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In silico SNP analysis of the breast cancer antigen NY-BR-1

BACKGROUND: Breast cancer is one of the most common malignancies with increasing incidences every year and a leading cause of death among women. Although early stage breast cancer can be effectively treated, there are limited numbers of treatment options available for patients with advanced and meta...

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Autores principales: Kosaloglu, Zeynep, Bitzer, Julia, Halama, Niels, Huang, Zhiqin, Zapatka, Marc, Schneeweiss, Andreas, Jäger, Dirk, Zörnig, Inka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116164/
https://www.ncbi.nlm.nih.gov/pubmed/27863482
http://dx.doi.org/10.1186/s12885-016-2924-7
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author Kosaloglu, Zeynep
Bitzer, Julia
Halama, Niels
Huang, Zhiqin
Zapatka, Marc
Schneeweiss, Andreas
Jäger, Dirk
Zörnig, Inka
author_facet Kosaloglu, Zeynep
Bitzer, Julia
Halama, Niels
Huang, Zhiqin
Zapatka, Marc
Schneeweiss, Andreas
Jäger, Dirk
Zörnig, Inka
author_sort Kosaloglu, Zeynep
collection PubMed
description BACKGROUND: Breast cancer is one of the most common malignancies with increasing incidences every year and a leading cause of death among women. Although early stage breast cancer can be effectively treated, there are limited numbers of treatment options available for patients with advanced and metastatic disease. The novel breast cancer associated antigen NY-BR-1 was identified by SEREX analysis and is expressed in the majority (>70%) of breast tumors as well as metastases, in normal breast tissue, in testis and occasionally in prostate tissue. The biological function and regulation of NY-BR-1 is up to date unknown. METHODS: We performed an in silico analysis on the genetic variations of the NY-BR-1 gene using data available in public SNP databases and the tools SIFT, Polyphen and Provean to find possible functional SNPs. Additionally, we considered the allele frequency of the found damaging SNPs and also analyzed data from an in-house sequencing project of 55 breast cancer samples for recurring SNPs, recorded in dbSNP. RESULTS: Over 2800 SNPs are recorded in the dbSNP and NHLBI ESP databases for the NY-BR-1 gene. Of these, 65 (2.07%) are synonymous SNPs, 191 (6.09%) are non-synoymous SNPs, and 2430 (77.48%) are noncoding intronic SNPs. As a result, 69 non-synoymous SNPs were predicted to be damaging by at least two, and 16 SNPs were predicted as damaging by all three of the used tools. The SNPs rs200639888, rs367841401 and rs377750885 were categorized as highly damaging by all three tools. Eight damaging SNPs are located in the ankyrin repeat domain (ANK), a domain known for its frequent involvement in protein-protein interactions. No distinctive features could be observed in the allele frequency of the analyzed SNPs. CONCLUSION: Considering these results we expect to gain more insights into the variations of the NY-BR-1 gene and their possible impact on giving rise to splice variants and therefore influence the function of NY-BR-1 in healthy tissue as well as in breast cancer.
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spelling pubmed-51161642016-11-25 In silico SNP analysis of the breast cancer antigen NY-BR-1 Kosaloglu, Zeynep Bitzer, Julia Halama, Niels Huang, Zhiqin Zapatka, Marc Schneeweiss, Andreas Jäger, Dirk Zörnig, Inka BMC Cancer Research Article BACKGROUND: Breast cancer is one of the most common malignancies with increasing incidences every year and a leading cause of death among women. Although early stage breast cancer can be effectively treated, there are limited numbers of treatment options available for patients with advanced and metastatic disease. The novel breast cancer associated antigen NY-BR-1 was identified by SEREX analysis and is expressed in the majority (>70%) of breast tumors as well as metastases, in normal breast tissue, in testis and occasionally in prostate tissue. The biological function and regulation of NY-BR-1 is up to date unknown. METHODS: We performed an in silico analysis on the genetic variations of the NY-BR-1 gene using data available in public SNP databases and the tools SIFT, Polyphen and Provean to find possible functional SNPs. Additionally, we considered the allele frequency of the found damaging SNPs and also analyzed data from an in-house sequencing project of 55 breast cancer samples for recurring SNPs, recorded in dbSNP. RESULTS: Over 2800 SNPs are recorded in the dbSNP and NHLBI ESP databases for the NY-BR-1 gene. Of these, 65 (2.07%) are synonymous SNPs, 191 (6.09%) are non-synoymous SNPs, and 2430 (77.48%) are noncoding intronic SNPs. As a result, 69 non-synoymous SNPs were predicted to be damaging by at least two, and 16 SNPs were predicted as damaging by all three of the used tools. The SNPs rs200639888, rs367841401 and rs377750885 were categorized as highly damaging by all three tools. Eight damaging SNPs are located in the ankyrin repeat domain (ANK), a domain known for its frequent involvement in protein-protein interactions. No distinctive features could be observed in the allele frequency of the analyzed SNPs. CONCLUSION: Considering these results we expect to gain more insights into the variations of the NY-BR-1 gene and their possible impact on giving rise to splice variants and therefore influence the function of NY-BR-1 in healthy tissue as well as in breast cancer. BioMed Central 2016-11-18 /pmc/articles/PMC5116164/ /pubmed/27863482 http://dx.doi.org/10.1186/s12885-016-2924-7 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Kosaloglu, Zeynep
Bitzer, Julia
Halama, Niels
Huang, Zhiqin
Zapatka, Marc
Schneeweiss, Andreas
Jäger, Dirk
Zörnig, Inka
In silico SNP analysis of the breast cancer antigen NY-BR-1
title In silico SNP analysis of the breast cancer antigen NY-BR-1
title_full In silico SNP analysis of the breast cancer antigen NY-BR-1
title_fullStr In silico SNP analysis of the breast cancer antigen NY-BR-1
title_full_unstemmed In silico SNP analysis of the breast cancer antigen NY-BR-1
title_short In silico SNP analysis of the breast cancer antigen NY-BR-1
title_sort in silico snp analysis of the breast cancer antigen ny-br-1
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116164/
https://www.ncbi.nlm.nih.gov/pubmed/27863482
http://dx.doi.org/10.1186/s12885-016-2924-7
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