ArticlePLoS genetics2021
Network-based protein-protein interaction prediction method maps perturbations of cancer interactome.
Article in PLoS genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of the Application of Graph Neural Networks to Extract Candidate Genes and Biological Associations.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2025Pooled it
- Integrated Interactomics Reveals Novel Protein Associations: The FOXA1-PBX1 Complex as a Case Study.bioRxiv : the preprint server for biology · 2026Article
- Graph and Hypergraph Theories Applied to Dynamic Protein-Protein Interaction Network Analysis, and Deep-Learning Frameworks for Protein Complex Network Prediction.International journal of molecular sciences · 2026Review
- The role of protein embeddings for protein-protein interaction prediction with graph neural networks.Briefings in bioinformatics · 2026Article
- CancerHubs Data Explorer: a web application for investigating mutation-enriched protein interaction hubs in human cancers.BioData mining · 2026Article
- Dual-protein embedding-based graph model with dynamic attention for interaction prediction.Briefings in bioinformatics · 2025Article
- CancerHubs: a systematic data mining and elaboration approach for identifying novel cancer-related protein interaction hubs.Briefings in bioinformatics · 2024Article
- Exploring treatment options in cancer: Tumor treatment strategies.Signal transduction and targeted therapy · 2024Review
- Article
- Inferring a directed acyclic graph of phenotypes from GWAS summary statistics.bioRxiv : the preprint server for biology · 2023Article
- Disruptor: Computational identification of oncogenic mutants disrupting protein-protein and protein-DNA interactions.Communications biology · 2023Article
- Targeting stressor-induced dysfunctions in protein-protein interaction networks via epichaperomes.Trends in pharmacological sciences · 2023Review
- Co-Immunoprecipitation (Co-Ip) in Mammalian Cells.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Review
- Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical Constrains.Cells · 2022Article
- A systemic study on the vulnerability and fatality of prostate cancer patients towards COVID-19 through analysis of the TMPRSS2, CXCL10 and their co-expressed genes.Genomics & informatics · 2022Article
- Article
- The RNA interactome in the Hallmarks of Cancer.Wiley interdisciplinary reviews. RNAReview
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5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The perturbations of protein-protein interactions (PPIs) were found to be the main cause of cancer. Previous PPI prediction methods which were trained with non-disease general PPI data were not compatible to map the PPI network in cancer. Therefore, we established a novel cancer specific PPI prediction method dubbed NECARE, which was based on relational graph convolutional network (R-GCN) with knowledge-based features. It achieved the best performance with a Matthews correlation coefficient (MCC) = 0.84±0.03 and an F1 = 91±2% compared with other methods. With NECARE, we mapped the cancer interactome atlas and revealed that the perturbations of PPIs were enriched on 1362 genes, which were named cancer hub genes. Those genes were found to over-represent with mutations occurring at protein-macromolecules binding interfaces. Furthermore, over 56% of cancer treatment-related genes belonged to hub genes and they were significantly related to the prognosis of 32 types of cancers. Finally, by coimmunoprecipitation, we confirmed that the NECARE prediction method was highly reliable with a 90% accuracy. Overall, we provided the novel network-based cancer protein-protein interaction prediction method and mapped the perturbation of cancer interactome. NECARE is available at: https://github.com/JiajunQiu/NECARE.
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