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Comprehensive characterization of protein–protein interactions perturbed by disease mutations

Open access
Cheng, Feixiong, Zhao, Junfei, Wang, Yang, Lu, Weiqiang, Liu, Zehui, Zhou, Yadi, Martin, William R., Wang, Ruisheng, Huang, Jin, Hao, Tong, Yue, Hong, Ma, Jing, Hou, Yuan, Castrillon, Jessica A., Fang, Jiansong, Lathia, Justin D., Keri, Ruth A., Lightstone, Felice C., Antman, Elliott Marshall, Rabadan, Raul, Hill, David E., Eng, Charis, Vidal, Marc, Loscalzo, Joseph·2021·Nature Genetics

Abstract

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.

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Metadata

Authors
Cheng, F., Zhao, J., Wang, Y., Lu, W., Liu, Z., Zhou, Y., Martin, W. R., Wang, R., Huang, J., Hao, T., Yue, H., Ma, J., Hou, Y., Castrillon, J. A., Fang, J., Lathia, J. D., Keri, R. A., Lightstone, F. C., Antman, E. M., Rabadan, R., Hill, D. E., Eng, C., Vidal, M., & Loscalzo, J.
Venue
Nature Genetics
Published
2021-02-08
Volume
53
Issue
3
Pages
342-353
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
OpenAlex
W3128572085
Cited by
227
References
15
FWCI
10.20
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Comprehensive characterization of protein–protein interactions perturbed by disease mutations. https://app.cochat.ai/papers/10.1038/s41588-020-00774-y
The paper
Cheng, F., Zhao, J., Wang, Y., Lu, W., Liu, Z., Zhou, Y., Martin, W. R., Wang, R., Huang, J., Hao, T., Yue, H., Ma, J., Hou, Y., Castrillon, J. A., Fang, J., Lathia, J. D., Keri, R. A., Lightstone, F. C., Antman, E. M., . . . Loscalzo, J. (2021). Comprehensive characterization of protein–protein interactions perturbed by disease mutations. Nature Genetics. https://doi.org/10.1038/s41588-020-00774-y

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.