Network Properties of Cancer Prognostic Gene Signatures in the Human Protein Interactome.

Jifeng Zhang, Shoubao Yan, Cheng Jiang, Zhicheng Ji, Chenrun Wang, Weidong Tian

Abstract read

In one paragraph

Article in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

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1 · What the graph read from it

What it found

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jifeng ZhangSchool of Biological Engineering, Huainan Normal University, Huainan, Anhui Province 232001, China.

Shoubao YanSchool of Biological Engineering, Huainan Normal University, Huainan, Anhui Province 232001, China.

Cheng JiangSchool of Biological Engineering, Huainan Normal University, Huainan, Anhui Province 232001, China.

Zhicheng JiDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland 21205, USA.

Chenrun WangSchool of Biological Engineering, Huainan Normal University, Huainan, Anhui Province 232001, China.

Weidong TianSchool of Life Science, Institute of Biostatistics, Fudan University, Shanghai 2004333, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 (

Indexed as

PrognosisFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansMaleNeoplasm ProteinsNeoplasmsProtein Interaction MappingProtein Interaction MapsTranscriptomeNeoplasm Proteinscancerhuman protein interactomemodulesnetwork propertyprognostic genesprognostic genes sets

Identifiers

PMID32111006

DOI10.3390/genes11030247

PMCPMC7140842

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.