Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of human pre and pro B cells from patients with childhood acute lymphoblastic leudemia

ABSTRACT: This data was generated as part of a larger study in to the leukemic stem cell potential of sorted childhood ALL populations. This work has been submitted for publication with the following summary. "We examined the leukemic stem cell potential of blasts at different stages of maturation in childhood acute lymphoblastic leukemia. Human leukemic bone marrow was transplanted intrafemorally onto NOD/scid mice. Cells sorted using the B precursor differentiation markers CD19, CD20 and CD34 were isolated from patient samples and engrafted mice before serial transplantation onto primary or subsequent (up to quaternary) recipients. Surprisingly, blasts representative of all the different maturational stages were able to reconstitute and re-establish the complete leukemic phenotype in vivo. Sorted blast populations mirrored normal B precursor cells with transcription of a number of stage appropriate genes. These observations lead to a new model for leukemia-propagating stem cells in childhood ALL." Diagnosis bone marrow specimens from children with acute lymphoblastic leukemia were FACS sorted into populations with surface expression CD34+CD19+ and CD34-CD19+. Expression analysis was performed to assess the developmental state of these two blast populations. These initial data have not been confirmed by RT PCR and should be viewed as preliminary. We are continuing with our work to further assess the transcriptional status of these populations.

ORGANISM(S): Homo sapiens

SUBMITTER: Simon Bomken

PROVIDER: E-MEXP-1522 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:The microarray data presented here relate to a study on TEL-AML1 associated childhood leukemia (Hong et al, 2008) the abstract of which is as follows: "Understanding cancer pathogenesis requires knowledge of not only the specific contributory genetic mutations but also the cellular framework in which they arise and function. Here we explore the clonal evolution of childhood precursor B-cell acute lymphoblastic leukemia characterised by a chromosomal translocation generating a TEL-AML1 fusion gene. We identify a cell compartment in leukemic children which can propagate leukemia when transplanted in mice. By studying a monochorionic twin pair, one pre-leukemic and one with frank leukemia, we establish the lineal relationship between these "tumor-propagating" cells and the pre-leukemic cell in which the TEL-AML1 fusion first arises or has functional impact. Analysis of TEL-AML1 transduced cord blood cells suggests that TEL-AML1 functions as a first-hit mutation by endowing this pre-leukemic cell with altered self-renewal and survival properties." The cells used to generate the microarray data were obtained as follows: We prospectively isolated CD34+CD38-/lowCD19+ cells from NOD/SCID mice transplanted with TEL-AML1-transduced human cord blood cells and compared their gene expression profiles, ascertained by affymetrix microarray analysis (see methods), to control 'hematopoietic stem cells' (HSCs immunophenotypically-defined as CD34+CD38-/lowCD19-) and pro-B cells (immunophenotypically-defined as CD34+CD38+CD19+) isolated from NOD/SCID animals transplanted with control vector transduced cord blood cells. While these different populations were obtained from three independent transduction and transplantation experiments, the data were generated from small numbers of cells and have not been validated by independent analyses such as RQ-PCR or protein analysis. They should therefore be regarded as preliminary in nature and we would therefore caution against detailed analysis of individual gene expression profiles based on these particular datasets. This caveat aside, the data may provide a broad overview of gene expression profiles in these cell types and such analyses suggest that TEL-AML1 generates a novel population of cells that contain features of both stem cells and committed B progenitors (Hong et al 2008). We are currently repeating the analyses using larger numbers of cells and more replicates together with appropriate cell populations from ALL patients and will post these data online when they become available.

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).

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Transcription profiling of human pre and pro B cells from patients with childhood acute lymphoblastic leudemia

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