High accuracy mutation detection in leukemia on a selected panel of cancer genes.
With the advent of whole-genome and whole-exome sequencing, high-quality catalogs of recurrently mutated cancer genes are becoming available for many cancer types. Increasing access to sequencing technology, including bench-top sequencers, provide the opportunity to re-sequence a limited set of canc...
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Public Library of Science (PLoS)
2012
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oai:doaj.org-article:7cc585744d7e4d0b81319ccdf94b75d12021-11-18T07:16:24ZHigh accuracy mutation detection in leukemia on a selected panel of cancer genes.1932-620310.1371/journal.pone.0038463https://doaj.org/article/7cc585744d7e4d0b81319ccdf94b75d12012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22675565/?tool=EBIhttps://doaj.org/toc/1932-6203With the advent of whole-genome and whole-exome sequencing, high-quality catalogs of recurrently mutated cancer genes are becoming available for many cancer types. Increasing access to sequencing technology, including bench-top sequencers, provide the opportunity to re-sequence a limited set of cancer genes across a patient cohort with limited processing time. Here, we re-sequenced a set of cancer genes in T-cell acute lymphoblastic leukemia (T-ALL) using Nimblegen sequence capture coupled with Roche/454 technology. First, we investigated how a maximal sensitivity and specificity of mutation detection can be achieved through a benchmark study. We tested nine combinations of different mapping and variant-calling methods, varied the variant calling parameters, and compared the predicted mutations with a large independent validation set obtained by capillary re-sequencing. We found that the combination of two mapping algorithms, namely BWA-SW and SSAHA2, coupled with the variant calling algorithm Atlas-SNP2 yields the highest sensitivity (95%) and the highest specificity (93%). Next, we applied this analysis pipeline to identify mutations in a set of 58 cancer genes, in a panel of 18 T-ALL cell lines and 15 T-ALL patient samples. We confirmed mutations in known T-ALL drivers, including PHF6, NF1, FBXW7, NOTCH1, KRAS, NRAS, PIK3CA, and PTEN. Interestingly, we also found mutations in several cancer genes that had not been linked to T-ALL before, including JAK3. Finally, we re-sequenced a small set of 39 candidate genes and identified recurrent mutations in TET1, SPRY3 and SPRY4. In conclusion, we established an optimized analysis pipeline for Roche/454 data that can be applied to accurately detect gene mutations in cancer, which led to the identification of several new candidate T-ALL driver mutations.Zeynep Kalender AtakKim De KeersmaeckerValentina GianfeliciEllen GeerdensRoel VandepoelDaphnie PauwelsMichaël PorcuIdoya LahortigaVanessa BrysWilly G DirksHilmar QuentmeierJacqueline CloosHarry CuppensAnne UyttebroeckPeter VandenbergheJan CoolsStein AertsPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 6, p e38463 (2012) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
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| topic |
Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Zeynep Kalender Atak Kim De Keersmaecker Valentina Gianfelici Ellen Geerdens Roel Vandepoel Daphnie Pauwels Michaël Porcu Idoya Lahortiga Vanessa Brys Willy G Dirks Hilmar Quentmeier Jacqueline Cloos Harry Cuppens Anne Uyttebroeck Peter Vandenberghe Jan Cools Stein Aerts High accuracy mutation detection in leukemia on a selected panel of cancer genes. |
| description |
With the advent of whole-genome and whole-exome sequencing, high-quality catalogs of recurrently mutated cancer genes are becoming available for many cancer types. Increasing access to sequencing technology, including bench-top sequencers, provide the opportunity to re-sequence a limited set of cancer genes across a patient cohort with limited processing time. Here, we re-sequenced a set of cancer genes in T-cell acute lymphoblastic leukemia (T-ALL) using Nimblegen sequence capture coupled with Roche/454 technology. First, we investigated how a maximal sensitivity and specificity of mutation detection can be achieved through a benchmark study. We tested nine combinations of different mapping and variant-calling methods, varied the variant calling parameters, and compared the predicted mutations with a large independent validation set obtained by capillary re-sequencing. We found that the combination of two mapping algorithms, namely BWA-SW and SSAHA2, coupled with the variant calling algorithm Atlas-SNP2 yields the highest sensitivity (95%) and the highest specificity (93%). Next, we applied this analysis pipeline to identify mutations in a set of 58 cancer genes, in a panel of 18 T-ALL cell lines and 15 T-ALL patient samples. We confirmed mutations in known T-ALL drivers, including PHF6, NF1, FBXW7, NOTCH1, KRAS, NRAS, PIK3CA, and PTEN. Interestingly, we also found mutations in several cancer genes that had not been linked to T-ALL before, including JAK3. Finally, we re-sequenced a small set of 39 candidate genes and identified recurrent mutations in TET1, SPRY3 and SPRY4. In conclusion, we established an optimized analysis pipeline for Roche/454 data that can be applied to accurately detect gene mutations in cancer, which led to the identification of several new candidate T-ALL driver mutations. |
| format |
article |
| author |
Zeynep Kalender Atak Kim De Keersmaecker Valentina Gianfelici Ellen Geerdens Roel Vandepoel Daphnie Pauwels Michaël Porcu Idoya Lahortiga Vanessa Brys Willy G Dirks Hilmar Quentmeier Jacqueline Cloos Harry Cuppens Anne Uyttebroeck Peter Vandenberghe Jan Cools Stein Aerts |
| author_facet |
Zeynep Kalender Atak Kim De Keersmaecker Valentina Gianfelici Ellen Geerdens Roel Vandepoel Daphnie Pauwels Michaël Porcu Idoya Lahortiga Vanessa Brys Willy G Dirks Hilmar Quentmeier Jacqueline Cloos Harry Cuppens Anne Uyttebroeck Peter Vandenberghe Jan Cools Stein Aerts |
| author_sort |
Zeynep Kalender Atak |
| title |
High accuracy mutation detection in leukemia on a selected panel of cancer genes. |
| title_short |
High accuracy mutation detection in leukemia on a selected panel of cancer genes. |
| title_full |
High accuracy mutation detection in leukemia on a selected panel of cancer genes. |
| title_fullStr |
High accuracy mutation detection in leukemia on a selected panel of cancer genes. |
| title_full_unstemmed |
High accuracy mutation detection in leukemia on a selected panel of cancer genes. |
| title_sort |
high accuracy mutation detection in leukemia on a selected panel of cancer genes. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2012 |
| url |
https://doaj.org/article/7cc585744d7e4d0b81319ccdf94b75d1 |
| work_keys_str_mv |
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| _version_ |
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