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High accuracy mutation detection in leukemia on a selected panel of cancer genes.

Kalender Atak Z, De Keersmaecker K, Gianfelici V, Geerdens E, Vandepoel R, Pauwels D, Porcu M, Lahortiga I, Brys V, Dirks WG, Quentmeier H, Cloos J, Cuppens H, Uyttebroeck A, Vandenberghe P, Cools J, Aerts S - PLoS ONE (2012)

Bottom Line: 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 confirmed mutations in known T-ALL drivers, including PHF6, NF1, FBXW7, NOTCH1, KRAS, NRAS, PIK3CA, and PTEN.Finally, we re-sequenced a small set of 39 candidate genes and identified recurrent mutations in TET1, SPRY3 and SPRY4.

View Article: PubMed Central - PubMed

Affiliation: Center for Human Genetics, KU Leuven, Leuven, Belgium.

ABSTRACT
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.

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Related in: MedlinePlus

SPRY4 mutations.(A) Sanger sequencing chromatograms showing confirmed SPRY4 variants. (B) Domain structure of the SPRY4 protein with indication of novel detected variants.
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pone-0038463-g005: SPRY4 mutations.(A) Sanger sequencing chromatograms showing confirmed SPRY4 variants. (B) Domain structure of the SPRY4 protein with indication of novel detected variants.

Mentions: Mutations in tyrosine phosphatase genes, that act as negative regulators of tyrosine signaling, were identified in many T-ALL cell lines and also in several T-ALL patients. Additional mutations in SPRY genes, negative regulators of the RAS/MAPK pathway, were also detected. We identified a homozygous variation in SPRY3 in one T-ALL patient sample, and 3 mutations in SPRY4 (2 mutations in cell lines and 1 somatically acquired mutation in a T-ALL patient sample). Sanger sequencing confirmed the presence of these mutations, but did not reveal any additional mutations of SPRY3/SPRY4 in 22 additional T-ALL cases, bringing the SPRY4 mutation frequency to 1/37 T-ALL patients and 2/18 T-ALL cell lines (Table S7, Figure 5).


High accuracy mutation detection in leukemia on a selected panel of cancer genes.

Kalender Atak Z, De Keersmaecker K, Gianfelici V, Geerdens E, Vandepoel R, Pauwels D, Porcu M, Lahortiga I, Brys V, Dirks WG, Quentmeier H, Cloos J, Cuppens H, Uyttebroeck A, Vandenberghe P, Cools J, Aerts S - PLoS ONE (2012)

SPRY4 mutations.(A) Sanger sequencing chromatograms showing confirmed SPRY4 variants. (B) Domain structure of the SPRY4 protein with indication of novel detected variants.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3366948&req=5

pone-0038463-g005: SPRY4 mutations.(A) Sanger sequencing chromatograms showing confirmed SPRY4 variants. (B) Domain structure of the SPRY4 protein with indication of novel detected variants.
Mentions: Mutations in tyrosine phosphatase genes, that act as negative regulators of tyrosine signaling, were identified in many T-ALL cell lines and also in several T-ALL patients. Additional mutations in SPRY genes, negative regulators of the RAS/MAPK pathway, were also detected. We identified a homozygous variation in SPRY3 in one T-ALL patient sample, and 3 mutations in SPRY4 (2 mutations in cell lines and 1 somatically acquired mutation in a T-ALL patient sample). Sanger sequencing confirmed the presence of these mutations, but did not reveal any additional mutations of SPRY3/SPRY4 in 22 additional T-ALL cases, bringing the SPRY4 mutation frequency to 1/37 T-ALL patients and 2/18 T-ALL cell lines (Table S7, Figure 5).

Bottom Line: 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 confirmed mutations in known T-ALL drivers, including PHF6, NF1, FBXW7, NOTCH1, KRAS, NRAS, PIK3CA, and PTEN.Finally, we re-sequenced a small set of 39 candidate genes and identified recurrent mutations in TET1, SPRY3 and SPRY4.

View Article: PubMed Central - PubMed

Affiliation: Center for Human Genetics, KU Leuven, Leuven, Belgium.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus