Noncanonical effector functions of the T-memory-like T-PLL cell are shaped by cooperative TCL1A and TCR signaling.

T-cell prolymphocytic leukemia (T-PLL) is a poor-prognostic neoplasm. Differentiation stage and immune-effector functions of the underlying tumor cell are insufficiently characterized. Constitutive activation of the T-cell leukemia 1A (TCL1A) oncogene distinguishes the (pre)leukemic cell from regular postthymic T cells. We assessed activation-response patterns of the T-PLL lymphocyte and interrogated the modulatory impact by TCL1A. Immunophenotypic and gene expression profiles revealed a unique spectrum of memory-type differentiation of T-PLL with predominant central-memory stages and frequent noncanonical patterns. Virtually all T-PLL expressed a T-cell receptor (TCR) and/or CD28-coreceptor without overrepresentation of specific TCR clonotypes. The highly activated leukemic cells also revealed losses of negative-regulatory TCR coreceptors (eg, CTLA4). TCR stimulation of T-PLL cells evoked higher-than-normal cell-cycle transition and profiles of cytokine release that resembled those of normal memory T cells. More activated phenotypes and higher TCL1A correlated with inferior clinical outcomes. TCL1A was linked to the marked resistance of T-PLL to activation- and FAS-induced cell death. Enforced TCL1A enhanced phospho-activation of TCR kinases, second-messenger generation, and JAK/STAT or NFAT transcriptional responses. This reduced the input thresholds for IL-2 secretion in a sensitizer-like fashion. Mice of TCL1A-initiated protracted T-PLL development resembled such features. When equipped with epitope-defined TCRs or chimeric antigen receptors, these Lckpr-hTCL1Atg T cells gained a leukemogenic growth advantage in scenarios of receptor stimulation. Overall, we propose a model of T-PLL pathogenesis in which TCL1A enhances TCR signals and drives the accumulation of death-resistant memory-type cells that use amplified low-level stimulatory input, and whose loss of negative coregulators additionally maintains their activated state. Treatment rationales are provided by combined interception in TCR and survival signaling.

Imaging, quantification and visualization of spatio-temporal patterning in mESC colonies under different culture conditions.

MOTIVATION: Mouse embryonic stem cells (mESCs) have developed into a prime system to study the regulation of pluripotency in stable cell lines. It is well recognized that different, established protocols for the maintenance of mESC pluripotency support morphologically and functionally different cell cultures. However, it is unclear how characteristic properties of cell colonies develop over time and how they are re-established after cell passage depending on the culture conditions. Furthermore, it appears that cell colonies have an internal structure with respect to cell size, marker expression or biomechanical properties, which is not sufficiently understood. The analysis of these phenotypic properties is essential for a comprehensive understanding of mESC development and ultimately requires a bioinformatics approach to guarantee reproducibility and high-throughput data analysis. RESULTS: We developed an automated image analysis and colony tracking framework to obtain an objective and reproducible quantification of structural properties of cell colonies as they evolve in space and time. In particular, we established a method that quantifies changes in colony shape and (internal) motion using fluid image registration and image segmentation. The methodology also allows to robustly track motion, splitting and merging of colonies over a sequence of images. Our results provide a first quantitative assessment of temporal mESC colony formation and estimates of structural differences between colony growth under different culture conditions. Furthermore, we provide a stream-based visualization of structural features of individual colonies over time for the whole experiment, facilitating visual comprehension of differences between experimental conditions. Thus, the presented method establishes the basis for the model-based analysis of mESC colony development. It can be easily extended to integrate further functional information using fluorescence signals and differentiation markers. AVAILABILITY: The analysis tool is implemented C++ and Mathematica 8.0 (Wolfram Research Inc., Champaign, IL, USA). The tool is freely available from the authors. We will also provide the source code upon request. CONTACT: nico.scherf@tu-dresden.de.

Therapy of chronic myeloid leukaemia can benefit from the activation of stem cells: simulation studies of different treatment combinations.

