Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Gene Expression Profiles with Common Translocations in Acute Myeloid Leukemia (AML) using SAGE

ABSTRACT: SAGE was used to profile gene expression in leukemic myeloid progenitor cells of AML patients with t(8;21), t(15;17), t(9;11) and inv(16). Keywords: SAGE analysis of gene expression in leukemic myeloid progenitor cells isolated from bone marrow Bone marrow cells from 4 patients with de novo t(9;11), 3 with treatment-related t(9;11), and 5 each with inv(16), t(15;17), t(8;21) were used for the study. Each sample contained at least 75% affected cells with no other chromosome abnormalities at cytogenetic level. Mononuclear cells were purified from bone marrow cells for each sample, and CD15+ myeloid progenitor cells were isolated from these mononuclear cells. Poly A+ RNA were isolated from CD15+ myeloid progenitor cells of each sample for SAGE tag collection.

ORGANISM(S): Homo sapiens

SUBMITTER: San Ming Wang

PROVIDER: E-GEOD-3255 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Gene expression profiles in acute myeloid leukemia with common translocations using SAGE.

Lee Sanggyu S Chen Jianjun J Zhou Guolin G Shi Run Zhang RZ Bouffard Gerard G GG Kocherginsky Masha M Ge Xijin X Sun Miao M Jayathilaka Nimanthi N Kim Yeong Cheol YC Emmanuel Neelmini N Bohlander Stefan K SK Minden Mark M Kline Justin J Ozer Ozden O Larson Richard A RA LeBeau Michelle M MM Green Eric D ED Trent Jeffery J Karrison Theodore T Liu Piu Paul PP Wang San Ming SM Rowley Janet D JD

Proceedings of the National Academy of Sciences of the United States of America 20060117 4

Identification of the specific cytogenetic abnormality is one of the critical steps for classification of acute myeloblastic leukemia (AML) which influences the selection of appropriate therapy and provides information about disease prognosis. However at present, the genetic complexity of AML is only partially understood. To obtain a comprehensive, unbiased, quantitative measure, we performed serial analysis of gene expression (SAGE) on CD15(+) myeloid progenitor cells from 22 AML patients who h ...[more]

PMID: 16418266

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Project description:We performed a genome-wide analysis of gene expression in primary human CD151 myeloid progenitor cells. By using the serial analysis of gene expression (SAGE) technique, we obtained quantitative information for the expression of 37,519 unique SAGE-tag sequences. Of these unique tags, (i) 25% were detected at high and intermediate levels, whereas 75% were present as single copies, (ii) 53% of the tags matched known expressed sequences, 34% of which were matched to more than one known expressed sequence, and (iii) 47% of the tags had no matches and represent potentially novel genes. The correct genes were confirmed by application of the generation of longer cDNA fragments from SAGE tags for gene identification (GLGI) technique for high-copy tags with multiple matches. A set of genes known to be important in myeloid differentiation were expressed at various levels and used different spliced forms. This study provides a normal baseline for comparison of gene expression in myeloid diseases. The strategy of using SAGE and GLGI techniques in this study has broad applications to the genome-wide identification of expressed genes. (Lee S et al. The pattern of gene expression in human CD15+ myeloid progenitor cells. Proc Natl Acad Sci U S A. 98(6):3340-5, 2001; Lee S et al. Gene expression profiles in acute myeloid leukemia with common translocations using SAGE. Proc Natl Acad Sci U S A. 103(4):1030-5, 2006) Human bone-marrow mononuclear cells were isolated from bone marrow with FicollyPaque solution and stored in liquid nitrogen. Cells from three donors were thawed at 37°C, pooled, and used immediately for the isolation of myeloid progenitor cells with CD15 magnetic beads (Dynal, Oslo, Norway). The cells isolated by CD15 magnetic beads were lysed directly with TRIzol reagent for isolation of total RNA. mRNA was purified from 5 mg of total RNA with oligo(dT)25 beads. cDNA was synthesized with a cDNA synthesis kit, and SAGE was performed according to the SAGE protocol with the exceptions described in the original paper. SAGE-tag sequences were collected with the Big-Dye sequencing kit and ABI377 sequencer, and tag sequences were extracted with SAGE 300 software.

Project description:Background: Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified. Methods: Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n=101) and/or poor quality control criteria (n=10) (test set). Results: With 10-marker classifiers, all training set samples as well as 97 of the 101 test samples with a low blast load, and all 10 samples with poor quality control criteria were correctly classified. Regarding test set samples, the overall error rate of the class prediction was below 4 percent, even though the leukemic blast load was as low as 2%. Sensitivity, specificity, negative and positive predictive values of the class assignments ranged from 91% to 100%. Of note, for acute promyelocytic leukemia and leukemias with t(8;21) or inv(16), the confidence level of the class assignment was influenced by the leukemic blast load. Conclusion: Gene expression profiling and a supervised method requiring 10-marker classifiers enable the identification of favorable cytogenetic risk acute myeloid leukemia even when samples contain low leukemic blast loads or display poor quality control criterion. Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n=101) and/or poor quality control criteria (n=10) (test set).

Dataset Information

Gene Expression Profiles with Common Translocations in Acute Myeloid Leukemia (AML) using SAGE

Publications

Gene expression profiles in acute myeloid leukemia with common translocations using SAGE.

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