Novel technologies for understanding the repertoire of tumour infiltrating T cells in cancer

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Published: 7 Apr 2016
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Prof Sine Reker Hadrup - Technical University of Denmark, Kongens Lyngby, Denmark

Prof Sine Reker Hadrup talks to ecancertv at ITOC-3 about her labs novel techniques in identifying T cell binding peptides and infiltration to tumours.

By designing MHC-1 multimers with UV sensitive peptides and utilising high throughput techniques, they have been able to generate large libraries of reagents.

From these, it is possible to stain T cells from tissue samples and follow specific immune reactivity in tumours.

 

 

 

3rd Immunotherapy of Cancer Conference (ITOC3)

Novel technologies for understanding the repertoire of tumour infiltrating T cells in cancer

Prof Sine Reker Hadrup - Technical University of Denmark, Kongens Lyngby, Denmark


We’re mostly focussed on trying to assess the T-cell receptor peptide MHC interactions so we design MHC multimers, meaning that this MHC class 1 complex is loaded with peptides of different origin of interest. We have some high throughput techniques to generate these in large numbers which means that we can cover or generate these reagents based on HLA types at least to a large extent. So what we do is that we, for example for a given patient cohort, identify peptides of potential interest in the certain disease settings and then we generate reagents matching these based on the HLA expression of the patient.

In a bit more detail what we do is that we have a UV sensible peptide that is cleavable so we can basically exchange peptides sitting in the groove from a standard complex carrying this conditional ligand to any peptide of interest. So by this means we can generate large libraries of peptide MHC radians in a relatively short period of time. Then we can create these radians for which we can actually stain T-cells from tissue samples.

Can you tell us a little bit about research you have worked on so far?

We have techniques for which we firstly label these free agents so that we are able to mix many in single samples and we are also further chasing this route to get even higher complexity in our assays. But, for example, we have recently in collaboration with people in the UK at UCL, Charles Swanton and group, worked in a non-small cell lung cancer study where we looked at whether T-cells would recognise changes occurring in tumours upon mutation changes and specifically focused on mutation that arises in what you can say as the trunk of the tumour so that it’s clonally distributed in all the tumour cells so you can basically really hit the core of the tumour. We can see that we have specific immune reactivity specifically directed against those types of mutations.

Can you tell us more about the exciting work you have in the pipeline?

We are definitely working to increase the complexity of these techniques and what we believe that we can do then is that we can much better go into a different type of patient material, for example to find these mutation-derived new epitopes also in peripheral blood and in tissue biopsies without having to expand T-cell at first before which you always introduce some bias to the T-cell repertoire. So we can better mimic basically what is really happening in the tissue with these more advanced techniques that we are working on. So far what we do is more like in an exploratory phase where we haven’t screened a large patient cohort but for detection of these mutation-derived new epitopes in cancer we specifically see that within this study in lung cancer, together with Charles Swanton, that we see this reactivity primarily directed against these clonal antigens and that so far it’s pretty significant and we haven’t seen any responses that are directed against these sub-clonal mutations. So there seem to be some characteristics but we don’t know why this is, whether it’s a matter of expression level or it can be other reasons why these mutations are predominantly recognised by the immune system.

What needs to be done, moving forward?

I think at least in this direction of understanding immune recognition of cancer I think what we really need is to have better predictive tools so that we can really find out in this huge landscape, for example, of mutational changes which are the ones that are likely to be immunogenic because now we are really like looking for the needle in the haystack whereas if we would have better ways to focus our libraries we would have a much better chance to find them but also a better way to have predictive tools.