Immunotherapeutic targeting of intracellular or secreted tumor-specific proteins remains a major challenge. To overcome these limitations, we are leveraging AI-based protein design to generate peptide-MHC class I-specific minibinders that mimic T-cell receptor (TCR) recognition. Our designed minibinders target a small-cell lung cancer (SCLC)-associated peptide identified by immunopeptidomics.

For this project, we have collaborated with the Immune Monitoring Group at the University of Tübingen to leverage their immunopeptidomics expertise to identify an HLA-A*02 restricted peptide derived from IGFBPL-1 (Insulin-Like Growth Factor Binding Protein 1), found to be frequently expressed on SCLC. We have utilized tools such as RFdiffusion (a generative AI algorithm) for the generation of specific designs against the IGFBPL1 peptide in combination with a novel refinement algorithm. To assess the immunotherapeutic potential of screened IGFBPL-1 binding candidates, TCR-mimetic binders are incorporated as binding modules into chimeric antigen receptor (CAR) T cell constructs.

The aim of my project is to assesses the functional specificity of our IGFBPL-1 pMHC CAR, against endogenous levels of IGFBPL1 in SCLC both in vitro and in vivo. We are also in the unique position of being able to assesses aspects of this functional specify in comparison against conventionally derived IGFBPL-1 specific TCR, generated by our collaborators.

Overall, the goal of this project is to advance the design of peptic centric CAR-T cells and the development of therapeutics for small cell lung cancer.