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Alexander Kohlmann

Publications and source records attributed to Alexander Kohlmann.

At least 19 recordsLinked to original sources
PubMed2006

Comparison of mRNA abundance quantified by gene expression profiling and percentage of positive cells using immunophenotyping for diagnostic antigens in acute and chronic leukemias.

BACKGROUND: Microarray analysis is considered a future diagnostic tool in leukemias. Whereas data accumulate on specific gene expression patterns in biologically defined leukemia entities, data on the correlation between flow cytometrically determined protein expression, which are essential in the diagnostic setting today, and microarray results are limited. METHODS: The results obtained by microarray analysis were compared using the Affymetrix GeneChip HG-U133 system in parallel with flow cytometric findings of 36 relevant targets in 814 patients with newly diagnosed acute and chronic leukemias as well as in normal bone marrow samples. RESULTS: In a total of 21,581 individual comparisons between signal intensities obtained by microarray analysis and percentages of positive cell as determined by flow cytometry, coefficients of correlation in the range of 0.171 to 0.807 were obtained. In particular, the degree of correlation was high in the following genes critical in the diagnostic setting: CD4, CD8, CD13 (ANPEP), CD33, CD23 (FCER2), CD64 (FCGR1A), CD117 (KIT), CD34, MPO, CD20 (MS4A1), CD7 (range of r, 0.589-0.807). CONCLUSIONS: The present data prove the high degree of correlation between findings obtained by microarray analysis and flow cytometry. They are in favor of a future application of the microarray technology as a robust diagnostic tool in leukemias.

Antigens, CD↗
PubMed2006

PQN and DQN: algorithms for expression microarrays.

An ideal expression algorithm should be able to tell truly different expression levels with small false positive errors and be robust to assay changes. We propose two algorithms. PQN is the non-central trimmed mean of perfect match intensities with quantile normalization. DQN is the non-central trimmed mean of differences between perfect match and mismatch intensities with quantile normalization. The quantiles for normalization can be either empirical or theoretical. When array types and/or assay change in a study, the normalization to common quantiles at the probe set level is essential. We compared DQN, PQN, RMA, GCRMA, DCHIP, PLIER and MAS5 for the Affymetrix Latin square data and our data of two sets of experiments using the same bone marrow but different types of microarrays and different assay. We found the computation for AUC of ROC at affycomp.biostat.jhsph.edu can be improved.

Algorithms↗
PubMed2006

Impact of trisomy 8 on expression of genes located on chromosome 8 in different AML subgroups.

Trisomy 8 is the most frequently observed trisomy in acute myeloid leukemia (AML) occurring as a sole karyotype abnormality or in addition to other chromosome aberrations. It was the aim of this study to analyze the impact of trisomy 8 on the expression of genes located on chromosome 8 in distinct AML subgroups characterized by different chromosome abnormalities in addition to trisomy 8. Gene expression analyses were performed on a total of 567 AML cases comprising the following subgroups: +8 sole, +8 within a complex aberrant karyotype, +8 in addition to t(15;17), inv(16), t(8;21), 11q23/MLL, or other abnormalities, AML with normal karyotype and the before mentioned subgroups without trisomy 8. A significant higher mean expression of genes located on chromosome 8 was observed in subgroups with +8 in comparison to their respective control groups. A varying number of significantly higher expressed genes was identified in all comparisons. No gene was significantly overexpressed in all comparisons, and no distinct gene expression pattern was identified allowing the identification of cases with trisomy 8. In conclusion, the gain of chromosome 8 leads to a higher expression of genes located on chromosome 8. However, no consistent pattern of genes was identified, which shows a higher expression in all AML subtypes with trisomy 8. These data suggest that trisomy 8 rather provides a platform for a higher expression of chromosome 8 genes which are individually up-regulated by the respective primary genetic abnormalities. Therefore, trisomy 8 in AML determines no specific disease characteristic but is a disease modulating secondary event.

Acute Disease↗
PubMed2006

Classification of AML by DNA-oligonucleotide microarrays.

Accurate diagnosis and classification of leukemias are the bases for the appropriate management of patients. The diagnostic accuracy and efficiency of present methods may be improved by the use of microarrays. The following chapter gives an overview of the method of gene expression profiling of leukemia samples, its laboratory procedure, and how to approach the analysis of the data.

