Network Properties of Cancer Prognostic Gene Signatures in the Human Protein Interactome
Prognostic gene signatures are critical in cancer prognosis assessments and their pinpoint treatments. However, their network properties remain unclear. Here, we obtained nine prognostic gene sets including 1439 prognostic genes of different cancers from related publications. Four network centraliti...
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doaj-dae1a23c53f44c5bb21b29bf2a2f87682020-11-25T00:42:12ZengMDPI AGGenes2073-44252020-02-0111324710.3390/genes11030247genes11030247Network Properties of Cancer Prognostic Gene Signatures in the Human Protein InteractomeJifeng Zhang0Shoubao Yan1Cheng Jiang2Zhicheng Ji3Chenrun Wang4Weidong Tian5School of Biological Engineering, Huainan Normal University, Huainan, Anhui Province 232001, ChinaSchool of Biological Engineering, Huainan Normal University, Huainan, Anhui Province 232001, ChinaSchool of Biological Engineering, Huainan Normal University, Huainan, Anhui Province 232001, ChinaDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland 21205, USASchool of Biological Engineering, Huainan Normal University, Huainan, Anhui Province 232001, ChinaSchool of Life Science, Institute of Biostatistics, Fudan University, Shanghai 2004333, ChinaPrognostic gene signatures are critical in cancer prognosis assessments and their pinpoint treatments. However, their network properties remain unclear. Here, we obtained nine prognostic gene sets including 1439 prognostic genes of different cancers from related publications. Four network centralities were used to examine the network properties of prognostic genes (PG) compared with other gene sets based on the Human Protein Reference Database (HPRD) and String networks. We also proposed three novel network measures for further investigating the network properties of prognostic gene sets (PGS) besides clustering coefficient. The results showed that PG did not occupy key positions in the human protein interaction network and were more similar to essential genes rather than cancer genes. However, PGS had significantly smaller intra-set distance (IAD) and inter-set distance (IED) in comparison with random sets (<i>p</i>-value < 0.001). Moreover, we also found that PGS tended to be distributed within network modules rather than between modules (<i>p</i>-value < 0.01), and the functional intersection of the modules enriched with PGS was closely related to cancer development and progression. Our research reveals the common network properties of cancer prognostic gene signatures in the human protein interactome. We argue that these are biologically meaningful and useful for understanding their molecular mechanism.https://www.mdpi.com/2073-4425/11/3/247prognostic genesprognostic genes setsnetwork propertyhuman protein interactomecancermodules |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jifeng Zhang Shoubao Yan Cheng Jiang Zhicheng Ji Chenrun Wang Weidong Tian |
spellingShingle |
Jifeng Zhang Shoubao Yan Cheng Jiang Zhicheng Ji Chenrun Wang Weidong Tian Network Properties of Cancer Prognostic Gene Signatures in the Human Protein Interactome Genes prognostic genes prognostic genes sets network property human protein interactome cancer modules |
author_facet |
Jifeng Zhang Shoubao Yan Cheng Jiang Zhicheng Ji Chenrun Wang Weidong Tian |
author_sort |
Jifeng Zhang |
title |
Network Properties of Cancer Prognostic Gene Signatures in the Human Protein Interactome |
title_short |
Network Properties of Cancer Prognostic Gene Signatures in the Human Protein Interactome |
title_full |
Network Properties of Cancer Prognostic Gene Signatures in the Human Protein Interactome |
title_fullStr |
Network Properties of Cancer Prognostic Gene Signatures in the Human Protein Interactome |
title_full_unstemmed |
Network Properties of Cancer Prognostic Gene Signatures in the Human Protein Interactome |
title_sort |
network properties of cancer prognostic gene signatures in the human protein interactome |
publisher |
MDPI AG |
series |
Genes |
issn |
2073-4425 |
publishDate |
2020-02-01 |
description |
Prognostic gene signatures are critical in cancer prognosis assessments and their pinpoint treatments. However, their network properties remain unclear. Here, we obtained nine prognostic gene sets including 1439 prognostic genes of different cancers from related publications. Four network centralities were used to examine the network properties of prognostic genes (PG) compared with other gene sets based on the Human Protein Reference Database (HPRD) and String networks. We also proposed three novel network measures for further investigating the network properties of prognostic gene sets (PGS) besides clustering coefficient. The results showed that PG did not occupy key positions in the human protein interaction network and were more similar to essential genes rather than cancer genes. However, PGS had significantly smaller intra-set distance (IAD) and inter-set distance (IED) in comparison with random sets (<i>p</i>-value < 0.001). Moreover, we also found that PGS tended to be distributed within network modules rather than between modules (<i>p</i>-value < 0.01), and the functional intersection of the modules enriched with PGS was closely related to cancer development and progression. Our research reveals the common network properties of cancer prognostic gene signatures in the human protein interactome. We argue that these are biologically meaningful and useful for understanding their molecular mechanism. |
topic |
prognostic genes prognostic genes sets network property human protein interactome cancer modules |
url |
https://www.mdpi.com/2073-4425/11/3/247 |
work_keys_str_mv |
AT jifengzhang networkpropertiesofcancerprognosticgenesignaturesinthehumanproteininteractome AT shoubaoyan networkpropertiesofcancerprognosticgenesignaturesinthehumanproteininteractome AT chengjiang networkpropertiesofcancerprognosticgenesignaturesinthehumanproteininteractome AT zhichengji networkpropertiesofcancerprognosticgenesignaturesinthehumanproteininteractome AT chenrunwang networkpropertiesofcancerprognosticgenesignaturesinthehumanproteininteractome AT weidongtian networkpropertiesofcancerprognosticgenesignaturesinthehumanproteininteractome |
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