Functional Characterization and Modeling of Acquired Resistance to Immune Modulation in Lung Cancer
Abstract
Immune checkpoint inhibitors (ICIs) that interfere with signals like PD-1, PD-L1 and CTLA4 that negatively regulate the activityof T-cells are now standard-of-care for the treatment of lung cancer. Response rates to these immune checkpoint inhibitors aremodest (objective response rates are ~15-20% in unselected patients) but the durability of the responses is remarkable.Despite such prolonged responses, most of these patients with lung cancer are not cured and develop acquired resistance tothe agents. At present, we lack a comprehensive understanding of the cellular and molecular mechanisms that underlieacquired resistance to immune checkpoint inhibitors. The overarching goal of this grant is to fill this knowledge gap and toidentify and overcome acquired resistance to immune modulation in lung cancer by: 1) Establishing the genomic landscape oflung cancers with acquired resistance to ICIs and 2) Functionally characterizing mechanisms of acquired resistance to ICIs.Here we describe our progress towards achieving these goals including the analysis of resistant tumors, validation ofresistance mechanisms and generation of new models to study resistance to immune checkpoint inhibitors. We also describenew therapeutic approaches that we are testing to overcome such resistance.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2018
- Accession Number
- AD1071923
Entities
People
- Katerina Politi
Organizations
- Yale University