DNA, Complementary↗
PubMed2005

Role of gene expression profiling for diagnosing acute leukemias.

Cytomorphology and cytochemistry in combination with multiparameter immunophenotyping today are the standard methods for establishing the diagnosis of acute leukemias. In addition, cytogenetics, fluorescence in situ hybridization, and polymerase chain reaction based assays provide important information regarding biologically defined and prognostically relevant subgroups and allow a comprehensive diagnosis of well defined subentities. With regard to the clinical setting a better understanding of the clinical course of distinct biologically defined disease subtypes is needed to select disease-specific therapeutic approaches. Paralleling the increase in knowledge on deregulated pathways in leukemia the development of new therapeutics is accelerated and therefore requires a detailed and comprehensive diagnostic tool. Revealing and quantifying the expression status of many ten thousands of genes in a single analysis the microarray technology holds this potential to become an essential tool for the molecular classification of leukemias. It may therefore be used as a routine method for diagnostic purposes in the near future. Furthermore, it is anticipated that new biologically defined and clinically relevant subtypes of leukemia will be identified based on gene expression profiling. This method may therefore guide therapeutic decisions.

Acute Disease↗
PubMed2005

Global approach to the diagnosis of leukemia using gene expression profiling.

Accurate diagnosis and classification of leukemias are the bases for the appropriate management of patients. The diagnostic accuracy and efficiency of present methods may be improved by the use of microarrays for gene expression profiling. We analyzed gene expression profiles in 937 bone marrow and peripheral blood samples from 892 patients with all clinically relevant leukemia subtypes and from 45 nonleukemic controls by U133A and U133B GeneChip arrays. For each subgroup, differentially expressed genes were calculated. Class prediction was performed using support vector machines. Prediction accuracy was estimated by 10-fold cross-validation and was assessed for robustness in a 100-fold resampling approach using randomly chosen test sets consisting of one third of the samples. Applying the top 100 genes of each subgroup, an overall prediction accuracy of 95.1% was achieved that was confirmed by resampling (median, 93.8%; 95% confidence interval, 91.4%-95.8%). In particular, acute myeloid leukemia (AML) with t(15;17), AML with t(8;21), AML with inv(16), chronic lymphatic leukemia (CLL), and pro-B-cell acute lymphoblastic leukemia (pro-B-ALL) with t(11q23) were classified with 100% sensitivity and 100% specificity. Accordingly, cluster analysis completely separated all 13 subgroups analyzed. Gene expression profiling can predict all clinically relevant subentities of leukemia with high accuracy.

Adolescent↗
PubMed2005

Pattern robustness of diagnostic gene expression signatures in leukemia.

Microarray technology has been proposed as an addition to the methods in current use for diagnosing leukemia. Before a new technology can be used in a diagnostic setting, the method has to be shown to produce robust results. It is known that, given the technical aspects of specimen sampling and target preparation, global gene expression patterns can change dramatically. Various parameters such as RNA degradation, shipment time, sample purity, and patient age can principally influence measured gene expression. However, thus far, no information has been available on the robustness of a diagnostic gene expression signature. We demonstrate here that for a subset of acute leukemia, expression profiling is applicable in a diagnostic setting, considering various influencing parameters. With the use of a set of differentially expressed genes, that is, a diagnostic gene expression signature, four genetically defined acute myeloid leukemia subtypes with recurrent chromosomal aberrations can clearly be identified. In addition, we show that preparation by different operators and using different sample-handling procedures did not impair the robustness of diagnostic expression signatures. In conclusion, our results provide additional support for the applicability of microarrays in a diagnostic setting, and we have been encouraged to enroll patients in a prospective study in which microarrays will be tested as an additional routine diagnostic method in parallel with standard diagnostic procedures.

Adult↗
PubMed2005

AML M3 and AML M3 variant each have a distinct gene expression signature but also share patterns different from other genetically defined AML subtypes.

