Project 1
Moffitt Cancer Center
∆ Immune Ecology: Project 1
Project Overview
Non-small cell lung cancer (NSCLC) is the most common and among the most lethal of human cancers, with about 2 million new cases per year and a 5-year survival for metastatic disease of less than 5%. The Moffitt Thoracic Oncology Department has pioneered immunotherapy strategies for NSCLC, achieving response rates of 30-45%, though most responses are followed by resistance. We have quantified the immune ecology from pre-treatment biopsies to generate predictors of response, and our preliminary analysis indicates that unique ecological interactions predetermine response. This project focuses on quantifying and utilizing how the immune ecology of these cancers changes (∆-Ecology) during treatment, particularly with the exciting development of KRAS-G12C inhibitors (G12Ci) such as AMG-510 (sotorasib), which have demonstrated clinical efficacy and may enhance antitumor T-cell responses. Our studies have shown that G12Ci enhanced tumor infiltrating lymphocyte levels in preclinical models, suggesting synergistic potential with checkpoint inhibitors and adoptive T-cell therapy. Utilizing tumor specimens from ongoing clinical studies and preclinical models, the overarching goal of this project is to define and predict the impact of KRAS and immune checkpoint inhibitors on NSCLC ∆-Ecology. Mathematical modeling of the dynamics of tumor ecology under treatment will be key to understanding these mechanisms, and we will also investigate other targeted agents that affect tumor-immune interactions for targeting resistance to RAS pathway inhibition.
Hypothesis
The ∆-Ecology of mutant NSCLC tumors under treatment (comparing pre- and early on-treatment) is an early predictor of patient response, we can exploit this predictor to drive novel multi-agent combination therapies through an integrated approach utilizing clinical data, in vivo studies, and mathematical modeling.
Aim 1: Quantify ∆-Ecology in Patient Samples
We will quantify the ∆-Ecology of patient samples pre- and on-immunotherapy treatment using data from a randomized Phase I/II trial (NCT02638090) in which anti-PD-1 naïve NSCLC patients are treated with pembrolizumab monotherapy (n=39). We will obtain clinical samples, stain for key immune and stromal markers, and analyze samples using Ecological Analysis Core tools to identify ecological signatures correlated with response. We will define ecological signature hotspots and investigate the dynamics of ∆-Ecology in KRAS mutant tumors undergoing immunotherapy using mathematical modeling calibrated from patient data.
Aim 2: Impact of KRAS Inhibitor Therapy with Immunotherapy
We will characterize the impact of KRAS inhibitor therapy on NSCLC ∆-Ecology using both human samples and murine KRAS-G12C tumor models. Focusing on G12C mutants, we will perform murine experiments to explore changes in tumor ecology with G12Ci therapy, both as monotherapy and in combination with anti-PD-1 immunotherapy. We will investigate changes in ecology of NSCLC tumors before treatment and after acquired resistance to sotorasib, obtained through our Rapid Tissue Donation program. We will develop and calibrate a mathematical model to explore treatment regimens that optimize synergy between the two therapies, and test model predictions in the murine system.
Aim 3: Evolutionary Therapy Strategies with Multiple Agents
Inhibition of the RAS pathway leads to adaptive resistance driven by RAS pathway reactivation. To design strategies that prevent or delay resistance while retaining synergy with immunotherapies, we will investigate combining G12Ci with two promising clinical-stage agents that work through distinct mechanisms. We will develop and calibrate a mathematical model of multi-agent combination therapy from murine experiments, and use a Phase i trials approach to derive evolutionary therapy strategies for multi-agent combinations.
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