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A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways.

ABSTRACT: Identifying dysregulated pathways from high-throughput experimental data in order to infer underlying biological insights is an important task. Current pathway-identification methods focus on single pathways in isolation; however, consideration of crosstalk between pathways could improve our understanding of alterations in biological states. We propose a novel method of pathway analysis based on global influence (PAGI) to identify dysregulated pathways, by considering both within-pathway effects and crosstalk between pathways. We constructed a global gene–gene network based on the relationships among genes extracted from a pathway database. We then evaluated the extent of differential expression for each gene, and mapped them to the global network. The random walk with restart algorithm was used to calculate the extent of genes affected by global influence. Finally, we used cumulative distribution functions to determine the significance values of the dysregulated pathways. We applied the PAGI method to five cancer microarray datasets, and compared our results with gene set enrichment analysis and five other methods. Based on these analyses, we demonstrated that PAGI can effectively identify dysregulated pathways associated with cancer, with strong reproducibility and robustness. We implemented PAGI using the freely available R-based and Web-based tools (http://bioinfo.hrbmu.edu.cn/PAGI).

SUBMITTER: Han J

PROVIDER: S-EPMC4277084 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways.

Han Junwei J Li Chunquan C Yang Haixiu H Xu Yanjun Y Zhang Chunlong C Ma Jiquan J Shi Xinrui X Liu Wei W Shang Desi D Yao Qianlan Q Zhang Yunpeng Y Su Fei F Feng Li L Li Xia X

Journal of the Royal Society, Interface 20150101 102

Identifying dysregulated pathways from high-throughput experimental data in order to infer underlying biological insights is an important task. Current pathway-identification methods focus on single pathways in isolation; however, consideration of crosstalk between pathways could improve our understanding of alterations in biological states. We propose a novel method of pathway analysis based on global influence (PAGI) to identify dysregulated pathways, by considering both within-pathway effects ...[more]

PMID: 25551156

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Project description:A comprehensive analysis to survey heme-binding proteins produced by the white-rot fungus Phanerochaete chrysosporium was achieved using a biotinylated heme-streptavidin beads system. Mitochondrial citrate synthase (PcCS), glyceraldehyde 3-phosphate dehydrogenase (PcGAPDH), and 2-Cys thioredoxin peroxidase (mammalian HBP23 homolog) were identified as putative heme-binding proteins. Among these, PcCS and PcGAPDH were further characterized using heterologously expressed recombinant proteins. Difference spectra of PcCS titrated with hemin exhibited an increase in the Soret absorbance at 414 nm, suggesting that the axial ligand of the heme is a His residue. The activity of PcCS was strongly inhibited by hemin with Ki oxaloacetate of 8.7 μM and Ki acetyl-CoA of 5.8 μM. Since the final step of heme biosynthesis occurred at the mitochondrial inner membrane, the inhibition of PcCS by heme is thought to be a physiological event. The inhibitory mode of the heme was similar to that of CoA analogues, suggesting that heme binds to PcCS at His347 at the AcCoA-CoA binding site, which was supported by the homology model of PcCS. PcGAPDH was also inhibited by heme, with a lower concentration than that for PcCS. This might be caused by the different location of these enzymes. From the integration of these phenomena, it was concluded that metabolic regulations by heme in the central metabolic and heme synthetic pathways occurred in the mitochondria and cytosol. This novel pathway crosstalk between the central metabolic and heme biosynthetic pathways, via a heme molecule, is important in regulating the metabolic balance (heme synthesis, ATP synthesis, flux balance of the tricarboxylic acid (TCA) cycle and cellular redox balance (NADPH production) during fungal aromatic degradation. KEY POINTS: • A comprehensive survey of heme-binding proteins in P. chrysosporium was achieved. • Several heme-binding proteins including CS and GAPDH were identified. • A novel metabolic regulation by heme in the central metabolic pathways was found.

Project description:BACKGROUND: Cancers, a group of multifactorial complex diseases, are generally caused by mutation of multiple genes or dysregulation of pathways. Identifying biomarkers that can characterize cancers would help to understand and diagnose cancers. Traditional computational methods that detect genes differentially expressed between cancer and normal samples fail to work due to small sample size and independent assumption among genes. On the other hand, genes work in concert to perform their functions. Therefore, it is expected that dysregulated pathways will serve as better biomarkers compared with single genes. RESULTS: In this paper, we propose a novel approach to identify dysregulated pathways in cancer based on a pathway interaction network. Our contribution is three-fold. Firstly, we present a new method to construct pathway interaction network based on gene expression, protein-protein interactions and cellular pathways. Secondly, the identification of dysregulated pathways in cancer is treated as a feature selection problem, which is biologically reasonable and easy to interpret. Thirdly, the dysregulated pathways are identified as subnetworks from the pathway interaction networks, where the subnetworks characterize very well the functional dependency or crosstalk between pathways. The benchmarking results on several distinct cancer datasets demonstrate that our method can obtain more reliable and accurate results compared with existing state of the art methods. Further functional analysis and independent literature evidence also confirm that our identified potential pathogenic pathways are biologically reasonable, indicating the effectiveness of our method. CONCLUSIONS: Dysregulated pathways can serve as better biomarkers compared with single genes. In this work, by utilizing pathway interaction networks and gene expression data, we propose a novel approach that effectively identifies dysregulated pathways, which can not only be used as biomarkers to diagnose cancers but also serve as potential drug targets in the future.

Dataset Information

A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways.

Publications

A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways.

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