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Alexander Kohlmann

Publications and source records attributed to Alexander Kohlmann.

20 records · Page 2Linked to original sources

Acute myeloid leukemias with reciprocal rearrangements can be distinguished by specific gene expression profiles.

Acute myeloid leukemia (AML) is a heterogeneous group of genetically defined diseases. Their classification is important with regard to prognosis and treatment. We performed microarray analyses for gene expression profiling on bone marrow samples of 37 patients with newly diagnosed AML. All cases had either of the distinct subtypes AML M2 with t(8;21), AML M3 or M3v with t(15;17), or AML M4eo with inv(16). Diagnosis was established by cytomorphology, cytogenetics, fluorescence in situ hybridization, and reverse transcriptase-PCR in every sample. By using two different strategies for microarray data analyses, this study revealed a unique correlation between AML-specific cytogenetic aberrations and gene expression profiles.

Acute Disease↗

Impact of integrating clinical and genetic information.

To assess the relevance of molecular markers it is required to combine clinical and genetic information. For reliable assessment of parameters relevant to diagnostics and therapy large patient collectives must be characterized both with respect to phenotype and genotype. Matching of genetic data like gene expression profiles, molecular genetics and cytogenetics with clinical data like follow-up, morphological findings and diagnoses involves integration of complex databases. In the context of a nationwide leukemia research network in Germany we designed an integrated database covering both genetic and clinical data of patients. The system contains follow-up data and relevant laboratory modalities, i. e. cytomorphology, cytogenetics, molecular genetics, FISH, immunophenotyping and gene expression profiling. So far 13,541 cases from 7,746 patients treated by 1,225 physicians are documented. The data structure consists of up to 888 variables per case. From our experience, integration of clinical and genetic information requires significant efforts - including data protection issues -, but is feasible and improves data quality leading to faster and more reliable research results for the benefit of the patients.

Computer Systems↗