Shaping axial identity during human pluripotent stem cell differentiation to neural crest cells

The neural crest (NC) is a multipotent cell population which can give rise to a vast array of derivatives including neurons and glia of the peripheral nervous system, cartilage, cardiac smooth muscle, melanocytes and sympathoadrenal cells. An attractive strategy to model human NC development and associated birth defects as well as produce clinically relevant cell populations for regenerative medicine applications involves the in vitro generation of NC from human pluripotent stem cells (hPSCs). However, in vivo, the potential of NC cells to generate distinct cell types is determined by their position along the anteroposterior (A–P) axis and, therefore the axial identity of hPSC-derived NC cells is an important aspect to consider. Recent advances in understanding the developmental origins of NC and the signalling pathways involved in its specification have aided the in vitro generation of human NC cells which are representative of various A–P positions. Here, we explore recent advances in methodologies of in vitro NC specification and axis patterning using hPSCs.

Developmental Origins of Cardiovascular Disease: Understanding High Mortality Rates in the American South

While many social scientists view heart disease as the outcome of current conditions, this cannot fully explain the significant geographic disparities in cardiovascular disease (CVD) mortality rates in the USA. The developmental origins hypothesis proposes that CVD vulnerability is created by poor conditions in utero that underbuilds major organs relative to those needed to process lush nutrition later in life. The American South underwent an economic transformation from persistent poverty to rapid economic growth in the post-World War II era. We use state-level data on income growth and current conditions to explain variation in CVD mortality rates in 2010–2011. Our proxy for unbalanced physical growth, the ratio of median household income in 1980 to that in 1950, has a large systematic influence on CVD mortality, an impact that increases dramatically with age. The income ratio combined with smoking, obesity, healthcare access, and education explain more than 70% of the variance in CVD mortality rates.

Cell-of-Origin and Genetic, Epigenetic, and Microenvironmental Factors Contribute to the Intra-Tumoral Heterogeneity of Pediatric Intracranial Ependymoma

Intra-tumoral heterogeneity (ITH) is a complex multifaceted phenomenon that posits major challenges for the clinical management of cancer patients. Genetic, epigenetic, and microenvironmental factors are concurrent drivers of diversity among the distinct populations of cancer cells. ITH may also be installed by cancer stem cells (CSCs), that foster unidirectional hierarchy of cellular phenotypes or, alternatively, shift dynamically between distinct cellular states. Ependymoma (EPN), a molecularly heterogeneous group of tumors, shows a specific spatiotemporal distribution that suggests a link between ependymomagenesis and alterations of the biological processes involved in embryonic brain development. In children, EPN most often arises intra-cranially and is associated with an adverse outcome. Emerging evidence shows that EPN displays large intra-patient heterogeneity. In this review, after touching on EPN inter-tumoral heterogeneity, we focus on the sources of ITH in pediatric intra-cranial EPN in the framework of the CSC paradigm. We also examine how single-cell technology has shed new light on the complexity and developmental origins of EPN and the potential impact that this understanding may have on the therapeutic strategies against this deadly pediatric malignancy.

Developmental Deconvolution for Classification of Cancer Origin

Cancer is a disease manifesting in abrogation of developmental programs, and malignancies are named based on their cell or tissue of origin. However, a systematic atlas of tumor origins is lacking. Here we map the single cell organogenesis of 56 developmental trajectories to the transcriptomes of over 10,000 tumors across 33 cancer types. We use this map to deconvolute individual tumors into their constituent developmental trajectories. Based on these deconvoluted developmental programs, we construct a Developmental Multilayer Perceptron (D-MLP) classifier that outputs cancer origin. The D-MLP classifier (ROC-AUC: 0.974 for top prediction) outperforms classification based on expression of either oncogenes or highly variable genes. We analyze tumors from patients with cancer of unknown primary (CUP), selecting the most difficult cases where extensive multimodal workup yielded no definitive tumor type. D-MLP revealed insights into developmental origins and diagnosis for most patient tumors. Our results provide a map of tumor developmental origins, provide a tool for diagnostic pathology, and suggest developmental classification may be a useful approach for otherwise unclassified patient tumors.