Translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates.
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 tis...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2011-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3115972?pdf=render |
| _version_ | 1828814776285790208 |
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| author | Patrik L Ståhl Magnus K Bjursell Hovsep Mahdessian Sophia Hober Karin Jirström Joakim Lundeberg |
| author_facet | Patrik L Ståhl Magnus K Bjursell Hovsep Mahdessian Sophia Hober Karin Jirström Joakim Lundeberg |
| author_sort | Patrik L Ståhl |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-12T10:30:43Z |
| format | Article |
| id | doaj.art-151746f6f302499e8b3136ee9b3566ba |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-12T10:30:43Z |
| publishDate | 2011-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-151746f6f302499e8b3136ee9b3566ba2022-12-22T00:27:22ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-01-0166e2079410.1371/journal.pone.0020794Translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates.Patrik L StåhlMagnus K BjursellHovsep MahdessianSophia HoberKarin JirströmJoakim LundebergBiomarker 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.http://europepmc.org/articles/PMC3115972?pdf=render |
| spellingShingle | Patrik L Ståhl Magnus K Bjursell Hovsep Mahdessian Sophia Hober Karin Jirström Joakim Lundeberg Translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates. PLoS ONE |
| title | Translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates. |
| title_full | Translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates. |
| title_fullStr | Translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates. |
| title_full_unstemmed | Translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates. |
| title_short | Translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates. |
| title_sort | translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates |
| url | http://europepmc.org/articles/PMC3115972?pdf=render |
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