ArticleBMC genomics2010
A comparative study of cancer proteins in the human protein-protein interaction network.
Article in BMC genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
51 citing papers in PubMed, 102 citations in OpenAlex.
- Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency.JCI insight · 2018Trial
- Pharmacogenomics of insulin-like growth factor-I generation during GH treatment in children with GH deficiency or Turner syndrome.The pharmacogenomics journal · 2014Trial
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- Exploring the Early Molecular Pathogenesis of Osteoarthritis Using Differential Network Analysis of Human Synovial Fluid.Molecular & cellular proteomics : MCP · 2024Article
- Computed cancer interactome explains the effects of somatic mutations in cancers.Protein science : a publication of the Protein Society · 2022Article
- Diabetes mellitus susceptibility with varied diseased phenotypes and its comparison with phenome interactome networks.World journal of clinical cases · 2022Review
- WINNER: A network biology tool for biomolecular characterization and prioritization.Frontiers in big data · 2022Article
- Characterization of the Survival Influential Genes in Carcinogenesis.International journal of molecular sciences · 2021Article
- Combinatorial analyses reveal cellular composition changes have different impacts on transcriptomic changes of cell type specific genes in Alzheimer's Disease.Scientific reports · 2021Article
- Network Properties of Cancer Prognostic Gene Signatures in the Human Protein Interactome.Genes · 2020Article
- Integrating molecular networks with genetic variant interpretation for precision medicine.Wiley interdisciplinary reviews. Systems biology and medicine · 2019Review
- Applications of molecular networks in biomedicine.Biology methods & protocols · 2019Review
- Natural Product Target Network Reveals Potential for Cancer Combination Therapies.Frontiers in pharmacology · 2019Article
- Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery.Molecules (Basel, Switzerland) · 2018Review
- Analyzing of Molecular Networks for Human Diseases and Drug Discovery.Current topics in medicinal chemistry · 2018Review
- Investigating MicroRNA and transcription factor co-regulatory networks in colorectal cancer.BMC bioinformatics · 2017Article
- Protein function in precision medicine: deep understanding with machine learning.FEBS letters · 2016Review
- Network analysis and juvenile idiopathic arthritis (JIA): a new horizon for the understanding of disease pathogenesis and therapeutic target identification.Pediatric rheumatology online journal · 2016Review
- Construction and analysis of protein-protein interaction networks based on proteomics data of prostate cancer.International journal of molecular medicine · 2016Article
- Coexpression network analysis of the genes regulated by two types of resistance responses to powdery mildew in wheat.Scientific reports · 2016Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
backgroundCancer is a complex disease. So far, many genes have been reported to involve in the development of cancer. Rather than the traditional approach to studying individual genes or loci, a systematic investigation of cancer proteins in the human protein-protein interaction network may provide important biological information for uncovering the molecular mechanisms of cancer and, potentially, other complex diseases.
resultsWe explored global and local network characteristics of the proteins encoded by cancer genes (cancer proteins) in the human interactome. We found that the network topology of the cancer proteins was much different from that of the proteins encoded by essential genes (essential proteins) or control genes (control proteins). Relative to the essential proteins or control proteins, cancer proteins tended to have higher degree, higher betweenness, shorter shortest-path distance, and weaker clustering coefficient in the human interactome. We further separated the cancer proteins into two groups (recessive and dominant cancer proteins) and compared their topological features. Recessive cancer proteins had higher betweenness than dominant cancer proteins, while their degree distribution and characteristic shortest path distance were also significantly different. Finally, we found that cancer proteins were not randomly distributed in the human interactome and they connected strongly with each other.
conclusionOur study revealed much stronger protein-protein interaction characteristics of cancer proteins relative to the essential proteins or control proteins in the whole human interactome. We also found stronger network characteristics of recessive than dominant cancer proteins. The results are helpful for cancer candidate gene prioritization and verification, biomarker discovery, and, ultimately, understanding the etiology of cancer at the systems biological level.
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Registered trials
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.