BACKGROUND: Newly diagnosed patients with chronic myeloid leukaemia (CML) are currently treated with tyrosine kinase inhibitors (TKIs) such as imatinib, nilotinib or dasatinib. However, incomplete eradication of residual disease is a general problem of long-term TKI therapy. Activation of mouse haematopoietic stem cells by interferon-α (IFNα) stimulated the discussion of whether a combination treatment leads to accelerated eradication of the CML clone. METHODS: We base our simulation approach on a mathematical model describing human CML as a competition phenomenon between normal and malignant cells. We amend this model to incorporate the description of IFNα activity and simulate different scenarios for potential treatment combinations. RESULTS: We demonstrate that the overall sensitivity of CML stem cells to IFNα activation is a crucial determinant for the benefit of a potential combination therapy. We furthermore show that pulsed IFNα together with continuous TKI administration is the most promising strategy for a combination treatment in which the therapeutic benefit prevails adverse side effects. CONCLUSION: Our modelling approach is a highly beneficial tool to quantitatively address the competition between normal and leukaemic haematopoiesis in treated CML patients. We derive testable predictions for different experimental settings that are suggested before the clinical implementation of the combination treatment.

Differential response to cytotoxic therapy explains treatment dynamics of acute myeloid leukaemia patients: insights from a mathematical modelling approach.

Disease response and durability of remission are very heterogeneous in patients with acute myeloid leukaemia (AML). There is increasing evidence that the individual risk of early relapse can be predicted based on the initial treatment response. However, it is unclear how such a correlation is linked to functional aspects of AML progression and treatment. We suggest a mathematical model in which leukaemia-initiating cells and normal/healthy haematopoietic stem and progenitor cells reversibly change between an active state characterized by proliferation and chemosensitivity and a quiescent state, in which the cells do not divide, but are also insensitive to chemotherapy. Applying this model to 275 molecular time courses of nucleophosmin 1-mutated patients, we conclude that the differential chemosensitivity of the leukaemia-initiating cells together with the cells' intrinsic proliferative capacity is sufficient to reproduce both, early relapse as well as long-lasting remission. We can, furthermore, show that the model parameters associated with individual chemosensitivity and proliferative advantage of the leukaemic cells are closely linked to the patients' time to relapse, while a reliable prediction based on early response only is not possible based on the currently available data. Although we demonstrate with our approach, that the complete response data is sufficient to quantify the aggressiveness of the disease, further investigations are necessary to study how an intensive early sampling strategy may prospectively improve risk assessment and help to optimize individual treatments.

QuickMap: a public tool for large-scale gene therapy vector insertion site mapping and analysis.

Several events of insertional mutagenesis in pre-clinical and clinical gene therapy studies have created intense interest in assessing the genomic insertion profiles of gene therapy vectors. For the construction of such profiles, vector-flanking sequences detected by inverse PCR, linear amplification-mediated-PCR or ligation-mediated-PCR need to be mapped to the host cell's genome and compared to a reference set. Although remarkable progress has been achieved in mapping gene therapy vector insertion sites, public reference sets are lacking, as are the possibilities to quickly detect non-random patterns in experimental data. We developed a tool termed QuickMap, which uniformly maps and analyzes human and murine vector-flanking sequences within seconds (available at www.gtsg.org). Besides information about hits in chromosomes and fragile sites, QuickMap automatically determines insertion frequencies in +/- 250 kb adjacency to genes, cancer genes, pseudogenes, transcription factor and (post-transcriptional) miRNA binding sites, CpG islands and repetitive elements (short interspersed nuclear elements (SINE), long interspersed nuclear elements (LINE), Type II elements and LTR elements). Additionally, all experimental frequencies are compared with the data obtained from a reference set, containing 1 000 000 random integrations ('random set'). Thus, for the first time a tool allowing high-throughput profiling of gene therapy vector insertion sites is available. It provides a basis for large-scale insertion site analyses, which is now urgently needed to discover novel gene therapy vectors with 'safe' insertion profiles.

Insertional mutagenesis and clonal dominance: biological and statistical considerations.

