T-cell recognition and cancer


The overall goal of the research group is to gain insight to T-cell recognition in cancer and autoimmune diseases through development of novel technologies for T-cell detection and characterization.

We do so through several parallel projects covering the following themes:

• Multiplex technologies for T-cell detection
• Native and modified T-cell receptors
• Immune recognition of cancer cells
• Immunotherapy
• Decoding T-cell reactivity in autoimmune diseases
• Automatic gating strategies for flow cytometry

Multiplex technologies for T-cell detection

We have developed a novel technology to tag and track multiple (>1000) antigen-specific T-cell specificities based on their peptide-MHC (pMHC) recognition motif through a pMHC multimer with a co-attached ‘DNA barcode’ (Bentzen/Hadrup unpublished data, patent pending). This technology for the first time implements the use of an oligonucleotide to form a molecular tag that is associated to the identity of the given peptide-MHC complex. The ‘DNA barcode’ will provide a label for the pMHC specificity of the given multimer binding the TCR and thereby reveal the TCR target. The advantage of using DNA barcodes as a novel type of tag for pMHC multimers relates to the overwhelming complexity that can easily be generated by use of this tagging system.

The use of DNA-barcode labelled MHC multimers allow the mixing of >1000 different MHC multimers for T-cell detection. After selection of MHC multimer binding T-cells, the specificity can be revealed by sequencing the co-attached barcode. We have shown that the number of reads for each DNA barcode will correlate to the number of T-cells binding the giving pMHC complex, and that T-cell detection can be accomplished with similar sensitivity as present state-of-the-art technologies.

Native and modified T-cell receptors

We are developing strategies to identify TCR sequences from single-cell sorted T-cells. We aim to use TCR transduced T-cells for adoptive cell therapy in cancer. With Merkel Cell Carcinoma as our model system, we will generate libraries of TCRs to be tested for efficacy in adoptive cell therapy with TCR transduced T-cells in xeno-graft mouse systems.

Immune recognition of cancer cells

The research group has pioneered the use of pMHC multimers for multiplex detection of antigens-responsive T-cells in limited biological material (Hadrup Nat. Method 2009 and Andersen, Nat Protocol 2012). We have a strong technology for multiplex detection of antigen specific T-cells by use of peptide-MHC based reagents. We have developed a high-throughput platform for T-cell epitope mapping and detection of rare populations of pathogen- and cancer-specific T-cell populations, through combinatorial encoding of MHC-multimers. We have used this technology to describe the T-cell recognition in Melanoma and Merkel Cell Carcinoma.

We have used this technology to dissect the antigen specific recognition of tumor infiltrating lymphocytes used for adoptive cell therapy in melanoma patients (Andersen RS, Cancer Res. 2012, Andersen RS, Oncoimmunolgy 2013), to establish efficient in vitro generation of tumor specific T-cells from patient’s peripheral blood suitable for adoptive cell therapy (Brimnes, Cancer Immunol Immunother 2012), and to characterized numerous of T-cell epitopes in the oncogenic virus, Merkel cell polyomavirus (Lyngaa et al, Clin Cancer Res, 2014). Furthermore, we have analyzed how the clinical use of demethylation agents may influence the immune recognition in hematological malignancies (Gang/Frøsig, Blood Cancer Journal 2014).
Link to www.cancer.dk

We are extending these earlier studies to understand the recognition profile of tumor reactive T-cells, with specific interests in the relationship between genetic heterogeneity of cancer and the immune recognition (McGranahan, et al. Science 2016); and the impact of both mutation-derived epitopes and shared antigens in the immune and their relative potential for cancer therapy (Verdegaal, Nature 2016).


In recent years cancer researchers has elucidated how the immune system interacts with developing cancer, and may have the potential to eradicate cancer cells. This has led to an increasing focus on the possibility of combining immunotherapy with conventional treatment (e.g. chemotherapy or radiotherapy). In ongoing studies, we are combining experimental immunotherapy in the form of a peptide vaccination with standard therapy in the form of 5-Azacitidine for treatment of patients with Myelodysplastic syndrome and Acute myeloid leukaemia. Our project is expected to expand our knowledge in regard to combination of immunotherapy and conventional treatment and will be essential for further development of this treatment modality.

We are additionally working on improved methods for expansion of T-cell in-vitro for adoptive cell therapies. These strategies will be tested in NSG xenograft mouse models systems.

Decoding T-cell reactivity in autoimmune diseases

Immune recognition of supposedly heathy tissue is responsible for the development of autoimmune diseases such as rheumatoid arthritis (RA) and multiple sclerosis (MS). Understanding the molecular patterns responsible for this immune attack will foster our possibilities to treat or circumvent disease. Our current ability to map T-cell reactivity to certain molecular patterns is poorly matching the huge diversity of T-cell recognition in humans. Our immune system holds approximately 107 different T-cell populations patrolling our body to fight intruding pathogens. We will 1) use our novel barcode labelled MHC multimers to describe T-cell recognition in limited biological samples from patients, 2) use of this new technology to retrieve excess information about T-cell receptor (TCR) sequences coupled with their molecular recognition pattern, and 3) the development of an in-silico predictor of binding between T-cell receptors and their specific molecular pattern.
Link til video on Youtube

Automatic gating strategies for flow cytometry

I am actively pursuing to enhance the quality of flow cytometry based analyses (Hadrup et al. CytometryA, 2014), implementing the use of automated gating algorithms in data analyses (manuscript in prep, and Kvistborg et. al. Immunity, 2015). I am Steering committee chair 2015 and onwards, The European association for cancer immunotherapy (CIMT) immunoguiding program (CIP), that actively works to improve quality and reproducibility in T-cell assays and implement new technologies among European research groups.




Sine Reker Hadrup
Head of Sections, Professor
DTU Health Tech
+45 35 88 62 90
25 APRIL 2019