA regulatory network for OCSCs, microarray technology and Gene Expression Omnibus (GEO) database had been used. Human serous epithelial ovarian carcinoma cell line COC1 cells were treated with cisplatin and paclitaxel then maintained in stem cell conditions for 6 days to obtain CD117+/CD133+ cells (OCSCs). We identified the differentially expressed miRNAs (DEMs), lncRNA (DELs) and mRNA (DEGs) between OCSCs and COC1 by microarray and combined them with representative microarray profiles in GEO Database. Results: According to the combination, 28 DEMs were identified at first, and 452 DEGs were obtained combining with the predicted targets of these miRNAs and our mRNA microarray results. Up-regulated DEGs of them were significantly enriched in ‘p53 signaling pathway’, ‘FoxO signaling pathway’ and ‘MicroRNAs in cancer’, whereas down-regulated DEGs were significantly enriched in ‘Adherens junction’ and ‘Hepatitis C’ pathway. 29 transcripts of 17 lncRNAs should be the ceRNAs of 10 of these miRNAs according to bioinformatics predicted results and lncRNA microarray. Finally, we obtained ceRNA network with 10 DEMs, 21 DEGs, and 25 transcripts of 13 DELs which should play an important role in maintenance of OCSCs characteristics. LINC00665-miR-146a-5p-NRP2 should be one of ceRNA pathways of the network. The qPCR results indicated that the expression of miR-146a-5p in OCSCs was lower than that in COC1, and LINC00665 shows the opposite trend. These results were consistent with the results of microarray partially. When LINC00665 expression was up-regulated in COC1, the cell proliferation ability enhanced, apoptosis rate reduced, and the percentage of G2/M phase cells increased. Conclusions: The ceRNA network we constructed may be involved in the stem cell characteristics maintenance of OCSCs and provide directions for further OCSCs research in the future, so as to assist the development and treatment of ovarian cancer.

scholarly journals Identification and validation of hub genes of synovial tissue for patients with osteoarthritis and rheumatoid arthritis

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Yanzhi Ge ◽  
Zuxiang Chen ◽  
Yanbin Fu ◽  
Xiujuan Xiao ◽  
Haipeng Xu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
Signaling Pathway ◽  
Quantitative Polymerase Chain Reaction ◽  
Functional Enrichment ◽  
Proximal Promoter ◽  
Integrated Analysis ◽  
Data Sets ◽  
Hub Genes ◽  
Multiple Gene

Abstract Background Osteoarthritis (OA) and rheumatoid arthritis (RA) were two major joint diseases with similar clinical phenotypes. This study aimed to determine the mechanistic similarities and differences between OA and RA by integrated analysis of multiple gene expression data sets. Methods Microarray data sets of OA and RA were obtained from the Gene Expression Omnibus (GEO). By integrating multiple gene data sets, specific differentially expressed genes (DEGs) were identified. The Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein–protein interaction (PPI) network analysis of DEGs were conducted to determine hub genes and pathways. The “Cell Type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT)” algorithm was employed to evaluate the immune infiltration cells (IICs) profiles in OA and RA. Moreover, mouse models of RA and OA were established, and selected hub genes were verified in synovial tissues with quantitative polymerase chain reaction (qPCR). Results A total of 1116 DEGs were identified between OA and RA. GO functional enrichment analysis showed that DEGs were enriched in regulation of cell morphogenesis involved in differentiation, positive regulation of neuron differentiation, nuclear speck, RNA polymerase II transcription factor complex, protein serine/threonine kinase activity and proximal promoter sequence-specific DNA binding. KEGG pathway analysis showed that DEGs were enriched in EGFR tyrosine kinase inhibitor resistance, ubiquitin mediated proteolysis, FoxO signaling pathway and TGF-beta signaling pathway. Immune cell infiltration analysis identified 9 IICs with significantly different distributions between OA and RA samples. qPCR results showed that the expression levels of the hub genes (RPS6, RPS14, RPS25, RPL11, RPL27, SNRPE, EEF2 and RPL19) were significantly increased in OA samples compared to their counterparts in RA samples (P < 0.05). Conclusion This large-scale gene analyses provided new insights for disease-associated genes, molecular mechanisms as well as IICs profiles in OA and RA, which may offer a new direction for distinguishing diagnosis and treatment between OA and RA.

