A comprehensive leukemia database: integration of cytogenetics, molecular genetics and microarray data with clinical information, cytomorphology and immunophenotyping

Dugas, Martin; Schoch, Claudia; Schnittger, Susanne; Haferlach, Torsten; Danhauser‐Riedl, Susanne; Hiddemann, Wolfgang; Messerer, D.; Überla, K

doi:10.1038/sj.leu.2402301

Cited by 21 publications

(9 citation statements)

References 22 publications

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“…The median shipment time was 1 day (range, 0-3 days). All samples underwent standardized processing, including sample central registration, 29 preparation, and evaluation by cytomorphology, 30 cytochemistry, multiparameter immunophenotyping, 31 cytogenetics, 32 fluorescence in situ hybridization (FISH), and molecular genetics. 33 Stabilized cell lysates were stored at Ϫ80°C for a median of 13 months (range, 0-67 months).…”

Section: Patient and Control Samplesmentioning

confidence: 99%

Global approach to the diagnosis of leukemia using gene expression profiling

Haferlach

Kohlmann

Schnittger

et al. 2005

Blood

183

109

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Section: Patient and Control Samplesmentioning

confidence: 99%

Global approach to the diagnosis of leukemia using gene expression profiling

Haferlach

Kohlmann

Schnittger

et al. 2005

Blood

183

109

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“…All samples were sent between May 1999 and July 2002 for reference diagnostics to our laboratory and registered in our leukemia database. 9 Samples were received either locally or by overnight mail. Prior to therapy, all patients gave their informed consent for participation in the current evaluation after having been advised about the purpose and investigational nature of the study as well as of potential risks.…”

Section: Patient Samplesmentioning

confidence: 99%

Pediatric acute lymphoblastic leukemia (ALL) gene expression signatures classify an independent cohort of adult ALL patients

et al. 2003

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Recent reports support a possible future application of gene expression profiling for the diagnosis of leukemias. However, the robustness of subtype-specific gene expression signatures has to be proven on independent patient samples. Here, we present gene expression data of 34 adult acute lymphoblastic leukemia (ALL) patients (Affymetrix U133A microarrays). Support Vector Machines (SVMs) were applied to stratify our samples based on given gene lists reported to predict MLL, BCR-ABL, and T-ALL, as well as MLL and non-MLL gene rearrangement positive pediatric ALL. In addition, seven other B-precursor ALL cases not bearing t(9;22) or t(11q23)/MLL chromosomal aberrations were analyzed. Using top differentially expressed genes, hierarchical cluster and principal component analyses demonstrate that the genetically more heterogeneous B-precursor ALL samples intercalate with BCR-ABL-positive cases, but were clearly distinct from T-ALL and MLL profiles. Similar expression signatures were observed for both heterogeneous B-precursor ALL and for BCR-ABL-positive cases. As an unrelated laboratory, we demonstrate that gene signatures defined for childhood ALL were also capable of stratifying distinct subtypes in our cohort of adult ALL patients. As such, previously reported gene expression patterns identified by microarray technology are validated and confirmed on truly independent leukemia patient samples.

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“…The previously reported AML expression profiles representing t(8;21), t(15;17), and inv(16) cases were included in this data set. All cases were sent for reference diagnostics to our laboratory, registered in our leukemia database (Dugas et al, 2001), and were treated within prospective randomized multi-center trials. The studies were conducted following the rules of the local internal review board and the tenets of the revised Helsinki protocol.…”

mentioning

confidence: 99%

Molecular characterization of acute leukemias by use of microarray technology

Kohlmann

Schoch

Schnittger

et al. 2003

Genes Chromosomes & Cancer

125

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Accurate subclassification of leukemia and the identification of prognostic determinants are essential to guide therapy and to improve patients' outcome. According to present standards, pre-therapeutic assessment depends on a combination of different methods. We aimed to expand the molecular characterization of different acute leukemia subtypes to identify new genome-wide diagnostic markers. Total RNA from 90 adult patients suffering from acute lymphoblastic leukemia (ALL, n = 25) and acute myeloid leukemia (AML, n = 65) was extracted at diagnosis and high density oligonucleotide microarrays were used to analyze the expression profiles of 12,000/22,000 genes in all specimens (Affymetrix U95Av2/U133A). All cases were thoroughly characterized by individual combinations of cytomorphology, cytogenetics, multiparameter immunophenotyping, and molecular genetics. The expression signature of a small set of differentially expressed genes was sufficient to accurately discriminate eight clinically relevant acute leukemia subgroups. Underlying chromosomal aberrations or immunophenotypical characteristics were strictly correlated with a distinct gene expression pattern for AML with t(8;21), t(15;17), t(11q23)/MLL, or inv(16) as well as for precursor B-ALL with t(9;22), t(8;14), or t(11q23)/MLL and precursor T-ALL. These data support a possible future application of microarray technology for classification of the acute leukemias.

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A comprehensive leukemia database: integration of cytogenetics, molecular genetics and microarray data with clinical information, cytomorphology and immunophenotyping

Cited by 21 publications

References 22 publications

Global approach to the diagnosis of leukemia using gene expression profiling

Global approach to the diagnosis of leukemia using gene expression profiling

Pediatric acute lymphoblastic leukemia (ALL) gene expression signatures classify an independent cohort of adult ALL patients

Molecular characterization of acute leukemias by use of microarray technology

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