Unlocking the TCR repertoire for personalized cancer immunotherapies.

Cancer is one of the leading causes of death worldwide. Over the past decades, new therapies have been developed that target the patients' immune system to mount an antitumor response. The efficacy of these immunotherapies has already been demonstrated in various clinical trials. Nevertheless, these therapies show a large variation in their individual responses as some patients respond well to the therapy, while others do not. In this project, we will investigate the differences between the T cell receptor (TCR) repertoires of responders and non-responders as a possible marker for immunotherapy responsiveness. We will apply state-of-the-art data mining methods and newly developed immunoinformatics tools to uncover those features that make a patient a clinical responder or non-responder. This will reveal the underlying mechanism of DC-based vaccine responsiveness. This can potentially accelerate general health care in terms of personalized medicine and will save costs.

Keywords:CANCER, IMMUNOTHERAPY

Disciplines:Bio-informatics, Adaptive immunology