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Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma

Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to h...

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Detalles Bibliográficos
Autores principales: Li, Chaoxing, Liu, Li, Dinu, Valentin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5896492/
https://www.ncbi.nlm.nih.gov/pubmed/29666752
http://dx.doi.org/10.7717/peerj.4571
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author Li, Chaoxing
Liu, Li
Dinu, Valentin
author_facet Li, Chaoxing
Liu, Li
Dinu, Valentin
author_sort Li, Chaoxing
collection PubMed
description Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway’s topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher’s exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov–Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level.
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spelling pubmed-58964922018-04-17 Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma Li, Chaoxing Liu, Li Dinu, Valentin PeerJ Bioinformatics Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway’s topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher’s exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov–Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level. PeerJ Inc. 2018-04-09 /pmc/articles/PMC5896492/ /pubmed/29666752 http://dx.doi.org/10.7717/peerj.4571 Text en ©2018 Li et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Li, Chaoxing
Liu, Li
Dinu, Valentin
Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma
title Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma
title_full Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma
title_fullStr Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma
title_full_unstemmed Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma
title_short Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma
title_sort pathways of topological rank analysis (potra): a novel method to detect pathways involved in hepatocellular carcinoma
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5896492/
https://www.ncbi.nlm.nih.gov/pubmed/29666752
http://dx.doi.org/10.7717/peerj.4571
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AT dinuvalentin pathwaysoftopologicalrankanalysispotraanovelmethodtodetectpathwaysinvolvedinhepatocellularcarcinoma