Endocrine Abstracts

Recently developed single cell technologies offer unprecedented investigations of cellular heterogeneity. While significant hurdles remain to be overcome, the field is progressing rapidly. In addition to now commonly performed genome and transcriptome analysis, it appears possible to examine the epigenome, proteome and metabolome at the single cell level. In addition, multi-omics technologies are being developed to profile simultaneously different material sources from the same cell, enabling for example correlations between genomic mutations and alteration of genes expression. Genome and transcriptome analyses were initially pricey and required wet-lab specialist skills. However, competitive sequencing costs, commercially available kits for material preparation, along with the development of techniques to extract good quality material from clinical samples render these analyses more accessible to both biomedical and clinical researchers. Nevertheless, specialist platforms for microfluidic or droplet technologies are often required, and specialised bioinformatic support is essential for quality control and data analysis. Single cell analyses have already provided significant advances, in particular in the field of cancer, and stem cell research. In contrast with bulk population analysis, examination of genomic material from tumour single cells reveals cellular heterogeneity, allow reconstitution of cellular hierarchies, and sometimes resolution to the cell(s) of origin of the tumour. This maybe the only way to identify rare cell types, and therefore better characterize mechanisms of resistance to treatments, and tumour reoccurrence. In addition, stromal niche cells can be segregated away from tumour cells, and their analysis offer clues to understand how the microenvironment interact with the tumour cells. Furthermore, characterisation of circulating (CTC) and disseminated (DTC) tumour cells can be performed. In stem cell research, characterisation of differentiation pathways is a central question to improve disease modelling and drug screening assays, and ultimately for regenerative medicine. Single cell transcriptome analysis coupled with the development of specific algorithms allows pseudotime analysis of heterogeneous cellular states, and reconstitution of differentiation pathways, with often characterisation of new, previously invisible, intermediate cell states. A special emphasis will be placed to exemplify the advances these technologies have provided in endocrine systems, in both normal and pathological situations. Finally, current challenges and future developments of these techniques will be discussed.