Harnessing Single Cell Technology to Define Self-Renewal in Normal and Malignant Stem Cells

Abstract The major clinical issue in hematological cancers is relapse. Patients often respond very well to chemotherapy, and can go years without any sign of disease, but a subset of patients will invariably re-develop leukemia with a poor final prognosis. Relapse occurs because our current chemotherapies are unable to reliably and completely eliminate leukemia stem cells. These cells are unique among the leukemic cell population in that they can self-renew, meaning that they can replenish a leukemia indefinitely, similar to the role of the hematopoietic stem cells in replenishing the normal blood system. Blocking self-renewal of these cells would stop their ability to form relapse, making them an ideal drug target. Unfortunately, leukemia stem cells and the mechanisms that allow them to self-renew remain frustratingly enigmatic. A major issue in regards to studying these cells is their rarity; they comprise 1 in every 105-107 cells within the total leukemic cell population in human ALL and mouse models, and they cannot be maintained efficiently ex vivo. Researchers necessarily rely on FACS enrichment based on certain cell surface markers, but this process is known to exclude subsets self-renewing cells that don’t express the selected markers. The goal of this project is to define what leukemia stem cells are. We will determine how they differ from normal hematopoeitic stem cells, which can also self-renew, and how are they unique from other leukemic cells that cannot self-renew. Based on these data, we will find ways to detect leukemia stem cells in patients, and identify drugs that target these cells and their self-renewal ability. Initially, we will use a panel of high self-renewing acute lymphoblastic leukemias and hematopoietic stem cells isolated from zebrafish models, which will allow us to use single cell technology to identify the attributes of self-renewing normal and malignant cells in a completely unbiased manner. We will translate our findings to human cells to build a biomarker panel that can detect the frequency of self-renewing cells in patient samples. We will return to zebrafish models to develop transgenic animals in which leukemia stem cells are fluorescently labeled, and use these animals in drug screens to identify compounds that are capable of either killing these cells outright, or blocking their self-renewal potential. In total, this project will provide the first unbiased, single cell analysis of any type of cancer stem cell, allowing us to answer fundamental questions in cancer biology, yet the data we obtain will be immediately useful for translational application.