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Functional and protein‑protein interaction network analysis of colorectal cancer induced by ulcerative colitis.

Dai Y, Jiang JB, Wang YL, Jin ZT, Hu SY - Mol Med Rep (2015)

Bottom Line: Cluster 3 in UC had the highest GWGS, while the topological centrality of Cluster 3 in UC had the lowest degree and betweenness.PPI network analysis provided an effective way to estimate and understand the likelihood of the potential connections between proteins/genes.The results obtained following the use of GWGS to analyze differences between clusters did not agree with the topological degree and betweenness centrality, which indicated that gene fold change based GWGS was controversial with degree here in CRC and UC.

View Article: PubMed Central - PubMed

Affiliation: Department of General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong 250012, P.R. China.

ABSTRACT
Colorectal cancer (CRC) is a well‑recognized complication of ulcerative colitis (UC), and patients with UC have a higher incidence of CRC, compared with the general population. However, the properties of CRC induced by UC have not been clarified using an interaction network to analyze and compare gene sets. In the present study, six microarray datasets of CRC and UC were extracted from the Array Express database, and gene signatures were identified using the genome‑wide relative significance (GWRS) method. Functional analysis was performed based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Prediction of the genes and microRNA were performed using a hypergeometric method. A protein‑protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/proteins, and clusters were obtained through the Molecular Complex Detection algorithm. Topological centrality and a novel analyzing method, based on the rank value of GWGS, were used to characterize the biological importance of the clusters. A total of 217 differentially expressed (DE) genes of CRC were identified, 341 DE genes were identified in UC, and 62 common genes existed in the two. Several KEGG pathways were the same in CRC and UC. Collagenase, progesterone, heparin, urokinase, nadh and adenosine drugs demonstrated potential for use in treatment of CRC and UC. In the PPI network of CRC, 210 nodes and 752 edges were observed, wheras 314 nodes and 882 edges were identified in UC. Cluster 3 in UC had the highest GWGS, while the topological centrality of Cluster 3 in UC had the lowest degree and betweenness. PPI network analysis provided an effective way to estimate and understand the likelihood of the potential connections between proteins/genes. The results obtained following the use of GWGS to analyze differences between clusters did not agree with the topological degree and betweenness centrality, which indicated that gene fold change based GWGS was controversial with degree here in CRC and UC.

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Related in: MedlinePlus

Protein-protein interaction network of ulcerative colitis DE genes. A total of 314 nodes (purple ovals), 882 edges (lines between nodes) and 341 DE genes were identified, where nodes represent gene signatures and edges between nodes represent interaction between genes in the network. Among the nodes, CD44 exhibited the highest degree (52), followed by IL1B (50) and MMP9 (49). Node sizes correspond to the absolute values of the fold change of the DE genes. Edges were derived from he Search Tool for the Retrieval of Interacting Genes/proteins database. DE, differentially expressed.
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f2-mmr-12-04-4947: Protein-protein interaction network of ulcerative colitis DE genes. A total of 314 nodes (purple ovals), 882 edges (lines between nodes) and 341 DE genes were identified, where nodes represent gene signatures and edges between nodes represent interaction between genes in the network. Among the nodes, CD44 exhibited the highest degree (52), followed by IL1B (50) and MMP9 (49). Node sizes correspond to the absolute values of the fold change of the DE genes. Edges were derived from he Search Tool for the Retrieval of Interacting Genes/proteins database. DE, differentially expressed.

Mentions: In the present study, PPI networks were constructed for the DE genes in CRC and UC. In the network, nodes represent DE genes and edges between the nodes represent interaction of genes in the network. In the CRC network, there were 210 nodes and 752 edges, which included 217 DE genes (Fig. 1). Among the nodes, MT2A was identified with the highest degree at 42, followed by COL1A1 at 37 and COL1A2 at 37. In the UC network, there were 314 nodes, 882 edges and 341 DE genes (Fig. 2). CD44 was identified with the highest degree, at 52, followed by IL1B at 50 and MMP9 at 49.


