Implementation of Complex in Vitro 3D Lung Cancer Model to Monitor Resistance to Immune Checkpoint Inhibitors Through Deep Profiling at Single-cell and Spatial Resolution
Abstract Text: Lung cancer is the leading cause of cancer related deaths worldwide with non-small cell lung cancer (NSCLC) being the most common type (80-85%). Immune Checkpoint Inhibitors (ICIs) has revolutionized the treatment of NSCLC. Nevertheless, some patients show resistance to treatment and knowledge on resistance mechanisms remains limited. The tumor microenvironment (TME) plays a pivotal role in response to immunotherapies. Yet, access to tumors after the first lines of treatment is challenging. To overcome this limitation, we propose to characterize TME influence on ICI resistance developing a complex human NSCLC derived 3D co-culture model including tumor cells, endothelial cells, fibroblasts, T cells and monocytes. We aim to profile the 3D model at baseline and monitor the influence of TME on response to standard treatment (chemotherapy + ICI treatment) through an exhaustive molecular spatial and phenotypic evaluation of the whole immune context. Preliminary data from flow cytometry, confocal imaging and spatial transcriptomics confirmed the presence of all different cell types at D5, with a prevalence for tumor cells. Moreover, at D14 we observed treatment effect in tumor cell killing with low residual immune cells. We are now collecting longitudinal data from D5 to D14 using single cell transcriptomics to better monitor interactions between treatment and TME. Those data are also used to optimize culture conditions to obtain an even more relevant TME model, including hot and cold like TME, to enable the identification of novel targets and biomarkers to overcome ICI resistance and improve patient stratification.