scholarly journals Identification of Molecular Markers Associated with Diagnosis and Prognosis in Lung Adenocarcinoma by Bioinformatics Analysis

2020 ◽  
Author(s):  
Zimeng Wei ◽  
Linnan Zang ◽  
Min Zhao
Keyword(s):  
Gene Expression ◽  
Molecular Markers ◽  
Lung Adenocarcinoma ◽  
Expression Profiles ◽  
Diagnosis And Treatment ◽  
Analysis Tool ◽  
Hub Genes ◽  
Kegg Analysis ◽  
Diagnosis And Prognosis ◽  
Ppi Networks

Abstract Background：Lung adenocarcinoma (LUAD) is the main histological subtype of lung cancer. However, the molecular mechanism underlying LUAD is not yet clearly defined, but elucidating this process in detail would be of great significance for clinical diagnosis and treatment. Our aim is to identify the candidate key genes and pathways associated with diagnosis and prognosis in LUAD.Methods：In this study, three gene expression profiles GSE118370, GSE32863 and GSE43458 were retrieved from Gene Expression Omnibus database (GEO), and the common differentially expressed genes (DEGs) were identified by online GEO2R analysis tool. Subsequently, the enrichment analysis of function and signaling pathways of DEGs in LUAD were performed by gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomics (KEGG) analysis. The protein-protein interaction (PPI) networks of the DEGs were established through the Search Tool for the Retrieval of Interacting Genes (STRING) database and hub genes were screened by plug-in CytoHubba in Cytoscape. Afterwards, the miRNAs and the hub genes network was constructed via miRWalk. Finally, receiver operating characteristic (ROC) curve and Kaplan-Meier plotter were performed to analyze the diagnosis and prognosis efficacy of hub genes. Results: A total of 311 DEGs were identified, including 74 up-regulated and 238 down-regulated genes. GO analysis results showed that DEGs were mainly enriched in biological processes including composition of extracellular matrix, regulation of angiogenesis and so on. KEGG analysis results revealed DEGs were mainly enrolled in cell adhesion signaling pathway. Subsequently, 10 hub genes, CDC20, CENPF, TPX2, TOP2A, KIAA0101, CDCA7, ASPM, ECT2, UBE2T and COL1A1, were identified. And TOP2A, CDCA7, TPX2 and COL1A1 showed strong relationships with each other and the miRNAs nearby in miRNAs-mRNA network obtained by miRWalk website. Finally, all these 10 hub genes were found significantly related to the diagnosis and prognosis of LUAD (p<0.05). Conclusions: The identification of hub genes in this study will help us to understand the pathogenesis of LUAD, especially the molecular mechanisms of its development. Our results suggested that TOP2A, CDCA7, TPX2 and COL1A1 might present predictive value for the development and prognosis in LUAD, and might be used as potential molecular markers for the diagnosis and treatment of LUAD.

scholarly journals Potential genes and pathways associated with heterotopic ossification derived from analyses of gene expression profiles

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Zhanyu Yang ◽  
Delong Liu ◽  
Rui Guan ◽  
Xin Li ◽  
Yiwei Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Kinase ◽  
Heterotopic Ossification ◽  
Signaling Pathway ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Heterotopic Bone ◽  
Hub Genes ◽  
Ppi Networks

Abstract Background Heterotopic ossification (HO) represents pathological lesions that refer to the development of heterotopic bone in extraskeletal tissues around joints. This study investigates the genetic characteristics of bone marrow mesenchymal stem cells (BMSCs) from HO tissues and explores the potential pathways involved in this ailment. Methods Gene expression profiles (GSE94683) were obtained from the Gene Expression Omnibus (GEO), including 9 normal specimens and 7 HO specimens, and differentially expressed genes (DEGs) were identified. Then, protein–protein interaction (PPI) networks and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for further analysis. Results In total, 275 DEGs were differentially expressed, of which 153 were upregulated and 122 were downregulated. In the biological process (BP) category, the majority of DEGs, including EFNB3, UNC5C, TMEFF2, PTH2, KIT, FGF13, and WISP3, were intensively enriched in aspects of cell signal transmission, including axon guidance, negative regulation of cell migration, peptidyl-tyrosine phosphorylation, and cell-cell signaling. Moreover, KEGG analysis indicated that the majority of DEGs, including EFNB3, UNC5C, FGF13, MAPK10, DDIT3, KIT, COL4A4, and DKK2, were primarily involved in the mitogen-activated protein kinase (MAPK) signaling pathway, Ras signaling pathway, phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt) signaling pathway, and Wnt signaling pathway. Ten hub genes were identified, including CX3CL1, CXCL1, ADAMTS3, ADAMTS16, ADAMTSL2, ADAMTSL3, ADAMTSL5, PENK, GPR18, and CALB2. Conclusions This study presented novel insight into the pathogenesis of HO. Ten hub genes and most of the DEGs intensively involved in enrichment analyses may be new candidate targets for the prevention and treatment of HO in the future.