Functional and protein‑protein interaction network analysis of colorectal cancer induced by ulcerative colitis.

Dai Y, Jiang JB, Wang YL, Jin ZT, Hu SY - Mol Med Rep (2015)

Protein-protein interaction network of ulcerative colitis DE genes. A total of 314 nodes (purple ovals), 882 edges (lines between nodes) and 341 DE genes were identified, where nodes represent gene signatures and edges between nodes represent interaction between genes in the network. Among the nodes, CD44 exhibited the highest degree (52), followed by IL1B (50) and MMP9 (49). Node sizes correspond to the absolute values of the fold change of the DE genes. Edges were derived from he Search Tool for the Retrieval of Interacting Genes/proteins database. DE, differentially expressed.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4581825&req=5

f2-mmr-12-04-4947: Protein-protein interaction network of ulcerative colitis DE genes. A total of 314 nodes (purple ovals), 882 edges (lines between nodes) and 341 DE genes were identified, where nodes represent gene signatures and edges between nodes represent interaction between genes in the network. Among the nodes, CD44 exhibited the highest degree (52), followed by IL1B (50) and MMP9 (49). Node sizes correspond to the absolute values of the fold change of the DE genes. Edges were derived from he Search Tool for the Retrieval of Interacting Genes/proteins database. DE, differentially expressed.
Mentions: In the present study, PPI networks were constructed for the DE genes in CRC and UC. In the network, nodes represent DE genes and edges between the nodes represent interaction of genes in the network. In the CRC network, there were 210 nodes and 752 edges, which included 217 DE genes (Fig. 1). Among the nodes, MT2A was identified with the highest degree at 42, followed by COL1A1 at 37 and COL1A2 at 37. In the UC network, there were 314 nodes, 882 edges and 341 DE genes (Fig. 2). CD44 was identified with the highest degree, at 52, followed by IL1B at 50 and MMP9 at 49.

Bottom Line: Cluster 3 in UC had the highest GWGS, while the topological centrality of Cluster 3 in UC had the lowest degree and betweenness.PPI network analysis provided an effective way to estimate and understand the likelihood of the potential connections between proteins/genes.The results obtained following the use of GWGS to analyze differences between clusters did not agree with the topological degree and betweenness centrality, which indicated that gene fold change based GWGS was controversial with degree here in CRC and UC.

View Article: PubMed Central - PubMed

Affiliation: Department of General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong 250012, P.R. China.

ABSTRACT
Colorectal cancer (CRC) is a well‑recognized complication of ulcerative colitis (UC), and patients with UC have a higher incidence of CRC, compared with the general population. However, the properties of CRC induced by UC have not been clarified using an interaction network to analyze and compare gene sets. In the present study, six microarray datasets of CRC and UC were extracted from the Array Express database, and gene signatures were identified using the genome‑wide relative significance (GWRS) method. Functional analysis was performed based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Prediction of the genes and microRNA were performed using a hypergeometric method. A protein‑protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/proteins, and clusters were obtained through the Molecular Complex Detection algorithm. Topological centrality and a novel analyzing method, based on the rank value of GWGS, were used to characterize the biological importance of the clusters. A total of 217 differentially expressed (DE) genes of CRC were identified, 341 DE genes were identified in UC, and 62 common genes existed in the two. Several KEGG pathways were the same in CRC and UC. Collagenase, progesterone, heparin, urokinase, nadh and adenosine drugs demonstrated potential for use in treatment of CRC and UC. In the PPI network of CRC, 210 nodes and 752 edges were observed, wheras 314 nodes and 882 edges were identified in UC. Cluster 3 in UC had the highest GWGS, while the topological centrality of Cluster 3 in UC had the lowest degree and betweenness. PPI network analysis provided an effective way to estimate and understand the likelihood of the potential connections between proteins/genes. The results obtained following the use of GWGS to analyze differences between clusters did not agree with the topological degree and betweenness centrality, which indicated that gene fold change based GWGS was controversial with degree here in CRC and UC.

Show MeSH
Related in: MedlinePlus