IT-PREDICT · Predicting immunotherapy response in melanoma and non-small cell lung cancer patients using an extracellular vesicle-derived miRNA signature and a non-invasive CRISPR-based detection assay.

Immunotherapy (IT) has revolutionized the treatment of metastatic lung cancer and melanoma by enhancing the immune system's ability to recognize and attack cancer cells. However, only about 50% of patients respond positively to IT and current methods assessing patient eligibility for IT primarily rely on invasive tumor biopsies and have proven inefficient. With 420,000 new melanoma and lung cancer cases diagnosed annually in the EU, this results in wasted costs, time and resources in healthcare systems. We propose to develop a non-invasive, rapid and cost-effective test to predict patients’ response to IT.Liquid biopsy offers a promising non-invasive alternative for analyzing blood to detect components secreted by cancer cells. Extracellular vesicles (EVs) have particularly gained attention as they are abundant and their content, including miRNAs, reflect the state of the cells that secrete them. EV miRNAs could therefore be used as biomarkers to predict IT response but we lack a consensus miRNA signature (mi-S) and scalable detection methods suitable for clinical use.The IT-PREDICT project will identify a mi-S predictive of IT response in lung cancer and melanoma patients. We will leverage one of the largest cohorts of melanoma and lung cancer patients with EV-derived miRNA profiles and use machine learning to define mi-S. We will then further develop a novel CRISPR-based one-pot and multiplex assay to enable cost-effective and scalable detection of the mi-S. This project will be the foundation for prospective clinical trials, with potential applications to other cancers. We also aim to develop the mi-S and its detection method into a commercially available kit.The project's feasibility is supported by my expertise in CRISPR and molecular biology, my supervisor’s specialization in EV research, the host institute's recognition as an anti-cancer center of excellence in IT, and its interdisciplinary collaboration with the Computer Science Laboratory of Burgundy.