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Translational Database Selection and Multiplexed Sequence Capture for Up Front Filtering of Reliable Breast Cancer Biomarker Candidates

Stahl, Patrik L.; Bjursell, Magnus K.; Mahdessian, Hovsep; Hober, Sophia; Jirström, Karin LU and Lundeberg, Joakim (2011) In PLoS ONE 6(6).
Abstract
Biomarker identification is of utmost importance for the development of novel diagnostics and therapeutics. Here we make use of a translational database selection strategy, utilizing data from the Human Protein Atlas (HPA) on differentially expressed protein patterns in healthy and breast cancer tissues as a means to filter out potential biomarkers for underlying genetic causatives of the disease. DNA was isolated from ten breast cancer biopsies, and the protein coding and flanking non-coding genomic regions corresponding to the selected proteins were extracted in a multiplexed format from the samples using a single DNA sequence capture array. Deep sequencing revealed an even enrichment of the multiplexed samples and a great variation of... (More)
Biomarker identification is of utmost importance for the development of novel diagnostics and therapeutics. Here we make use of a translational database selection strategy, utilizing data from the Human Protein Atlas (HPA) on differentially expressed protein patterns in healthy and breast cancer tissues as a means to filter out potential biomarkers for underlying genetic causatives of the disease. DNA was isolated from ten breast cancer biopsies, and the protein coding and flanking non-coding genomic regions corresponding to the selected proteins were extracted in a multiplexed format from the samples using a single DNA sequence capture array. Deep sequencing revealed an even enrichment of the multiplexed samples and a great variation of genetic alterations in the tumors of the sampled individuals. Benefiting from the upstream filtering method, the final set of biomarker candidates could be completely verified through bidirectional Sanger sequencing, revealing a 40 percent false positive rate despite high read coverage. Of the variants encountered in translated regions, nine novel non-synonymous variations were identified and verified, two of which were present in more than one of the ten tumor samples. (Less)
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type
Contribution to journal
publication status
published
subject
in
PLoS ONE
volume
6
issue
6
publisher
Public Library of Science
external identifiers
  • wos:000291730000024
  • scopus:79958814978
ISSN
1932-6203
DOI
10.1371/journal.pone.0020794
language
English
LU publication?
yes
id
ff658a53-e629-4198-910b-734eee3e8bd5 (old id 2049440)
date added to LUP
2011-08-02 09:01:29
date last changed
2017-01-01 05:57:24
@article{ff658a53-e629-4198-910b-734eee3e8bd5,
  abstract     = {Biomarker identification is of utmost importance for the development of novel diagnostics and therapeutics. Here we make use of a translational database selection strategy, utilizing data from the Human Protein Atlas (HPA) on differentially expressed protein patterns in healthy and breast cancer tissues as a means to filter out potential biomarkers for underlying genetic causatives of the disease. DNA was isolated from ten breast cancer biopsies, and the protein coding and flanking non-coding genomic regions corresponding to the selected proteins were extracted in a multiplexed format from the samples using a single DNA sequence capture array. Deep sequencing revealed an even enrichment of the multiplexed samples and a great variation of genetic alterations in the tumors of the sampled individuals. Benefiting from the upstream filtering method, the final set of biomarker candidates could be completely verified through bidirectional Sanger sequencing, revealing a 40 percent false positive rate despite high read coverage. Of the variants encountered in translated regions, nine novel non-synonymous variations were identified and verified, two of which were present in more than one of the ten tumor samples.},
  author       = {Stahl, Patrik L. and Bjursell, Magnus K. and Mahdessian, Hovsep and Hober, Sophia and Jirström, Karin and Lundeberg, Joakim},
  issn         = {1932-6203},
  language     = {eng},
  number       = {6},
  publisher    = {Public Library of Science},
  series       = {PLoS ONE},
  title        = {Translational Database Selection and Multiplexed Sequence Capture for Up Front Filtering of Reliable Breast Cancer Biomarker Candidates},
  url          = {http://dx.doi.org/10.1371/journal.pone.0020794},
  volume       = {6},
  year         = {2011},
}