Acute promyelocytic leukemia (APL) with t(15;17) appears in two phenotypes: AML M3, with abnormal promyelocytes showing heavy granulation and bundles of Auer rods, and AML M3 variant (M3v), with non- or hypogranular cytoplasm and a bilobed nucleus. We investigated the global gene expression profiles of 35 APL patients (19 AML M3, 16 AML M3v) by using high-density DNA-oligonucleotide microarrays. First, an unsupervised approach clearly separated APL samples from other AMLs characterized genetically as t(8;21) (n = 35), inv(16) (n = 35), or t(11q23)/MLL (n = 35) or as having a normal karyotype (n = 50). Second, we found genes with functional relevance for blood coagulation that were differentially expressed between APL and other AMLs. Furthermore, a supervised pairwise comparison between M3 and M3v revealed differential expression of genes that encode for biological functions and pathways such as granulation and maturation of hematologic cells, explaining morphologic and clinical differences. Discrimination between M3 and M3v based on gene signatures showed a median classification accuracy of 90% by use of 10-fold CV and support vector machines. Additional molecular mutations such as FLT3-LM, which were significantly more frequent in M3v than in M3 (P < 0.0001), may partly contribute to the different phenotypes. However, linear regression analysis demonstrated that genes differentially expressed between M3 and M3v did not correlate with FLT3-LM.

Adolescent↗
PubMed2005

Acute myeloid leukemia with a complex aberrant karyotype is a distinct biological entity characterized by genomic imbalances and a specific gene expression profile.

Acute myeloid leukemia (AML) with a complex aberrant karyotype is a distinct biological entity. It is characterized by: (1) a sharp increase in incidence above age 50; (2) a characteristic pattern of chromosomal gain and, especially, loss, that is, of 5q14q33, 7q32q35, and 17p13, translating into reduced expression of genes in these regions; (3) a unique gene expression pattern including up-regulation of genes involved in DNA repair; (4) a high incidence of TP53 deletions and/or mutations; and (5) an overall unfavorable prognosis. Further unraveling the biology of AML with a complex aberrant karyotype by gene expression profiling may provide deeper insights into the pathogenesis of as well as the reasons for chemoresistance in this AML subtype. These data may be the basis for developing targeted therapeutic strategies to increase the cure rate in patients with AML and a complex aberrant karyotype.

Acute Disease↗
PubMed2005

Detailed analysis of FLT3 expression levels in acute myeloid leukemia.

BACKGROUND AND OBJECTIVES: FLT3 mutations are found in up to 30% of cases of acute myeloid leukemia (AML). Although new FLT3 mutations are being increasing by investigated, the role of FLT3 expression levels in wild type as well as in mutated FLT3 has only been infrequently addressed. DESIGN AND METHODS: To further evaluate the role of FLT3 in AML we investigated FLT3 expression levels in 207 adult AML patients and 8 healthy donors by real-time polymerase chain reaction (PCR). The expression levels were correlated with clinical parameters, FAB types, cytogenetics, flow cytometry, microarray analysis, FLT3 mutations, further molecular aberrations and prognosis. RESULTS: FLT3 expression levels were different in certain FAB types with increasing levels in the following order: M3<M3v<M6<M2<M4eo<M4<M0<M1<M5a<M5b. These results correlate with the FLT3 receptor surface expression (CD135) detected by flow cytometry (p<0.001), showing the highest CD135 expression in FAB M5. Independent analysis of FLT3 expression in cytogenetic AML subgroups showed the lowest levels in t(15;17) and the highest in the t(11q23) positive AML. In addition, FLT3 expression levels correlated with high percentages of bone marrow blasts (p<0.001) and high leukocyte counts (p<0.001). On the molecular level, no differences in FLT3 expression levels were detected between AML with and without any FLT3 mutation as well as for FAB M5 with or without MLL abnormalities (p=0.495). Furthermore, no significant difference could be found between the group of t(11q23) and MLL-PTD (p=0.180) or between MLL-PTD positive and MLL negative normal karyotypes (p=0.859). In patients with normal cytogenetics no impact or overall survival or event-free survival could be detected (p=0.128 and p=0.305, respectively) regardless of FLT3 muatation status, whereas investigating the group of patients with normal cytogenetics and wild-type FLT3, a clear tendency for a worse overall (p=0.059) and event free (p=0.087) survival was found. INTERPRETATION AND CONCLUSIONS: FLT3 expression levels are correlated with clinical data, genetic subgroups as well as prognosis. Furthermore, our data indicate that FLT3 expression and signaling are closely associated with FAB M5.

