Charles Darwin proposed more than 100 years ago that species evolved by means of natural selection. But selective forces not only act on organisms, they also govern the evolution of the cells in our body. One of these forces is the immune system that, besides protecting us from viruses and bacteria, recognises our own faulty somatic cells and ultimately shapes the emergence of cancer in a process called immunoediting. However, to what extent the genome of our cells undergoes immunoediting, and what are the determinants that predispose us to develop cancer and metastasis remain poorly understood.
Over the last decade, next-generation sequencing (NGS) technologies have allowed us to explore the landscape of the genetic causes of cancer. However, no consistent drivers of metastasis have been identified so far and cancer is still a disease of concern. In parallel, the immune system has gained relevance in the clinical management of cancer thanks to the incredible results obtained in patients treated with immune checkpoint inhibitors (ICIs). ICIs unmask the patient own's immune system to act against malignant cells leading to complete or partial regressions in a substantial number of patients. Nonetheless, many patients fail to respond to the treatment and, to date, we lack scientific knowledge to understand the mechanisms of this resistance. In my Marie-Curie project, I proposed a simple mechanism of evolutionary adaptation driven by the immune-mediated negative selection against growing tumors harbouring immunogenic mutations. This process is intrinsically linked to the primary resistance to treatment in metastatic tumors. Tumors that have been subjected to the selective pressures of a healthy immune system can either be immune-adapted, by depleting all immunogenic mutations, or immune-escaped, by acquiring mechanisms of immune evasion. Therefore, understanding the interaction between the immune system and cancer progression could help us to differentiate between individuals which are sensitive or resistant to immunotherapies, ultimately reducing the overall burden of the current standard of care in the standard setting of clinical practice.
I developed a mathematical model to theoretically demonstrate the process of immunoediting during tumor growth, and implemented a computational method to determine the levels of immune selection acting in primary and metastatic tumors. I demonstrated how an evolutionary metric could differentiate between patients that are going to benefit from immunotherapeutic agents based on the personalized genomic data.
