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Uncovering packaging features of co-regulated modules based on human protein interaction and transcriptional regulatory networks.

Chen L, Wang H, Zhang L, Li W, Wang Q, Shang Y, He Y, He W, Li X, Tai J, Li X - BMC Bioinformatics (2010)

Bottom Line: Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways).Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods.Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes.

View Article: PubMed Central - HTML - PubMed

Affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Hei Longjiang Province, China. chenlina_2004@yahoo.com.cn

ABSTRACT

Background: Network co-regulated modules are believed to have the functionality of packaging multiple biological entities, and can thus be assumed to coordinate many biological functions in their network neighbouring regions.

Results: Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways). Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods.

Conclusions: Dysfunctions in co-regulated interactions often occur in the development of cancer. Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes. This was extended to causal dysfunctions of some complexes maintained by several physically interacting proteins, thus coordinating several metabolic pathways that directly underlie cancer.

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A sample module associated with 'biopolymer metabolic process'. Blue nodes represent TFs, red nodes represent cancer-mutated genes, and green nodes represent non-mutated genes. Interactions between TFs and proteins are blue; interactions between protein pairs are gray.
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Figure 4: A sample module associated with 'biopolymer metabolic process'. Blue nodes represent TFs, red nodes represent cancer-mutated genes, and green nodes represent non-mutated genes. Interactions between TFs and proteins are blue; interactions between protein pairs are gray.

Mentions: For all 96 co-regulated modules, we labelled TFs and proteins with their associated biological functions. We found that each module could work as an 'assembler' to assemble a set of genes with similar biological functions that were regulated by one or more TFs. For example, Figure 4 illustrates one module associated with a 'biopolymer metabolic process' (module 27). In this module, two groups of regulated subsets were identified: one group consisted of JUN and three tumour-mutated genes (CCND1, MSH2 and BRCA1). Recent studies have reported that JUN, a key cancer-related regulator, is important in carcinogenesis: inappropriate gene activation or numerous different genetic defects of JUN or its target genes could lead to cell growth inhibition, DNA damage or cell cycle delay, and these series of unexpected variations could finally have effects on tumour emergence, promotion and metastasis [22,23]. Another group contained five TFs (RPA1, RPA2, TP53BP1, FUBP1, and JUN) and their target genes (BRCA1 and BRCA2). BRCA1 and BRCA2 are important tumour suppressor genes, whose loss of function is closely associated with tumorigenesis [24,25]. Several studies have reported that these two genes are involved in DNA recombination and DNA repair [26-28]. A mutation in BRCA1 or BRCA2 compromises interaction with replication protein A (RPA1 and RPA2), and these two proteins are essential for DNA replication, repair, and recombination [29,30]. Lack of interaction first inhibits the recruitment of double-strand break repair proteins, then leads to an accumulation of carcinogenic DNA abnormalities, eventually causing predisposition to early onset cancer. These findings demonstrated that one or more TFs in co-regulated modules could package different genes with specific functions. Cancer-related modules could assemble a set of cancer-mutated genes and regulate specific biological functions associated with cancer, thus contributing to the pathogenesis of disease traits.


Uncovering packaging features of co-regulated modules based on human protein interaction and transcriptional regulatory networks.

Chen L, Wang H, Zhang L, Li W, Wang Q, Shang Y, He Y, He W, Li X, Tai J, Li X - BMC Bioinformatics (2010)

A sample module associated with 'biopolymer metabolic process'. Blue nodes represent TFs, red nodes represent cancer-mutated genes, and green nodes represent non-mutated genes. Interactions between TFs and proteins are blue; interactions between protein pairs are gray.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2914056&req=5

Figure 4: A sample module associated with 'biopolymer metabolic process'. Blue nodes represent TFs, red nodes represent cancer-mutated genes, and green nodes represent non-mutated genes. Interactions between TFs and proteins are blue; interactions between protein pairs are gray.
Mentions: For all 96 co-regulated modules, we labelled TFs and proteins with their associated biological functions. We found that each module could work as an 'assembler' to assemble a set of genes with similar biological functions that were regulated by one or more TFs. For example, Figure 4 illustrates one module associated with a 'biopolymer metabolic process' (module 27). In this module, two groups of regulated subsets were identified: one group consisted of JUN and three tumour-mutated genes (CCND1, MSH2 and BRCA1). Recent studies have reported that JUN, a key cancer-related regulator, is important in carcinogenesis: inappropriate gene activation or numerous different genetic defects of JUN or its target genes could lead to cell growth inhibition, DNA damage or cell cycle delay, and these series of unexpected variations could finally have effects on tumour emergence, promotion and metastasis [22,23]. Another group contained five TFs (RPA1, RPA2, TP53BP1, FUBP1, and JUN) and their target genes (BRCA1 and BRCA2). BRCA1 and BRCA2 are important tumour suppressor genes, whose loss of function is closely associated with tumorigenesis [24,25]. Several studies have reported that these two genes are involved in DNA recombination and DNA repair [26-28]. A mutation in BRCA1 or BRCA2 compromises interaction with replication protein A (RPA1 and RPA2), and these two proteins are essential for DNA replication, repair, and recombination [29,30]. Lack of interaction first inhibits the recruitment of double-strand break repair proteins, then leads to an accumulation of carcinogenic DNA abnormalities, eventually causing predisposition to early onset cancer. These findings demonstrated that one or more TFs in co-regulated modules could package different genes with specific functions. Cancer-related modules could assemble a set of cancer-mutated genes and regulate specific biological functions associated with cancer, thus contributing to the pathogenesis of disease traits.

Bottom Line: Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways).Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods.Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes.

View Article: PubMed Central - HTML - PubMed

Affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Hei Longjiang Province, China. chenlina_2004@yahoo.com.cn

ABSTRACT

Background: Network co-regulated modules are believed to have the functionality of packaging multiple biological entities, and can thus be assumed to coordinate many biological functions in their network neighbouring regions.

Results: Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways). Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods.

Conclusions: Dysfunctions in co-regulated interactions often occur in the development of cancer. Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes. This was extended to causal dysfunctions of some complexes maintained by several physically interacting proteins, thus coordinating several metabolic pathways that directly underlie cancer.

Show MeSH
Related in: MedlinePlus