Digital single cell immunology: decoding cellular interactions for improved immunotherapy
Successful immunotherapy against cancer is the result of a multitude of cellular interactions within the immune system. It is highly exciting how vaccination with small numbers of human plasmacytoid dendritic cells (pDCs) can induce anti-tumour immunity in metastatic cancer patients. Remarkably, how pDCs, as an extremely rare subset of cells, can act as Swiss army knives to regulate the tight balance between tolerance and immunity: i.e. secrete massive amounts of type I IFNs, prime T cells and exert cytotoxic effector functions, is still elusive. Do pDCs possess all functions or comprises the population distinct functional subsets all with their specialized roles. I will unravel which pDC is superior in inducing cytotoxic T cells (CTLs) for augmented cancer immunity. Despite advances in single cell technologies, understanding the role of heterogeneity in immune cell populations, remains poorly understood. In ImmunoCode, I will develop a novel and ambitious single cell technology platform, wherein innovative microfluidic approaches and single cell transcriptomics allow 1) functional analysis of single (pairs of) immune cells and 2) design of minimal environments under the omission of external factors that could influence cellular behaviour. This approach will provide me with the unique opportunity to unravel pDC function and plasticity. Although in this ERC proposal I will focus on understanding pDCs heterogeneity, my technology can in fact be exploited to any cell type that shows heterogeneous function. My unique and high-risk technical approach allows for decoding immune cell-cell or cell-pathogen interactions longitudinally and in great detail which will revolutionise the fields of immunology and cellular immunotherapy. Ultimately, ImmunoCode will have a tremendous impact by refining the design of vaccine strategies and the development of differently composed cellular vaccines to battle cancer and infectious and auto-immune diseases.