Pathway Commons, a web resource for biological pathway data

Cerami, Ethan; Groß, Benjamin; Demir, Emek; Rodchenkov, Igor; Babur, Özgün; Anwar, Nadia; Schultz, Nikolaus; Bader, Gary D.; Sander, Chris

doi:10.1093/nar/gkq1039

Cited by 1,002 publications

(892 citation statements)

References 24 publications

(28 reference statements)

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“…The protein interaction network was constructed as previously described [52] from integration of the Human Protein Interaction Network (www.pathwaycommons.org) [53], the Human Protein Reference Database [54], the National Cancer Institute Pathway Interaction Database, the Interactome (www.ebi.ac. uk/intact/) and the Molecular Interaction Database [55].…”

Section: Construction Of the Protein Interaction Networkmentioning

confidence: 99%

β - catenin is central to DUX4 -driven network rewiring in facioscapulohumeral muscular dystrophy

Banerji

Knopp

Moyle

et al. 2015

J. R. Soc. Interface.

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Facioscapulohumeral muscular dystrophy (FSHD) is an incurable disease, characterized by skeletal muscle weakness and wasting. Genetically, FSHD is characterized by contraction or hypomethylation of repeat D4Z4 units on chromosome 4, which causes aberrant expression of the transcription factor DUX4 from the last repeat. Many genes have been implicated in FSHD pathophysiology, but an integrated molecular model is currently lacking. We developed a novel differential network methodology, Interactome Sparsification and Rewiring (InSpiRe), which detects network rewiring between phenotypes by integrating gene expression data with known protein interactions. Using InSpiRe, we performed a meta-analysis of multiple microarray datasets from FSHD muscle biopsies, then removed secondary rewiring using non-FSHD datasets, to construct a unified network of rewired interactions. Our analysis identified b-catenin as the main coordinator of FSHD-associated protein interaction signalling, with pathways including canonical Wnt, HIF1-a and TNF-a clearly perturbed. To detect transcriptional changes directly elicited by DUX4, gene expression profiling was performed using microarrays on murine myoblasts. This revealed that DUX4 significantly modified expression of the genes in our FSHD network. Furthermore, we experimentally confirmed that Wnt/ b-catenin signalling is affected by DUX4 in murine myoblasts. Thus, we provide the first unified molecular map of FSHD signalling, capable of uncovering pathomechanisms and guiding therapeutic development.

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Section: Construction Of the Protein Interaction Networkmentioning

confidence: 99%

β - catenin is central to DUX4 -driven network rewiring in facioscapulohumeral muscular dystrophy

Banerji

Knopp

Moyle

et al. 2015

J. R. Soc. Interface.

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“…These collections included, among others, the Human Protein Reference Database (HPRD), GO, Kyoto Encyclopedia of Genes and Genomes (KEGG), the Molecular Signature Database (MSigDB), the Pathway Commons and NCBI Entrez Gene databases. 14,[21][22][23][24][25][26][27][28][29][30] FGS whose expression altered most significantly upon HDACinhibition in DU-145 and PC3 cells across all conditions after correction for multiple testing (adjusted P value < 0.05, top five FGS or more in case of ties), were retrieved and are displayed in Figure 1. This approach enabled the identification of biological themes that are differentially expressed upon HDAC-inhibition across all conditions irrespective of the gene expression direction change (Fig.…”

Section: Analysis Of Functional Annotation (Afa) After Treatment Withmentioning

confidence: 99%

Analysis of the genomic response of human prostate cancer cells to histone deacetylase inhibitors

et al. 2013

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histone deacetylases (hDacs) have emerged as important targets for cancer treatment. hDac-inhibitors (hDacis) are well tolerated in patients and have been approved for the treatment of patients with cutaneous T-cell lymphoma (cTcL).To improve the clinical benefit of hDacis in solid tumors, combination strategies with hDacis could be employed. In this study, we applied analysis of Functional annotation (aFa) to provide a comprehensive list of genes and pathways affected upon hDaci-treatment in prostate cancer cells. This approach provides an unbiased and objective approach to high throughput data mining. By performing aFa on gene expression data from prostate cancer cell lines DU-145 (an hDaci-sensitive cell line) and pc3 (a relatively hDaci-resistant cell line) treated with hDacis valproic acid or vorinostat, we identified biological processes that are affected by hDacis and are therefore potential treatment targets for combination therapy. Our analysis revealed that hDac-inhibition resulted among others in upregulation of major histocompatibility complex (Mhc) genes and deregulation of the mitotic spindle checkpoint by downregulation of genes involved in mitosis. These findings were confirmed by aFa on publicly available data sets from hDaci-treated prostate cancer cells. In total, we analyzed 375 microarrays with hDaci treated and non-treated (control) prostate cancer cells. all results from this extensive analysis are provided as an online research source (available at the journal's website and at http:// luigimarchionni.org/hDacIs.html). By publishing this data, we aim to enhance our understanding of the cellular changes after hDac-inhibition, and to identify novel potential combination strategies with hDacis for the treatment of prostate cancer patients. Analysis of the genomic response of human prostate cancer cells to histone deacetylase inhibitors

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“…While there are more than 2300 articles for the keyword 'NRF2' in PubMed (as of January 2012), major protein-protein interaction resources (BioGRID, MINT, STRING, HPRD) contain only a few (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) interactors for NRF2. Besides one study on the global mapping of binding sites for NRF2 through ChIP-Seq profiling [10] and a specific network modeling approach on Nrf2 regulation in mouse lung [11], there is no large-scale collection of NRF2-regulated target genes.…”

Section: Introductionmentioning

confidence: 99%

The NRF2‐related interactome and regulome contain multifunctional proteins and fine‐tuned autoregulatory loops

et al. 2012

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a b s t r a c t NRF2 is a well-known, master transcription factor (TF) of oxidative and xenobiotic stress responses. Recent studies uncovered an even wider regulatory role of NRF2 influencing carcinogenesis, inflammation and neurodegeneration. Prompted by these advances here we present a systems-level resource for NRF2 interactome and regulome that includes 289 protein-protein, 7469 TF-DNA and 85 miRNA interactions. As systems-level examples of NRF2-related signaling we identified regulatory loops of NRF2 interacting proteins (e.g., JNK1 and CBP) and a fine-tuned regulatory system, where 35 TFs regulated by NRF2 influence 63 miRNAs that down-regulate NRF2. The presented network and the uncovered regulatory loops may facilitate the development of efficient, NRF2-based therapeutic agents.

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Pathway Commons, a web resource for biological pathway data

Cited by 1,002 publications

References 24 publications

β - catenin is central to DUX4 -driven network rewiring in facioscapulohumeral muscular dystrophy

β - catenin is central to DUX4 -driven network rewiring in facioscapulohumeral muscular dystrophy

Analysis of the genomic response of human prostate cancer cells to histone deacetylase inhibitors

The NRF2‐related interactome and regulome contain multifunctional proteins and fine‐tuned autoregulatory loops

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