Image-based isolation of single cells for sequencing - Polso, Minttu (My University, 2020)
Cancer is a complex disease characterized by unregulated cell division, resistance towards cell death, activated tissue invasion and the ability to metastasize. Tumors typically display heterogeneous mixture of cancer cells containing also many other cell types, such as stromal and immune cells. This phenotypic heterogeneity can have a great impact on the success of the treatments, such as immuno- or targeted therapies. To understand cancer heterogeneity, it is essential to develop techniques, which enable us to recognize different cell populations and gain more information from their ‘omic’ backgrounds, whilst keeping their spatial data. The aim of this Pro Gradu project was to set up a new technology for spatial isolation of single cells from tissues or cell cultures. As a cancer model for the optimization, we selected a renal cell carcinoma (RCC), which is among ten most common cancers in the world. The heterogeneity of the tumors makes it difficult to find appropriate treatment for RCC patients, leading to ~ 30% of recurrence rate. The technology, setup together with the Horvath group, is based on computer-assisted microscopy isolation (CAMI), which combines high-content (HC) microscopy of cells with machine learning-based image recognition. This allows us, by using laser microdissection microscope, to extract single cells based on their phenotypic characteristics, for the follow-up studies e.g. transcriptomics. The system setup included optimization of protocols for the cell culture on CAMI suitable microscopy slides, HC-imaging, laser cutting, and RNA extraction using RCC cell line, patient derived cancer cells (PDCs) and FFPE tissue blocks as sample material. To conclude, we have an up and running system for image-based isolation of single cells from tissue and cell culture, whilst some further optimization is still needed for obtaining better RNA quality.
Keywords: cancer, live cell staining, HC-imaging, heterogeneity, single cell isolation, laser microdissection