Descripción del proyecto
Despite significant medical advancements, cancer remains a major cause of mortality worldwide, and several cancer types still lack efficient therapy, in part due to resistance to traditional immunotherapy (IT). Endothelial cells (ECs) present an important yet overlooked modulator of tumor immunity, possessing an immunosuppressive nature, and proposed to contribute to IT resistance. Studies of the host lab indeed identified immunomodulatory features in EC subsets (coined IMECs). My central hypothesis is that targeting immunosuppressive (IMMUSUP) genes in tumor ECs may promote anti-tumor immune reaction to overcome resistance and improve the efficacy of traditional IT. The aim of this work is to identify novel, IMMUSUP genes expressed by tumor ECs and assess the potential of targeting these genes in vivo to promote anti-tumor immune response. I will explore in particular mystery genes (with poor functional annotation, ca 1/3 of the mammalian coding genome and an unexplored resource of potential targets) to maximize the identification of novel IMMUSUP genes beyond the currently used targets in traditional IT. Thus, I will (i) identify and prioritize EC IMMUSUP genes using artificial intelligence/machine learning approaches and (ii) in silico bioinformatics coupled to a mystery-genome wide siRNA screen to reveal IMMUSUP activity; (iii) confirm IMMUSUP targets via lipid nanoparticle-based siRNA delivery to generate EC-specific knockdown mice in models of lung, esophageal, and liver cancer; and (iv) determine the Mode of Action of the most promising targets using multidisciplinary approaches. My work will yield insights about previously unknown drug targets in tumor ECs, potentially paving the way for development of alternative IT with enhanced efficacy. My prior experience in immunology and bioinformatics combined with the host lab's expertise in EC (dys)function and single cell -'omics' technologies will ensure high quality execution of this project.