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Distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids
Single nucleotide variations (SNVs) can result in loss or gain of protein functional sites. We analyzed the effects of SNVs on enzyme active sites, ligand binding sites, and various types of post translational modification (PTM) sites. We found that, for most types of protein functional sites, the S...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5296879/ https://www.ncbi.nlm.nih.gov/pubmed/28176830 http://dx.doi.org/10.1038/srep42169 |
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author | Pan, Yang Yan, Cheng Hu, Yu Fan, Yu Pan, Qing Wan, Quan Torcivia-Rodriguez, John Mazumder, Raja |
author_facet | Pan, Yang Yan, Cheng Hu, Yu Fan, Yu Pan, Qing Wan, Quan Torcivia-Rodriguez, John Mazumder, Raja |
author_sort | Pan, Yang |
collection | PubMed |
description | Single nucleotide variations (SNVs) can result in loss or gain of protein functional sites. We analyzed the effects of SNVs on enzyme active sites, ligand binding sites, and various types of post translational modification (PTM) sites. We found that, for most types of protein functional sites, the SNV pattern differs between germline and somatic mutations as well as between synonymous and non-synonymous mutations. From a total of 51,138 protein functional site affecting SNVs (pfsSNVs), a pan-cancer analysis revealed 142 somatic pfsSNVs in five or more cancer types. By leveraging patient information for somatic pfsSNVs, we identified 17 loss of functional site SNVs and 60 gain of functional site SNVs which are significantly enriched in patients with specific cancer types. Of the key pfsSNVs identified in our analysis above, we highlight 132 key pfsSNVs within 17 genes that are found in well-established cancer associated gene lists. For illustrating how key pfsSNVs can be prioritized further, we provide a use case where we performed survival analysis showing that a loss of phosphorylation site pfsSNV at position 105 in MEF2A is significantly associated with decreased pancreatic cancer patient survival rate. These 132 pfsSNVs can be used in developing genetic testing pipelines. |
format | Online Article Text |
id | pubmed-5296879 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-52968792017-02-13 Distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids Pan, Yang Yan, Cheng Hu, Yu Fan, Yu Pan, Qing Wan, Quan Torcivia-Rodriguez, John Mazumder, Raja Sci Rep Article Single nucleotide variations (SNVs) can result in loss or gain of protein functional sites. We analyzed the effects of SNVs on enzyme active sites, ligand binding sites, and various types of post translational modification (PTM) sites. We found that, for most types of protein functional sites, the SNV pattern differs between germline and somatic mutations as well as between synonymous and non-synonymous mutations. From a total of 51,138 protein functional site affecting SNVs (pfsSNVs), a pan-cancer analysis revealed 142 somatic pfsSNVs in five or more cancer types. By leveraging patient information for somatic pfsSNVs, we identified 17 loss of functional site SNVs and 60 gain of functional site SNVs which are significantly enriched in patients with specific cancer types. Of the key pfsSNVs identified in our analysis above, we highlight 132 key pfsSNVs within 17 genes that are found in well-established cancer associated gene lists. For illustrating how key pfsSNVs can be prioritized further, we provide a use case where we performed survival analysis showing that a loss of phosphorylation site pfsSNV at position 105 in MEF2A is significantly associated with decreased pancreatic cancer patient survival rate. These 132 pfsSNVs can be used in developing genetic testing pipelines. Nature Publishing Group 2017-02-08 /pmc/articles/PMC5296879/ /pubmed/28176830 http://dx.doi.org/10.1038/srep42169 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Pan, Yang Yan, Cheng Hu, Yu Fan, Yu Pan, Qing Wan, Quan Torcivia-Rodriguez, John Mazumder, Raja Distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids |
title | Distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids |
title_full | Distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids |
title_fullStr | Distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids |
title_full_unstemmed | Distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids |
title_short | Distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids |
title_sort | distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5296879/ https://www.ncbi.nlm.nih.gov/pubmed/28176830 http://dx.doi.org/10.1038/srep42169 |
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