Comprehensive characterization of protein–protein interactions perturbed by disease mutations
| Autor: | Ruth A. Keri, Justin D. Lathia, Raul Rabadan, Elliott M. Antman, Felice C. Lightstone, Jessica A. Castrillon, Rui-Sheng Wang, Tong Hao, Marc Vidal, Zehui Liu, Yadi Zhou, David E. Hill, Hong Yue, Yuan Hou, Joseph Loscalzo, Jiansong Fang, Feixiong Cheng, Junfei Zhao, Yang Wang, William R. Martin, Jing Ma, Charis Eng, Weiqiang Lu, Jin Huang |
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| Rok vydání: | 2021 |
| Předmět: |
Genomics
Computational biology Biology Arginine medicine.disease_cause Article Germline Protein–protein interaction Histones 03 medical and health sciences 0302 clinical medicine Human interactome Interaction network Neoplasms Serine Genetics medicine Humans Disease Protein Interaction Maps Exome sequencing 030304 developmental biology rho Guanine Nucleotide Dissociation Inhibitor alpha 0303 health sciences Mutation Arachidonate 5-Lipoxygenase Genome Human Mechanism (biology) Computational Biology Reproducibility of Results Pharmacogenomic Testing Receptors LDL Proprotein Convertase 9 rhoA GTP-Binding Protein 030217 neurology & neurosurgery |
| Zdroj: | Nat Genet |
| ISSN: | 1546-1718 1061-4036 |
| Popis: | Technological and computational advances in genomics and interactomics have made it possible to identify how disease mutations perturb protein–protein interaction (PPI) networks within human cells. Here, we show that disease-associated germline variants are significantly enriched in sequences encoding PPI interfaces compared to variants identified in healthy participants from the projects 1000 Genomes and ExAC. Somatic missense mutations are also significantly enriched in PPI interfaces compared to noninterfaces in 10,861 tumor exomes. We computationally identified 470 putative oncoPPIs in a pan-cancer analysis and demonstrate that oncoPPIs are highly correlated with patient survival and drug resistance/sensitivity. We experimentally validate the network effects of 13 oncoPPIs using a systematic binary interaction assay, and also demonstrate the functional consequences of two of these on tumor cell growth. In summary, this human interactome network framework provides a powerful tool for prioritization of alleles with PPI-perturbing mutations to inform pathobiological mechanism- and genotype-based therapeutic discovery. Human disease mutations affect protein–protein interfaces in a three-dimensional structurally resolved interaction network. Predicted oncoPPIs in cancer correlate with survival and drug sensitivity, and affect growth in vitro, supporting their relevance to disease pathogenesis. |
| Databáze: | OpenAIRE |
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