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This thesis is devoted to mathematical modeling of acute leukemias, which form a heterogeneous group of severe blood cancers. New models of dynamic behavior of blood forming (hematopoietic) and leukemic cells are developed and studied analytically. Bone marrow aspiration data contributed from the University Hospital of Heidelberg (Prof. Dr. A. D. Ho) and clonal tracking experiments from literature serve as a test scenario for the proposed models. To reflect the compartmental architecture of the hematopoietic and leukemic cell line, the models are represented by systems of nonlinear ordinary differential equations. Different possible modes of interaction between healthy and leukemic cells are proposed such as competition for environmental signals or autonomous leukemic cell growth and competition for marrow space. Extensive analytical studies of system dynamics and the derived criteria for coexistence and out-competition of the different cell types result in biologically meaningful characterizations of the cancer stem cell state by dynamic cell properties. Numerical studies allow to investigate the impact of different cell parameters on the clinical course and patient prognosis. A model-based prognostic marker for survival of relapsing acute myeloid leukemia patients is developed and tested based on clinical data. The obtained results underline the strong impact of leukemia stem cell behavior on the clinical dynamics. Extensions of the models including multiple leukemic clones allow to link experimental observations of clonal evolution to yet not measurable but clinically meaningful cell parameters at different stages of the disease. The models derived in this thesis depend on a quasi-steady state approximation describing the dependence of cytokine concentrations on mature cell density. In the last part of this work it is rigorously shown that solutions depending on the quasi-steady state approximation are close to solutions of a singular perturbation problem including dynamics of the signal molecules as a ...