Genetic Risk Prediction for Normal-Karyotype Acute Myeloid Leukemia Using Whole-Exome Sequencing
Normal-karyotype acute myeloid leukemia (NK-AML) is a highly malignant and cytogenetically heterogeneous hematologic cancer. We searched for somatic mutations from 10 pairs of tumor and normal cells by using a highly efficient and reliable analysis workflow for whole-exome sequencing data and perfor...
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BioMed Central
2013-03-01
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| Series: | Genomics & Informatics |
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| Online Access: | http://genominfo.org/upload/pdf/gni-11-46.pdf |
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| author | Seong Gu Heo Eun Pyo Hong Ji Wan Park |
| author_facet | Seong Gu Heo Eun Pyo Hong Ji Wan Park |
| author_sort | Seong Gu Heo |
| collection | DOAJ |
| description | Normal-karyotype acute myeloid leukemia (NK-AML) is a highly malignant and cytogenetically heterogeneous hematologic cancer. We searched for somatic mutations from 10 pairs of tumor and normal cells by using a highly efficient and reliable analysis workflow for whole-exome sequencing data and performed association tests between the NK-AML and somatic mutations. We identified 21 nonsynonymous single nucleotide variants (SNVs) located in a coding region of 18 genes. Among them, the SNVs of three leukemia-related genes (MUC4, CNTNAP2, and GNAS) reported in previous studies were replicated in this study. We conducted stepwise genetic risk score (GRS) models composed of the NK-AML susceptible variants and evaluated the prediction accuracy of each GRS model by computing the area under the receiver operating characteristic curve (AUC). The GRS model that was composed of five SNVs (rs75156964, rs56213454, rs6604516, rs10888338, and rs2443878) showed 100% prediction accuracy, and the combined effect of the three reported genes was validated in the current study (AUC, 0.98; 95% confidence interval, 0.92 to 1.00). Further study with large sample sizes is warranted to validate the combined effect of these somatic point mutations, and the discovery of novel markers may provide an opportunity to develop novel diagnostic and therapeutic targets for NK-AML. |
| format | Article |
| id | doaj-art-58d15c0e349b470c831a566db0d6fc8a |
| institution | Kabale University |
| issn | 1598-866X 2234-0742 |
| language | English |
| publishDate | 2013-03-01 |
| publisher | BioMed Central |
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| series | Genomics & Informatics |
| spelling | doaj-art-58d15c0e349b470c831a566db0d6fc8a2025-02-03T00:00:52ZengBioMed CentralGenomics & Informatics1598-866X2234-07422013-03-01111465110.5808/GI.2013.11.1.4677Genetic Risk Prediction for Normal-Karyotype Acute Myeloid Leukemia Using Whole-Exome SequencingSeong Gu Heo0Eun Pyo Hong1Ji Wan Park2Department of Medical Genetics, Hallym University College of Medicine, Chuncheon 200-702, Korea.Department of Medical Genetics, Hallym University College of Medicine, Chuncheon 200-702, Korea.Department of Medical Genetics, Hallym University College of Medicine, Chuncheon 200-702, Korea.Normal-karyotype acute myeloid leukemia (NK-AML) is a highly malignant and cytogenetically heterogeneous hematologic cancer. We searched for somatic mutations from 10 pairs of tumor and normal cells by using a highly efficient and reliable analysis workflow for whole-exome sequencing data and performed association tests between the NK-AML and somatic mutations. We identified 21 nonsynonymous single nucleotide variants (SNVs) located in a coding region of 18 genes. Among them, the SNVs of three leukemia-related genes (MUC4, CNTNAP2, and GNAS) reported in previous studies were replicated in this study. We conducted stepwise genetic risk score (GRS) models composed of the NK-AML susceptible variants and evaluated the prediction accuracy of each GRS model by computing the area under the receiver operating characteristic curve (AUC). The GRS model that was composed of five SNVs (rs75156964, rs56213454, rs6604516, rs10888338, and rs2443878) showed 100% prediction accuracy, and the combined effect of the three reported genes was validated in the current study (AUC, 0.98; 95% confidence interval, 0.92 to 1.00). Further study with large sample sizes is warranted to validate the combined effect of these somatic point mutations, and the discovery of novel markers may provide an opportunity to develop novel diagnostic and therapeutic targets for NK-AML.http://genominfo.org/upload/pdf/gni-11-46.pdfacute myeloid leukemiaDNA sequence analysisgenetic variationrisk assessment |
| spellingShingle | Seong Gu Heo Eun Pyo Hong Ji Wan Park Genetic Risk Prediction for Normal-Karyotype Acute Myeloid Leukemia Using Whole-Exome Sequencing Genomics & Informatics acute myeloid leukemia DNA sequence analysis genetic variation risk assessment |
| title | Genetic Risk Prediction for Normal-Karyotype Acute Myeloid Leukemia Using Whole-Exome Sequencing |
| title_full | Genetic Risk Prediction for Normal-Karyotype Acute Myeloid Leukemia Using Whole-Exome Sequencing |
| title_fullStr | Genetic Risk Prediction for Normal-Karyotype Acute Myeloid Leukemia Using Whole-Exome Sequencing |
| title_full_unstemmed | Genetic Risk Prediction for Normal-Karyotype Acute Myeloid Leukemia Using Whole-Exome Sequencing |
| title_short | Genetic Risk Prediction for Normal-Karyotype Acute Myeloid Leukemia Using Whole-Exome Sequencing |
| title_sort | genetic risk prediction for normal karyotype acute myeloid leukemia using whole exome sequencing |
| topic | acute myeloid leukemia DNA sequence analysis genetic variation risk assessment |
| url | http://genominfo.org/upload/pdf/gni-11-46.pdf |
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