Inflammation in X - linked Adrenoleukodystrophy

Project Description: Cells compute by processing external stimuli according to their internal state, abiding to rules that remain poorly understood (Rubens et al., 2016). Cell fate decisions are the key for constructing a multicellular organism. Errors, bias or aberrant delays in making such decisions can lead to neoplasia or in extreme cases, tumorigenesis. Our key question is how cells make decisions in a context of a multicellular organism. Here we propose an interdisciplinary study to uncover the detailed molecular logic driving cell fate decisions in a context of multipotent neural crest lineage. To achieve this, we will combine large-scale singlecell transcriptional measurements (Fan et al., 2016) with color-multiplexed lineage tracing (“Confetti”) performed in collaboration with Peter Kharchenko lab at Harvard Medical School. Applying advanced newly-proposed methods, we will analyze developmental trajectories and fate splits in the transcriptional space, lineage-specific modules and fate-biasing genes, and in addition will perform inference of early transcriptional regulatory events and signaling pathways associated with cell fate decisions in normal development and pathology. We expect the proposed computational and experimental pipelines will be widely applicable to other developmental and regenerative biology problems. We aim to predict and validate fate decisions in the entire neural crest lineage in mouse and human embryos, and to uncover the critical events leading from neural crest to different malignancies and congenital abnormalities. More precisely, we will focus on cancers arising from the neural crest-derived sympathoadrenal cells including pheochromocytoma (PCC), paraganglioma (PGL) and neuroblastoma (NB). In preliminary data we observed that these tumors are highly heterogeneous and resemble some stages of neural crest differentiation into chromaffin or glomus cells or sympathetic neuroblasts. Identifying the origins of different malignancy subtypes will help to reveal the causes of disease heterogeneity and to predict clinical behavior. Creating “comparative identity maps” using single cell analyses of tumors and healthy progenitor populations will allow us to identify the differentiation statuses for different subtypes of PCC, PGL and NB. This, in turn, we allow us to design new drugs that will drive the tumor in a more differentiated and less malignant state. The Project entails the combination of developmental biology, comparative embryology, cancer research and advanced bioinformatics. Strong candidates are expected to have a good knowledge of developmental neurobiology or be strong in computer sciences or both.