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Surface marker expression profiles of dendritic cells (DC) generated from blasts in patients with acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) are valuable tools to characterize and quantify DC in experimental settings
Surface marker expression profiles of dendritic cells (DC) generated from blasts in patients with acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) are valuable tools to characterize and quantify DC in experimental settings
Dendritic cells (DC) play a central role in connecting innate with specific adoptive immunity resulting in target specific activation T-cells. As professional antigen presenting cells (APC) DC specifically stimulate T-effector cells, especially tumor-cytotoxic T-cells. Therefore they are regarded as interesting candidates for anti-tumor or anti-leukemic vaccination strategies. The insufficient expression of costimulatory antigens, MHC molecules and tumor-associated antigens (TAA) on the surface of cancer cells and disturbed mechanisms of apoptosis are the main reason for an ineffective immune response in oncologic diseases. It was shown that acute myeloid leukemic cells can be differentiated to leukemia-derived DC (DCleu ), regaining the stimulatory capacity of professional DC while potentially presenting the whole leukemic antigen repertoire. Thus, vaccination strategies, using ex vivo or in vivo generated DC, might induce a highly specific anti-leukemic T-cell response circumventing the cumbersome identification of leukemia-associated antigens. In this thesis DC antigen (DCA) expression profiles of mononuclear cells (MNC) and dendritic cells (DC) generated from these MNC should be analyzed. The generated MNC and DC should be compared with respect to their DC antigen (DCA) expression profiles and the DCAs value to detect and quantify (leukemia-derived) DC in different AML/MDS subtypes and under different culture conditions. Therefore MNC and DC were generated from 137 patients with acute myeloid leukemia (AML) and 49 patients with myelodysplastic syndromes (MDS) under 6 different serum free culture conditions. DCA studied were: CD1a/1b/1c, CD206, CD25, CD137L, CD83, CD86, CD80 and CD40. DC-generating media were chosen according to their different mechanisms of inducing DC-differentiation: 1. ‚Basic method‘: TNF/GM-CSF/IL-4, 2. MCM-Mimic, 3. Ca Ionophore, 4. Picibanil, 5. Poly I:C and 6. Cytokines. Quality and quantity of generated DC was estimated by Flow cytometry applying a specified, ‘DC-based’ gating-strategy. Expression and coexpression profiles of 10 different DCA as well as various costimulatory molecules, maturation markers and blast antigens were evaluated. Only those DCA qualified for the quantification of leukemia-derived DC that were not expressed on uncultured MNC fractions. AML patients presented with an average of 58 % blasts, MDS patients with 13 % blasts in MNC fractions. DCA were expressed on average on less than 7% of uncultured MNC, however some of the markers could be expressed on up to 77% of uncultured cells in single AML cases. Consequently these DCA did not qualify for detection of DC in those cases. Highest expression rates were found for CD86 and CD40 in naïve AML and for CD137L and CD40 in naïve MDS samples. Other DCA (e.g. CD1a, 1b, 1c) were only rarely found on naïve blasts. DCA expression on uncultured AML and MDS MNC varied with FAB types and cytogenetic risk. After culture in different DC-differentiating media, on average 28% DC could be generated from AML MNC and 30% from MDS MNC, depending on methods used, with an average DC viability of more than 60% and an average DC maturity of 49% (AML) and 56% (MDS). On average 36% of leukemic blasts could be converted to DC. Proportions of DCleu in the total DC fraction varied from 40-58% and were on average 49% (AML) and 43% (MDS) after culture. Average results of all culture methods tested were comparable, however every method failed to create DC in some individual cases. The most important results of this thesis are: 1. It could be shown that DCA are expressed on naïve blasts in AML and MDS in individual patients. That means that the individual patients’ DCA-profiles have to be evaluated before DC-culture to find suitable DCA to detect and quantify (leukemia-derived) DC after culture. 2. Different methods of DC-generation qualify with varying individual efficiency to generate leukemic, mature, migratory and viable DC in individual cases. 3. To select the best DC-generating method the best DC-marker (no expression on naïve blasts, high expression on DC) has to be chosen to quantify DC in individual samples. 4. The use of only one method is not sufficient to create DC in every single AML and MDS sample. However, a successful, quantitative DC/DCleu -generation is possible in every case of AML and MDS by the combination of 3 different DC-generating media, but not every blast is convertible to DC leu . 5. There is a need for new, specific DC-markers that are not expressed on naïve blasts.
