CICCI studied intestinal cancer cell invasion, GDCOLCA investigated gamma delta T cells in colon cancer metastasis, and TCAPS explored mRNA regulation in CD8 T cells.
BEATSON INSTITUTE FOR CANCER RESEARCH LBG
Glasgow-based cancer research institute specialising in tumour biology, T cell immunology, protein regulation, and computational oncology.
Their core work
The Beatson Institute is a dedicated cancer research centre based in Glasgow, Scotland, focused on understanding the molecular mechanisms of cancer biology. Their work spans from structural biology of protein regulation (ubiquitination, E3 ligases) to immunology of tumour microenvironments, particularly T cell biology in colorectal cancer. They combine wet-lab cancer biology with computational and bioinformatics approaches, and actively train the next generation of researchers through fellowship programmes in translational medicine and personalised oncology.
What they specialise in
RINGE3, their largest grant (EUR 2M ERC Consolidator), focused on RING E3-mediated ubiquitination mechanisms.
TCAPS examined mRNA cap regulation in CD8 T cells and GDCOLCA studied gamma delta T cells in colon cancer.
INFERNET applied mathematical modelling to multi-scale molecular networks, while TOPMed10 trained fellows in computational modelling and molecular bioinformatics.
TOPMed10 fellowship programme focused on omics-driven personalised medicine with training in clinical informatics and biostatistics.
How they've shifted over time
Early H2020 work (2015-2017) centred on structural cancer biology — protein ubiquitination mechanics, intestinal cancer invasion, and training in translational omics and personalised medicine. From 2017 onward, the focus shifted decisively toward cancer immunology (T cell biology, mRNA regulation) and computational approaches (mathematical modelling of molecular networks, statistical inference). This reflects a broader trend in cancer research: moving from understanding tumour mechanics toward immune-based interventions and data-driven discovery.
Beatson is converging on the intersection of T cell immunology and computational modelling — positioning them for immune-oncology and data-driven drug target discovery collaborations.
How they like to work
Beatson strongly prefers to lead: 4 of 6 projects were coordinated by them, indicating confidence in project management and a preference for setting the research agenda. Their consortia are modest in size (12 unique partners across 9 countries), suggesting focused collaborations with selected experts rather than large-scale multi-partner programmes. They are accessible as partners too, having joined INFERNET as a third party and TOPMed10 as a partner, showing willingness to contribute specialist expertise to others' initiatives.
Beatson has collaborated with 12 distinct partners across 9 countries, indicating a well-distributed European network for a mid-sized research institute. Their partnerships span multiple countries rather than clustering in one region, reflecting the international nature of their MSCA and ERC projects.
What sets them apart
Beatson combines deep cancer biology expertise with growing computational and immunological capabilities — a rare triple competence in a single institute. Their strong track record as project coordinators (4 out of 6 projects) and success in securing competitive ERC and MSCA funding makes them a credible lead partner for cancer-related consortia. For anyone building a project around tumour immunology, protein regulation, or computational oncology, Beatson brings both scientific depth and proven project leadership.
Highlights from their portfolio
- RINGE3Largest project (EUR 2M ERC Consolidator Grant) investigating fundamental protein ubiquitination mechanisms — signals strong individual research excellence.
- TCAPSEUR 1M grant on mRNA cap regulation in CD8 T cells represents Beatson's pivot toward cancer immunology, a high-growth research area.
- INFERNETParticipation as third party in a computational biology network project signals Beatson's expanding capability in mathematical modelling and bioinformatics.