Immunoinformatics is the branch of bioinformatics that studies the immune system. As a field, it’s gaining traction thanks to the rise of immunotherapies and the steadily increasing wealth of immunological data. In the context of cancer, immune cells are able to recognize tumors and fight them all across the body. Hence, the interest in reinvigorating the immune system via cancer immunotherapies. However, the response rate remains at 20-40%, which is remarkable in late-stage cancers (main patient group targeted) but still low. The only response biomarker for cancer immunotherapies is a high number of mutations or Tumor Mutational Burden High (TMB-H). During my placement at Tumour Immunogenomics and Immunesurveilance group (UCL Cancer Institute), we to refine using our immunoinformatic models (NetCleave, NOAH and PredIG) and a large patient dataset (UCLCPI3000+) In addition, UCL Cancer Institute is devoted to early cancer detection and immunotherapy sensitization fields to improve response rates to cancer treatment. In this line, I have contributed to cancer detection with antibody predictions (Brewpitopes) and to immunotherapy sensitization with transcriptomic and proteomics analyses.
Roc Farriol (Thu,) studied this question.