Improvements of (retroviral) gene transfer vectors, stem cell isolation and culture techniques as well as transduction protocols eventually resulted not only in the successful genetic modification of cells capable of reconstituting the haematopoietic system in various animal models, but also human beings. This was a conditio sine qua non for the successful application of gene therapy for inherited diseases as meanwhile achieved for severe combined immune deficiencies (SCID-X1, ADA-SCID) and chronic granulomatous disease (CGD). Unexpectedly, in long-term animal experiments as well as in the follow up of patients from the CGD trial, haematopoietic clones bearing insertions in certain gene loci became dominant, which was most apparent in the myeloid blood compartment. Accumulating data strongly suggest that this clonal dominance was due to some growth and/or survival advantage conferred by gene-activating or -suppressing effects of the integrated retroviral vector (insertional mutagenesis). Importantly, such induced clonal dominance seems not to lead to malignant transformation of affected cell clones inadvertently. The latter finding has become the basis for the concept of 'induced haematopoietic stem cells', a potentially powerful tool to investigate genes involved in the regulation of mechanisms underlying competitive advantages of stem cells, but also in the multi-step nature of malignant transformation. Here we discuss promises and open issues of this concept as well as the important question of common insertion sites statistics and its pitfalls.

Activation of Evi1 inhibits cell cycle progression and differentiation of hematopoietic progenitor cells.

The transcription factor Evi1 has an outstanding role in the formation and transformation of hematopoietic cells. Its activation by chromosomal rearrangement induces a myelodysplastic syndrome with progression to acute myeloid leukemia of poor prognosis. Similarly, retroviral insertion-mediated upregulation confers a competitive advantage to transplanted hematopoietic cells, triggering clonal dominance or even leukemia. To study the molecular and functional response of primary murine hematopoietic progenitor cells to the activation of Evi1, we established an inducible lentiviral expression system. EVI1 had a biphasic effect with initial growth inhibition and retarded myeloid differentiation linked to enhanced survival of myeloblasts in long-term cultures. Gene expression microarray analysis revealed that within 24 h EVI1 upregulated 'stemness' genes characteristic for long-term hematopoietic stem cells (Aldh1a1, Abca1, Cdkn1b, Cdkn1c, Epcam, among others) but downregulated genes involved in DNA replication (Cyclins and their kinases, among others) and DNA repair (including Brca1, Brca2, Rad51). Cell cycle analysis demonstrated EVI1's anti-proliferative effect to be strictly dose-dependent with accumulation of cells in G0/G1, but preservation of a small fraction of long-term proliferating cells. Although confined to cultured cells, our study contributes to new hypotheses addressing the mechanisms and molecular targets involved in preleukemic clonal dominance or leukemic transformation by Evi1.

T-cell receptor diversity prevents T-cell lymphoma development.

Mature T-cell lymphomas (MTCLs) have an extremely poor prognosis and are much less frequent than immature T-cell leukemias. This suggests that malignant outgrowth of mature T lymphocytes is well controlled. Indeed, in a previous study we found that mature T cells are resistant to transformation with known T-cell oncogenes. Here, however, we observed that T-cell receptor (TCR) mono-/oligoclonal mature T cells from TCR transgenic (tg) mice (OT-I, P14) expressing the oncogenes NPM/ALK or ΔTrkA readily developed MTCLs in T-cell-deficient recipients. Analysis of cell surface markers largely ruled out that TCR tg lymphomas were derived from T-cell precursors. Furthermore, cotransplanted non-modified TCR polyclonal T cells suppressed malignant outgrowth of oncogene expressing TCR tg T lymphocytes. A dominant role of an anti-leukemic immune response or Tregs in the control of MTCLs seems unlikely as naïve T cells derived from oncogene expressing stem cells, which should be tolerant to leukemic antigens, as well as purified CD4 and CD8 were resistant to transformation. However, our results are in line with a model in which homeostatic mechanisms that stabilize the diversity of the normal T-cell repertoire, for example, clonal competition, also control the outgrowth of potentially malignant T-cell clones. This study introduces a new innate mechanism of lymphoma control.

A novel view on stem cell development: analysing the shape of cellular genealogies.

