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Pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes
Large-scale cancer genome sequencing has enabled the catalogs of somatic mutations; however, the mutational impact on intrinsically disordered protein regions (IDRs) has not been systematically investigated to date. Here, we comprehensively characterized the mutational landscapes of IDRs and found t...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122534/ https://www.ncbi.nlm.nih.gov/pubmed/35061901 http://dx.doi.org/10.1093/nar/gkac028 |
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author | Zou, Haozhe Pan, Tao Gao, Yueying Chen, Renwei Li, Si Guo, Jing Tian, Zhanyu Xu, Gang Xu, Juan Ma, Yanlin Li, Yongsheng |
author_facet | Zou, Haozhe Pan, Tao Gao, Yueying Chen, Renwei Li, Si Guo, Jing Tian, Zhanyu Xu, Gang Xu, Juan Ma, Yanlin Li, Yongsheng |
author_sort | Zou, Haozhe |
collection | PubMed |
description | Large-scale cancer genome sequencing has enabled the catalogs of somatic mutations; however, the mutational impact on intrinsically disordered protein regions (IDRs) has not been systematically investigated to date. Here, we comprehensively characterized the mutational landscapes of IDRs and found that IDRs have higher mutation frequencies across diverse cancers. We thus developed a computational method, ROI-Driver, to identify putative driver genes enriching IDR and domain hotspots in cancer. Numerous well-known cancer-related oncogenes or tumor suppressors that play important roles in cancer signaling regulation, development and immune response were identified at a higher resolution. In particular, the incorporation of IDR structures helps in the identification of novel potential driver genes that play central roles in human protein–protein interaction networks. Interestingly, we found that the putative driver genes with IDR hotspots were significantly enriched with predicted phase separation propensities, suggesting that IDR mutations disrupt phase separation in key cellular pathways. We also identified an appreciable number of clinically relevant genes enriching IDR mutational hotspots that exhibited differential expression patterns and are associated with cancer patient survival. In summary, combinations of mutational effects on IDRs significantly increase the sensitivity of driver detection and are likely to open new therapeutic avenues for various cancers. |
format | Online Article Text |
id | pubmed-9122534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-91225342022-05-23 Pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes Zou, Haozhe Pan, Tao Gao, Yueying Chen, Renwei Li, Si Guo, Jing Tian, Zhanyu Xu, Gang Xu, Juan Ma, Yanlin Li, Yongsheng Nucleic Acids Res Methods Online Large-scale cancer genome sequencing has enabled the catalogs of somatic mutations; however, the mutational impact on intrinsically disordered protein regions (IDRs) has not been systematically investigated to date. Here, we comprehensively characterized the mutational landscapes of IDRs and found that IDRs have higher mutation frequencies across diverse cancers. We thus developed a computational method, ROI-Driver, to identify putative driver genes enriching IDR and domain hotspots in cancer. Numerous well-known cancer-related oncogenes or tumor suppressors that play important roles in cancer signaling regulation, development and immune response were identified at a higher resolution. In particular, the incorporation of IDR structures helps in the identification of novel potential driver genes that play central roles in human protein–protein interaction networks. Interestingly, we found that the putative driver genes with IDR hotspots were significantly enriched with predicted phase separation propensities, suggesting that IDR mutations disrupt phase separation in key cellular pathways. We also identified an appreciable number of clinically relevant genes enriching IDR mutational hotspots that exhibited differential expression patterns and are associated with cancer patient survival. In summary, combinations of mutational effects on IDRs significantly increase the sensitivity of driver detection and are likely to open new therapeutic avenues for various cancers. Oxford University Press 2022-01-21 /pmc/articles/PMC9122534/ /pubmed/35061901 http://dx.doi.org/10.1093/nar/gkac028 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Online Zou, Haozhe Pan, Tao Gao, Yueying Chen, Renwei Li, Si Guo, Jing Tian, Zhanyu Xu, Gang Xu, Juan Ma, Yanlin Li, Yongsheng Pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes |
title | Pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes |
title_full | Pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes |
title_fullStr | Pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes |
title_full_unstemmed | Pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes |
title_short | Pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes |
title_sort | pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122534/ https://www.ncbi.nlm.nih.gov/pubmed/35061901 http://dx.doi.org/10.1093/nar/gkac028 |
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