Dendritic cells, myelodysplastic syndromes, acute myeloid leukemia, serum free culture, surface marker, flow cytometry
Dreyßig, Julia
2010
Englisch
Universitätsbibliothek der Ludwig-Maximilians-Universität München
Dreyßig, Julia (2010): Surface marker expression profiles of dendritic cells (DC) generated from blasts in patients with acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) are valuable tools to characterize and quantify DC in experimental settings. Dissertation, LMU München: Medizinische Fakultät
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Abstract

Dendritic cells (DC) play a central role in connecting innate with specific adoptive immunity resulting in target specific activation T-cells. As professional antigen presenting cells (APC) DC specifically stimulate T-effector cells, especially tumor-cytotoxic T-cells. Therefore they are regarded as interesting candidates for anti-tumor or anti-leukemic vaccination strategies. The insufficient expression of costimulatory antigens, MHC molecules and tumor-associated antigens (TAA) on the surface of cancer cells and disturbed mechanisms of apoptosis are the main reason for an ineffective immune response in oncologic diseases. It was shown that acute myeloid leukemic cells can be differentiated to leukemia-derived DC (DCleu ), regaining the stimulatory capacity of professional DC while potentially presenting the whole leukemic antigen repertoire. Thus, vaccination strategies, using ex vivo or in vivo generated DC, might induce a highly specific anti-leukemic T-cell response circumventing the cumbersome identification of leukemia-associated antigens. In this thesis DC antigen (DCA) expression profiles of mononuclear cells (MNC) and dendritic cells (DC) generated from these MNC should be analyzed. The generated MNC and DC should be compared with respect to their DC antigen (DCA) expression profiles and the DCAs value to detect and quantify (leukemia-derived) DC in different AML/MDS subtypes and under different culture conditions. Therefore MNC and DC were generated from 137 patients with acute myeloid leukemia (AML) and 49 patients with myelodysplastic syndromes (MDS) under 6 different serum free culture conditions. DCA studied were: CD1a/1b/1c, CD206, CD25, CD137L, CD83, CD86, CD80 and CD40. DC-generating media were chosen according to their different mechanisms of inducing DC-differentiation: 1. ‚Basic method‘: TNF/GM-CSF/IL-4, 2. MCM-Mimic, 3. Ca Ionophore, 4. Picibanil, 5. Poly I:C and 6. Cytokines. Quality and quantity of generated DC was estimated by Flow cytometry applying a specified, ‘DC-based’ gating-strategy. Expression and coexpression profiles of 10 different DCA as well as various costimulatory molecules, maturation markers and blast antigens were evaluated. Only those DCA qualified for the quantification of leukemia-derived DC that were not expressed on uncultured MNC fractions. AML patients presented with an average of 58 % blasts, MDS patients with 13 % blasts in MNC fractions. DCA were expressed on average on less than 7% of uncultured MNC, however some of the markers could be expressed on up to 77% of uncultured cells in single AML cases. Consequently these DCA did not qualify for detection of DC in those cases. Highest expression rates were found for CD86 and CD40 in naïve AML and for CD137L and CD40 in naïve MDS samples. Other DCA (e.g. CD1a, 1b, 1c) were only rarely found on naïve blasts. DCA expression on uncultured AML and MDS MNC varied with FAB types and cytogenetic risk. After culture in different DC-differentiating media, on average 28% DC could be generated from AML MNC and 30% from MDS MNC, depending on methods used, with an average DC viability of more than 60% and an average DC maturity of 49% (AML) and 56% (MDS). On average 36% of leukemic blasts could be converted to DC. Proportions of DCleu in the total DC fraction varied from 40-58% and were on average 49% (AML) and 43% (MDS) after culture. Average results of all culture methods tested were comparable, however every method failed to create DC in some individual cases. The most important results of this thesis are: 1. It could be shown that DCA are expressed on naïve blasts in AML and MDS in individual patients. That means that the individual patients’ DCA-profiles have to be evaluated before DC-culture to find suitable DCA to detect and quantify (leukemia-derived) DC after culture. 2. Different methods of DC-generation qualify with varying individual efficiency to generate leukemic, mature, migratory and viable DC in individual cases. 3. To select the best DC-generating method the best DC-marker (no expression on naïve blasts, high expression on DC) has to be chosen to quantify DC in individual samples. 4. The use of only one method is not sufficient to create DC in every single AML and MDS sample. However, a successful, quantitative DC/DCleu -generation is possible in every case of AML and MDS by the combination of 3 different DC-generating media, but not every blast is convertible to DC leu . 5. There is a need for new, specific DC-markers that are not expressed on naïve blasts.