Spatially Resolved Gene Expression in Early Detection of Cancer
Joakim Lundeberg, PhD, Professor, Science for Life Laboratory, KTH Royal Institute of Technology
Tissue represents an ecosystem of different cells carrying out various tasks. Specific types of cells exist in every organ and serve specialized functions defined by the particular genes and proteins in each cell type. In disease, a fraction of cells often lose their gene expression patterns and often impact the morphology of the tissue. The latter is frequently used in disease stratification. The new spatial technologies to overlay both gene expression information and morphology hold great promise for more precise analysis. Thus spatial multimodal maps to describe and explain the cellular basis of health and disease are quickly evolving. We have developed and established the Spatial Transcriptomics technology, in which tissue imaging is merged with spatial RNA sequencing and resolved by computational means. Spatial Transcriptomics technology was the first method to provide unbiased whole transcriptome analysis with spatial information from tissue using barcoded array surfaces and had, since the initial publication, been used in multiple biological systems in health and disease. This presentation will cover methodological and analytical aspects of the technology in the context of early events in cancer.
Single-Cell Atlases of the Gut to Prioritise Cells Involved in Disease
Rasa Elmentaite, PhD, Staff Scientist, Wellcome Sanger Institute
The cellular landscape of the human intestinal tract is dynamic throughout life, developing in utero and changing in response to functional requirements and environmental exposures, as well as in health and disease. To comprehensively map cell lineages, we used single-cell RNA sequencing and antigen receptor analysis of almost half a million cells from up to 5 anatomical regions in the developing and up to 11 distinct anatomical regions in the healthy paediatric and adult human gut. We discover new disease-relevant biology, including the presence of BEST4 cells with links to cystic fibrosis, neuronal developmental lineages associated with Hirschsprung’s disease, and expansion of immune recruiting fibroblasts relevant to inflammatory bowel disease. We envisage using single-cell technologies in accelerating drug discovery using human data. Therapeutic avenues include the use of single-cell genomics to stratify patients on the basis of their cellular responses to disease; prediction of the organ of action and drug delivery route; design of molecular diagnostics based on precise cellular markers; and cell therapy design based on tissue-resident immune cell profiles.