Summary
Despite the constant surveillance of immune cells, tumour cells can still evade the immune response. Unravelling the interactions of T cells and B cells with tumour cells can shed light on tumour evasion. Extensive research is focused on the mechanisms of activation of an immune response in T cells. However, it is known that detection events, i.e., physical contact between individual surveying T cells and tumour cells, don’t necessarily lead to such activation. Little is known about physical interactions between T cells and tumour cells that do not end in activation. Here I suggest focusing on these detection-without activation events. In these cases, how is the detection information encoded in T cells? i.e., How are T cells and other immune cells affected by the interaction with tumour cells on the molecular level?. My working assumption is that the evading mechanism can be manifested as a physical change in immune cells upon touching tumour cells, and I suggest detecting the ‘smoking gun’ of this process in biopsies, in the form of changes in the gene expression program of touching immune cells. This was not done before because it is almost impossible to study single interacting cells in tumour tissues. It requires both high spatial resolution, to detect individually interacting cells, and high molecular resolution, to quantify cell types and states. Here, using a technology I developed for in situ sequencing with super-resolution, I will generate the first dataset of super-resolved spatial genomics mapping of human biopsies and detect tens of thousands of individual interactions between physically touching immune and tumour cell types. I will then build a new imaging technology to sequence T cell and B cell receptor in situ and detect tumour-specific ones, and will build a computational framework to detect genes and pathways involved in the immune-tumour crosstalk. This will reveal mechanistic insights into tumour evasion and suggest directions for its reversion.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101117324 |
| Start date: | 01-09-2023 |
| End date: | 31-08-2028 |
| Total budget - Public funding: | 2 124 896,00 Euro - 2 124 896,00 Euro |
Cordis data
Original description
Despite the constant surveillance of immune cells, tumour cells can still evade the immune response. Unravelling the interactions of T cells and B cells with tumour cells can shed light on tumour evasion. Extensive research is focused on the mechanisms of activation of an immune response in T cells. However, it is known that detection events, i.e., physical contact between individual surveying T cells and tumour cells, don’t necessarily lead to such activation. Little is known about physical interactions between T cells and tumour cells that do not end in activation. Here I suggest focusing on these detection-without activation events. In these cases, how is the detection information encoded in T cells? i.e., How are T cells and other immune cells affected by the interaction with tumour cells on the molecular level?. My working assumption is that the evading mechanism can be manifested as a physical change in immune cells upon touching tumour cells, and I suggest detecting the ‘smoking gun’ of this process in biopsies, in the form of changes in the gene expression program of touching immune cells. This was not done before because it is almost impossible to study single interacting cells in tumour tissues. It requires both high spatial resolution, to detect individually interacting cells, and high molecular resolution, to quantify cell types and states. Here, using a technology I developed for in situ sequencing with super-resolution, I will generate the first dataset of super-resolved spatial genomics mapping of human biopsies and detect tens of thousands of individual interactions between physically touching immune and tumour cell types. I will then build a new imaging technology to sequence T cell and B cell receptor in situ and detect tumour-specific ones, and will build a computational framework to detect genes and pathways involved in the immune-tumour crosstalk. This will reveal mechanistic insights into tumour evasion and suggest directions for its reversion.Status
SIGNEDCall topic
ERC-2023-STGUpdate Date
12-03-2024
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