IA14 Preclinical and Translational Approaches to Capturing Mechanisms of Immunotherapy Response and Resistance in NSCLC

Abstract

Strategies incorporating immune checkpoint inhibition have achieved unprecedented successes and been rapidly incorporated into standard-of-care regimens for patients with locally advanced or metastatic non-small cell lung cancer. Unfortunately, high rates of primary or acquired therapeutic resistance limit their broader efficacy for patients or durability. Using preclinical models, we have studied response and resistance to both single-agent and combination checkpoint blockade strategies. Consistently we have observed that the initial therapeutic response is accompanied by an overall reprogramming of the cellular immune microenvironment, followed by the development of resistance. Upregulation of molecules such as CD38 on tumor cells and cells of the myeloid compartment orchestrate changes in the metabolic environment as well as the cellular landscape, each of which define important and targetable components of resistance. We have similarly built patient cohorts and interventional trials for patients who are treated with surgical resection to leverage the neoadjuvant treatment space for tissue-based examination of response and resistance. This approach allows us to monitor for clinical response or resistance to treatment, while obtaining appropriate tissues for deep, multiplatform profiling of the tumor, normal tissues, and circulating factors. These efforts include the ICON Project (ImmogenomiC PrOfiling of Non-small cell lung cancer), which has profiled 150 patient tumors without neoadjuvant treatment or with neoadjuvant chemotherapy only and longitudinally followed patients for outcomes. Additionally, in the phase II NEOSTAR trial patients received neoadjuvant nivolumab (n=23) or nivolumab plus ipilimumab (n=21) before undergoing surgical resection, with tumors from both of the arms undergoing multiplatform profiling. These individual efforts and comparison of the tumor data between them allow us to understand the baseline immunogenomic profiles and heterogeneity of NSCLC, as well as the effects of standard chemotherapy or immunotherapy. Using these datasets, we can define subsets of patients likely to respond to therapy, while identifying types of responses, biomarkers, and potential mechanisms that define resistance that can be targeted by combination or sequential therapies.