A Cytoscape app for motif enumeration with ISMAGS

Parys, Thomas Van; Melckenbeeck, Ine; Houbraken, Maarten; Audenaert, Pieter; Colle, Didier; Pickavet, Mario; Demeester, Piet; Peer, Yves Van de

doi:10.1093/bioinformatics/btw626

Cited by 27 publications

(13 citation statements)

References 12 publications

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“…In our study, PPI network of DEGs was constructed using STRING database, and an interaction with a combined score > 0.4 was considered statistically significant. Cytoscape (version 3.7.1) is an open source bioinformatics software platform for visualizing molecular interaction networks [ 15 ]. The plug-in Molecular Complex Detection (MCODE) (version 1.5.1) of Cytoscape is an APP for clustering a given network based on topology to find densely connected regions [ 16 ].…”

Section: Methodsmentioning

confidence: 99%

Identifying the novel key genes in renal cell carcinoma by bioinformatics analysis and cell experiments

Chen

Wen

et al. 2020

Cancer Cell Int

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Background: Although major driver gene have been identified, the complex molecular heterogeneity of renal cell cancer (RCC) remains unclear. Therefore, more relevant genes need to be identified to explain the pathogenesis of renal cancer. Methods: Microarray datasets GSE781, GSE6344, GSE53000 and GSE68417 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by employing GEO2R tool, and function enrichment analyses were performed by using DAVID. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using STRING and Cytoscape. Survival analysis was performed using GEPIA. Differential expression was verified in Oncomine. Cell experiments (cell viability assays, transwell migration and invasion assays, wound healing assay, flow cytometry) were utilized to verify the roles of the hub genes on the proliferation of kidney cancer cells (A498 and OSRC-2 cell lines). Results: A total of 215 DEGs were identified from four datasets. Six hub gene (SUCLG1, PCK2, GLDC, SLC12A1, ATP1A1, PDHA1) were identified and the overall survival time of patients with RCC were significantly shorter. The expression levels of these six genes were significantly decreased in six RCC cell lines(A498, OSRC-2, 786-O, Caki-1, ACHN, 769-P) compared to 293t cell line. The expression level of both mRNA and protein of these genes were downregulated in RCC samples compared to those in paracancerous normal tissues. Cell viability assays showed that overexpressions of SUCLG1, PCK2, GLDC significantly decreased proliferation of RCC. Transwell migration, invasion, wound healing assay showed overexpression of three genes(SUCLG1, PCK2, GLDC) significantly inhibited the migration, invasion of RCC. Flow cytometry analysis showed that overexpression of three genes(SUCLG1, PCK2, GLDC) induced G1/S/ G2 phase arrest of RCC cells. Conclusion: Based on our current findings, it is concluded that SUCLG1, PCK2, GLDC may serve as a potential prognostic marker of RCC.

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Section: Methodsmentioning

confidence: 99%

Identifying the novel key genes in renal cell carcinoma by bioinformatics analysis and cell experiments

Chen

Wen

et al. 2020

Cancer Cell Int

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“…A combined score of >0.4 was considered to indicate statistical significance. Cytoscape (version 3.6.1), which is a software platform for bioinformatics analysis (22), was used for visualizing PPI.…”

Section: Methodsmentioning

confidence: 99%

Expression and potential prognostic value of histone family gene signature in breast cancer

et al. 2019

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Breast cancer (BC) is the most common type of malignancy among females worldwide. Histone modifications, which are the major post-translational modifications, have a significant role in cancer development and prognosis. However, whether histone family genes may serve as potential prognostic biomarkers for BC patients has remained elusive. In the present study, RNA-sequencing data were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed genes were identified and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway functional enrichment analysis was performed. As histone family genes have been reported to be associated with cervical cancer, the present study hypothesized that histone family genes are associated with gynecological tumors. Histone family genes, including histone cluster 1 H1A family member B (HIST1H1B), HIST1H2AJ, HIST1H2AM, HIST1H2BI, HIST1H2BO, HIST1H3B, HIST1H3F, HIST1H3H, HIST1H4C and HIST1H4D, were upregulated and identified as hub genes in the protein-protein interaction network. In addition, Oncomine and the Human Protein Atlas were used to further verify the expression levels of histone gene sets. The PrognoScan database was then used to investigate the association between expression and prognostic value regarding cancer patient survival. The present results indicated that higher expression of histone gene sets was associated with poor overall survival, relapse-free survival and distant metastasis-free survival of BC patients. The differential expression of histone family genes between BC and normal samples was validated by reverse transcription-quantitative PCR. Finally, to determine the clinical role of histone family genes in BC, the correlations between histone family genes expression and clinical characteristics were investigated through data collected from TCGA. Therefore, the present study indicates that histone gene sets may be used as prognostic factors for survival prediction for BC patients.

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“…The degree of a gene was determined as the number of the edges possessed by a node. The topological properties of the networks were analyzed using Cytoscape software 3.6.0 ( cytoscape.org/ ) ( 17 ).…”

Section: Methodsmentioning

confidence: 99%

Prognostic significance of microsatellite instability‑associated pathways and genes in gastric cancer

Hang

Wang

et al. 2018

Int J Mol Med

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The aim of the present study was to reveal the potential molecular mechanisms of microsatellite instability (MSI) on the prognosis of gastric cancer (GC). The investigation was performed based on an RNAseq expression profiling dataset downloaded from The Cancer Genome Atlas, including 64 high-level MSI (MSI-H) GC samples, 44 low-level MSI (MSI-L) GC samples and 187 stable microsatellite (MSI-S) GC samples. Differentially expressed genes (DEGs) were identified between the MSI-H, MSI-L and MSI-S samples. Pathway enrichment analysis was performed for the identified DEGs and the pathway deviation scores of the significant enrichment pathways were calculated. A Multi-Layer Perceptron (MLP) classifier, based on the different pathways associated with the MSI statuses was constructed for predicting the outcome of patients with GC, which was validated in another independent dataset. A total of 190 DEGs were selected between the MSI-H, MSI-L and MSI-S samples. The MLP classifier was established based on the deviation scores of 10 significant pathways, among which antigen processing and presentation, and inflammatory bowel disease pathways were significantly enriched with HLA-DRB5, HLA-DMA, HLA-DQA1 and HLA-DRA; the measles, toxoplasmosis and herpes simplex infection pathways were significantly enriched with Janus kinase 2 (JAK2), caspase-8 (CASP8) and Fas. The classifier performed well on an independent validation set with 100 GC samples. Taken together, the results indicated that MSI status may affect GC prognosis, partly through the antigen processing and presentation, inflammatory bowel disease, measles, toxoplasmosis and herpes simplex infection pathways. HLA-DRB5, HLA-DMA, HLA-DQA1, HLA-DRA, JAK2, CASP8 and Fas may be predictive factors for prognosis in GC.

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A Cytoscape app for motif enumeration with ISMAGS

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 27 publications

References 12 publications

Identifying the novel key genes in renal cell carcinoma by bioinformatics analysis and cell experiments

Identifying the novel key genes in renal cell carcinoma by bioinformatics analysis and cell experiments

Expression and potential prognostic value of histone family gene signature in breast cancer

Prognostic significance of microsatellite instability‑associated pathways and genes in gastric cancer

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