Acute Disease↗
PubMed2004

Identification of differentially expressed genes in scrapie-infected mouse brains by using global gene expression technology.

The pathogenesis of prion diseases, a class of transmissible fatal neurodegenerative diseases in humans and animals, is still unclear. The aim of this study was to identify the differentially regulated genes that correlate with the development of prion diseases for a better understanding of their pathological mechanisms. We employed Affymetrix Mouse Expression Arrays 430A containing >22,000 transcripts and compared the global gene expression profiles from brains of mice who were intracerebrally inoculated with scrapie strains ME7 and RML with those from brains of uninfected and mock-infected mice. The microarray data were analyzed by Significance Analysis of Microarrays, revealing 121 genes whose expression increased at least twofold in both ME7- and RML-infected mouse brains, with an estimated false discovery rate of < or =5%. These genes encode proteins involved in proteolysis, protease inhibition, cell growth and maintenance, the immune response, signal transduction, cell adhesion, and molecular metabolism. The time course of expression generally showed up-regulation of these genes from 120 days postinoculation (dpi) for ME7-inoculated mouse brains and from 90 dpi for RML-inoculated mouse brains. The onset of elevated expression correlated temporally with the onset of PrP(Sc) accumulation and the activation of glia, which may have contributed to neuronal cell death. Among the differentially regulated genes reported in the present study, the emergence of genes for several cathepsins and S100 calcium binding proteins was conspicuous. These and other genes reported here may represent novel potential diagnostic and therapeutic targets for prion disease.

Animals↗
PubMed2004

Gene expression profiling as a diagnostic tool in acute myeloid leukemia.

The standard methods for establishing the diagnosis of acute leukemias are cytomorphology and cytochemistry in combination with multiparameter immunophenotyping. Cytogenetics, fluorescence in situ hybridization, and PCR-based assays add important information regarding biologically defined and prognostically relevant subgroups, and allow a comprehensive diagnosis of well-defined subentities. In the clinical setting, a better understanding of the clinical course of distinct, biologically defined disease subtypes is the basis for a selection of disease-specific therapeutic approaches. As knowledge of deregulated pathways in leukemia increases and accelerates the development of new therapeutics, a detailed and comprehensive diagnostic tool is required. Microarray technology, which quantifies gene expression intensities of thousands of genes in a single analysis, has the potential to become an essential tool for the molecular classification of leukemias. It may, therefore, be used as a routine method for diagnostic purposes in the near future. Furthermore, gene expression profiling may also lead to the detection of new biologically defined and clinically relevant subtypes in leukemia and guide therapeutic decision-making in the future.

Acute Disease↗
PubMed2003

The fusion protein AML1-ETO in acute myeloid leukemia with translocation t(8;21) induces c-jun protein expression via the proximal AP-1 site of the c-jun promoter in an indirect, JNK-dependent manner.

Overexpression of proto-oncogene c-jun and constitutive activation of the Jun N-terminal kinase (JNK) signaling pathway have been implicated in the leukemic transformation process. However, c-jun expression and the role of the JNK signaling pathway have not been investigated in primary acute myeloid leukemia (AML) cells with frequently observed balanced rearrangements such as t(8;21). In the present study, we report elevated c-jun mRNA expression in AML patient bone marrow cells with t(8;21), t(15;17) or inv(16), and a high correlation in mRNA expression levels of AML1-ETO and c-jun within t(8;21)-positive AML patient cells. In myeloid U937 cells, c-jun mRNA and protein expression increase upon inducible expression of AML1-ETO. AML1-ETO transactivates the human c-jun promoter through the proximal activator protein (AP-1) site by activating the JNK pathway. Overexpression of JNK-inhibitor JIP-1 and chemical JNK inhibitors reduce the transactivation capacity of AML1-ETO on the c-jun promoter and the proapoptotic function of AML1-ETO in U937 cells. An autocrine mechanism involving granulocyte-colony stimulating factor (G-CSF) and G-CSF receptor (G-CSF-R) might participate in AML1-ETO mediated JNK-signaling, because AML1-ETO induces G-CSF and G-CSF-R expression, and G-CSF-R-neutralizing antibodies reduce AML1-ETO-induced JNK phosphorylation. These data suggest a model in which AML1-ETO induces proto-oncogene c-jun expression via the proximal AP-1 site of the c-jun promoter in a JNK-dependent manner.