Integrating network topology, gene expression data and GO annotation information for protein complex prediction

2019 ◽  
Vol 17 (01) ◽  
pp. 1950001 ◽  
Author(s):  
Wei Zhang ◽  
Jia Xu ◽  
Yuanyuan Li ◽  
Xiufen Zou
Keyword(s):  
Gene Expression ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Protein Complex ◽  
Complex Disease ◽  
Protein Complexes ◽  
Expression Profiles ◽  
Interaction Network ◽  
Ppi Networks ◽  
Annotation Information

The prediction of protein complexes based on the protein interaction network is a fundamental task for the understanding of cellular life as well as the mechanisms underlying complex disease. A great number of methods have been developed to predict protein complexes based on protein–protein interaction (PPI) networks in recent years. However, because the high throughput data obtained from experimental biotechnology are incomplete, and usually contain a large number of spurious interactions, most of the network-based protein complex identification methods are sensitive to the reliability of the PPI network. In this paper, we propose a new method, Identification of Protein Complex based on Refined Protein Interaction Network (IPC-RPIN), which integrates the topology, gene expression profiles and GO functional annotation information to predict protein complexes from the reconstructed networks. To demonstrate the performance of the IPC-RPIN method, we evaluated the IPC-RPIN on three PPI networks of Saccharomycescerevisiae and compared it with four state-of-the-art methods. The simulation results show that the IPC-RPIN achieved a better result than the other methods on most of the measurements and is able to discover small protein complexes which have traditionally been neglected.

scholarly journals Repository of proposed pathways and protein–protein interaction networks in age-related macular degeneration

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Fran M. Pool ◽  
Christina Kiel ◽  
Luis Serrano ◽  
Philip J. Luthert
Keyword(s):  
Oxidative Stress ◽  
Macular Degeneration ◽  
Protein Interaction ◽  
Complex Disease ◽  
The Elderly ◽  
Geographic Atrophy ◽  
Age Related Macular Degeneration ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Age Related

AbstractAge-related macular degeneration (AMD) is one of the commonest causes of sight loss in the elderly population and to date there is no intervention that slows or prevents early AMD disease progressing to blinding neovascularization or geographic atrophy. AMD is a complex disease and factors proposed to contribute to the development and progression of disease include aging, genetics, epigenetics, oxidative stress, pro-inflammatory state, and life-style factors such as smoking, alcohol, and high fat diet. Here, we generate a knowledge repository of pathways and protein–protein interaction (PPI) networks likely to be implicated in AMD pathogenesis, such as complement activation, lipid trafficking and metabolism, vitamin A cycle, oxidative stress, proteostasis, bioenergetics, autophagy/mitophagy, extracellular matrix (ECM) turnover, and choroidal vascular dropout. Two disctinct clusters ermerged from the networks for parainflamation and ECM homeostasis, which may represent two different disease modules underlying AMD pathology. Our analyses also suggest that the disease manifests primarily in RPE/choroid and less in neural retina. The use of standardized syntax when generating maps of these biological processes (SBGN standard) and networks (PSI standard) enables visualization of complex information in graphical programs such as CellDesigner and Cytoscape and enhances reusability and extension of data. The ability to focus onto subnetworks, multiple visualizations and simulation options will enable the AMD research community to computationally model subnetworks or to test experimentally new hypotheses arising from connectivities in the AMD pathway map.

Sign in / Sign up

Export Citation Format

Share Document