OBJECTIVES: The analysis of individual cell fates within a population of stem and progenitor cells is still a major experimental challenge in stem cell biology. However, new monitoring techniques, such as high-resolution time-lapse video microscopy, facilitate tracking and quantitative analysis of single cells and their progeny. Information on cellular development, divisional history and differentiation are naturally comprised into a pedigree-like structure, denoted as cellular genealogy. To extract reliable information concerning effecting variables and control mechanisms underlying cell fate decisions, it is necessary to analyse a large number of cellular genealogies. MATERIALS AND METHODS: Here, we propose a set of statistical measures that are specifically tailored for the analysis of cellular genealogies. These measures address the degree and symmetry of cellular expansion, as well as occurrence and correlation of characteristic events such as cell death. Furthermore, we discuss two different methods for reconstruction of lineage fate decisions and show their impact on the interpretation of asymmetric developments. In order to illustrate these techniques, and to circumvent the present shortage of available experimental data, we obtain cellular genealogies from a single-cell-based mathematical model of haematopoietic stem cell organization. RESULTS AND CONCLUSIONS: Based on statistical analysis of cellular genealogies, we conclude that effects of external variables, such as growth conditions, are imprinted in their topology. Moreover, we demonstrate that it is essential to analyse timing of cell fate-specific changes and of occurrence of cell death events in the divisional context in order to understand the mechanisms of lineage commitment.

Increased power of microarray analysis by use of an algorithm based on a multivariate procedure.

MOTIVATION: The power of microarray analyses to detect differential gene expression strongly depends on the statistical and bioinformatical approaches used for data analysis. Moreover, the simultaneous testing of tens of thousands of genes for differential expression raises the 'multiple testing problem', increasing the probability of obtaining false positive test results. To achieve more reliable results, it is, therefore, necessary to apply adjustment procedures to restrict the family-wise type I error rate (FWE) or the false discovery rate. However, for the biologist the statistical power of such procedures often remains abstract, unless validated by an alternative experimental approach. RESULTS: In the present study, we discuss a multiplicity adjustment procedure applied to classical univariate as well as to recently proposed multivariate gene-expression scores. All procedures strictly control the FWE. We demonstrate that the use of multivariate scores leads to a more efficient identification of differentially expressed genes than the widely used MAS5 approach provided by the Affymetrix software tools (Affymetrix Microarray Suite 5 or GeneChip Operating Software). The practical importance of this finding is successfully validated using real time quantitative PCR and data from spike-in experiments. AVAILABILITY: The R-code of the statistical routines can be obtained from the corresponding author. CONTACT: Schuster@imise.uni-leipzig.de

Interactions of erythropoietin, granulocyte colony-stimulating factor, stem cell factor, and interleukin-11 on murine hematopoiesis during simultaneous administration.

We investigated how in vivo effects of single hematopoietic cytokines change if given in combination for a prolonged time. Mice were treated with every combination of recombinant human (rh) erythropoietin (EPO), rh granulocyte colony-stimulating factor (G-CSF), recombinant rat (rr) stem cell factor (SCF), and rh interleukin (IL)-11 by continuous infusion over 7 days (full factorial design with three dose levels for each cytokine). Burst-forming unit-erythroid (BFU-E), colony-forming unit-erythroid (CFU-E), and colony-forming unit-granulocyte-macrophage (CFU-GM) were determined in bone marrow and spleen, reticulocytes, hematocrit, granulocytes, and thrombocytes in the peripheral blood. An analysis of variance (ANOVA) and multiple comparison of means was used to evaluate the data. For several cell types, cytokine effects superimposed in an additive way if combined. However, in a large number of circumstances, nonadditive pairwise interactions were found. They differed in type and magnitude involving high-dose saturation, high-dose antagonistic effects, and even effect reversals (qualitative interactions). Hence, in general, it was not possible to foresee the combination effects on the basis of existing knowledge of single effects. On the other hand, the cytokine network was robust and no system hazards were observed under multiple cytokine combinations. The results illustrate that the cytokine network has nonlinear dynamic properties in vivo with dose-response characteristics of one cytokine being continuously modified by other cytokines.