Chromosomes, Human, Pair 21↗
PubMed2003

Elevated c-Jun expression in acute myeloid leukemias inhibits C/EBPalpha DNA binding via leucine zipper domain interaction.

Transcription factor C/EBPalpha induces normal myeloid differentiation, inactivation of C/EBPalpha leads to a differentiation block in acute myeloid leukemias (AML), and overexpression of C/EBPalpha results in AML growth arrest and differentiation. Recent reports suggest that C/EBPalpha is activated or inactivated via protein-protein interactions. We previously reported that C/EBPalpha needs to inactivate the proto-oncogene c-Jun via leucine zipper domain interaction in order to induce granulocytic differentiation. We, therefore, hypothesized that c-Jun expression might be elevated in AML and subsequently inactivate C/EBPalpha. In fact, compared to normal bone marrow mononuclear cells, c-Jun expression is increased in AML patient samples (Affymetrix expression microarray analysis, n=166). c-Jun binds to C/EBPalpha via the leucine zipper domains and prevents C/EBPalpha from DNA binding. Inactivation of C/EBPalpha by c-Jun is necessary for c-Jun to induce proliferation because c-Jun-induced proliferation can be prevented by ectopic overexpression of C/EBPalpha. The dominant-negative 30-kDa C/EBPalpha protein, found in AML, fails to downregulate c-Jun mRNA expression in AML patient samples. Thus, our data suggest a model for AML in which c-Jun promotes proliferation and prevents differentiation by inhibiting C/EBPalpha DNA binding via leucine zipper domain interaction. It might depend on the expression levels of C/EBPalpha and c-Jun, if inhibition of C/EBPalpha by c-Jun or if inhibition of c-Jun by C/EBPalpha is more predominant: proliferation versus differentiation; AML versus normal myeloid development.

CCAAT-Enhancer-Binding Protein-alpha↗
PubMed2003

Correlation of protein expression and gene expression in acute leukemia.

BACKGROUND: Flow cytometry (FC) is a standard method for diagnosing and subclassifying acute myeloid (AML) and acute lymphoblastic (ALL) leukemias and allows the analysis of cell surface and intracellular proteins. In the future, diagnostic procedures may include oligonucleotide microarray analysis (MA) to detect expression patterns of large numbers of specific genes. METHODS: For comparison between methods, we performed FC and MA by using the Affymetrix GeneChip HG-U133A microarray in parallel and correlated protein expression levels and mRNA abundance of 39 relevant genes in 113 patients with newly diagnosed AML and ALL and four normal bone marrow samples. RESULTS: In 1,512 of 2,187 (69.1%) comparisons between methods, congruent results were obtained with regard to positivity or negativity of expression, respectively. Specifically, there was a significant correlation between protein expression and mRNA abundance for genes essential for diagnosing and subclassifying AML and ALL with regard to positivity and expression. CONCLUSIONS: These data suggest that protein expression is highly correlated to mRNA abundance in AML and ALL. Further, expression patterns of specific genes provide important information at diagnosis for patients with AML and ALL that may be used for the discrimination from other leukemias.

Antigens, CD↗
PubMed2003

Molecular characterization of acute leukemias by use of microarray technology.

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.

Acute Disease↗
PubMed2003

Gene expression profiling as a tool for the diagnosis of acute leukemias.

The standard methods to diagnose leukemia are cytomorphology and, in some cases, histology, which both are supplemented by cytochemistry and multiparameter immunophenotyping. Cytogenetics, fluorescence in situ hybridisation (FISH), and polymerase chain reaction (PCR) assays add important information and allow comprehensive diagnosis of well-defined subentities today. In the clinic, better understanding of the course of distinct, biologically defined disease subtypes is the basis for a selection of specific therapeutic approaches. As knowledge on deregulated pathways in leukemia accelerates the development of new therapeutics, a detailed and comprehensive diagnostic tool is required. The microarray technology that quantifies gene expression intensities of thousands of genes in a single analysis has the potential to become essential for the molecular classification of leukemias. Microarrays may be used routinely for diagnostic purposes in the near future. Gene expression profiling should also lead to the detection of new biological and clinically relevant subtypes in leukemia and therefore guide therapeutic decisions.

Acute Disease↗