Diane Heiser

FLT3-ITD Knockin Impairs Hematopoietic Stem Cell Quiescence/Homeostasis, Leading to Myeloproliferative Neoplasm

Internal tandem duplication (ITD) mutations within the FMS-like tyrosine kinase-3 (FLT3) render the receptor constitutively active driving proliferation and survival in leukemic blasts. Expression of FLT3-ITD from the endogenous promoter in a murine knockin model results in progenitor expansion and a myeloproliferative neoplasm. In this study, we show that this expansion begins with overproliferation within a compartment of normally quiescent long-term hematopoietic stem cells (LT-HSCs), which become rapidly depleted. This depletion is reversible upon treatment with the small molecule inhibitor Sorafenib, which also ablates the disease. Although the normal LT-HSC has been defined as FLT3(-) by flow cytometric detection, we demonstrate that FLT3 is capable of playing a role within this compartment by examining the effects of constitutively activated FLT3-ITD. This indicates an important link between stem cell quiescence/homeostasis and myeloproliferative disease while also giving novel insight into the emergence of FLT3-ITD mutations in the evolution of leukemic transformation.

Deletion of Tristetraprolin Caused Spontaneous Reactive Granulopoiesis by a Non–Cell-Autonomous Mechanism Without Disturbing Long-Term Hematopoietic Stem Cell Quiescence

Tristetraprolin (TTP, Zfp36, Nup475, Tis11) dramatically reduces the stability of target mRNAs by binding to AU-rich elements in their 3′ untranslated regions. Through this mechanism, TTP functions as a rheostatic, temporal regulator of gene expression. TTP knockout (KO) mice exhibit completely penetrant granulocytic hyperplasia. We have shown that the hematopoietic stem-progenitor cell compartment in TTP KO mice is also altered. Although no change was detected in long-term hematopoietic stem cell (HSC) frequency or function, as assayed by immunophenotypic markers or limiting dilution transplants, we observed increases in the frequencies and numbers of short-term HSCs, multipotent progenitors, and granulocyte–monocyte progenitors. This pattern is consistent with “reactive granulopoiesis,” in which committed myeloid progenitors and more primitive progenitors cycle more actively to increase production of mature granulocytes in response to infection or adjuvant. We created reverse chimeras by transplanting wild-type bone marrow into TTP KO mice and found the “reactive granulopoiesis” phenocopied, indicating a non–hematopoietic stem-progenitor cell–autonomous mechanism. Correspondingly, we found elevated levels of the granulopoietic TTP targets IL-1β, TNF-α, and IL-6 in the plasma of TTP KO mice. Consistent with the non–cell-autonomous nature of the phenotype, we found elevated levels of IL-1β, TNF-α, and IL-6 transcripts in the livers of TTP KO mice and no detectable difference in the bone marrows. These findings demonstrate the importance of TTP in inflammatory homeostasis and highlight the ability of the hematopoietic system to respond to stress without significant numbers of quiescent HSCs entering the cell cycle.

Correlated miR-mRNA Expression Signatures of Mouse Hematopoietic Stem and Progenitor Cell Subsets Predict “Stemness” and “Myeloid” Interaction Networks

Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a “stemness” signature in the most primitive hematopoietic stem cell (HSC) populations, as well as “myeloid” patterns associated with two branches of myeloid development.

Inferring MicroRNA Regulation of mRNA with Partially Ordered Samples of Paired Expression Data and Exogenous Prediction Algorithms

MicroRNAs (miRs) are known to play an important role in mRNA regulation, often by binding to complementary sequences in “target” mRNAs. Recently, several methods have been developed by which existing sequence-based target predictions can be combined with miR and mRNA expression data to infer true miR-mRNA targeting relationships. It has been shown that the combination of these two approaches gives more reliable results than either by itself. While a few such algorithms give excellent results, none fully addresses expression data sets with a natural ordering of the samples. If the samples in an experiment can be ordered or partially ordered by their expected similarity to one another, such as for time-series or studies of development processes, stages, or types, (e.g. cell type, disease, growth, aging), there are unique opportunities to infer miR-mRNA interactions that may be specific to the underlying processes, and existing methods do not exploit this. We propose an algorithm which specifically addresses [partially] ordered expression data and takes advantage of sample similarities based on the ordering structure. This is done within a Bayesian framework which specifies posterior distributions and therefore statistical significance for each model parameter and latent variable. We apply our model to a previously published expression data set of paired miR and mRNA arrays in five partially ordered conditions, with biological replicates, related to multiple myeloma, and we show how considering potential orderings can improve the inference of miR-mRNA interactions, as measured by existing knowledge about the involved transcripts.