OBJECTIVES/GOALS: Aim 1: Define the genetic events that cooperate with Trp53 mutations to mediate the transformation of MDS to sAML at the stem cell level. Aim 2: Use Bayesian networks to model the signaling pathway activation states identify aberrant regulators of self-renewal in LSCs. METHODS/STUDY POPULATION: To model the transformation of MDS, I will utilize a mouse model of MDS and sAML. The Trp53 mutated mouse mimics the genetics of human MDS and develops MDS. To discover how additional mutations contribute to disease progression, I use the Sleeping Beauty transposon system which induces random mutations. I propose to use this mouse model to define the molecular mechanisms of transformation of MDS to sAML. I will also measure levels of activated signaling intermediates in sAML using CyTOF. CyTOF is a method of flow cytometry that measures up to 40 proteins simultaneously at single-cell resolution. I will also use Bayesian network to model the signaling architecture of the MDS/sAML stem cells. RESULTS/ANTICIPATED RESULTS: I will identify putative mediators of self-renewal in gene expression data and the corresponding Bayesian networks model. I will prioritize genes and signaling intermediates that act in pathways that rank highly in both methods and those that have previously published roles in self-renewal. Based on prior work, I will focus on EZH2, NFï «B, and mTOR pathways in addition to candidate pathways revealed by these studies. Small molecule inhibitors that target candidate signaling intermediates will be used for experimental validation. I will test the impact of these small molecule inhibitors on LSC self-renewal using serial colony forming assays as well as in vivo mouse reconstitution assays. DISCUSSION/SIGNIFICANCE: We focus on the role of stem cells in the transformation of MDS to sAML. Understanding the mutations and signaling relationships that mediate self-renewal in Trp53 mutant stem cells will allow for precise therapeutic target of this disease and improve outcomes for these patients.