Lung cancer is the leading cause of cancer related deaths in the United States and is responsible for approximately 160,000 deaths per year. In the last decade substantial progress has been made in identifying and targeting genetic drivers of this disease, but unfortunately sustained responses to agents that target these drivers have not been achievable due to the development of acquired resistance. Immunotherapy, specifically inhibition of immune checkpoints (e.g. PD-1 and CTLA-4), has emerged as a promising option to overcome these obstacles and has been shown to lead to durable responses in a broad range of lung cancer subtypes. Unfortunately, less than 20% of tumors are responsive to immune checkpoint inhibition and those that do respond frequently acquire resistance to these agents. Currently, the mechanisms dictating response and resistance to immune checkpoint inhibitors remain poorly understood and the lack of clinical specimens and representative mouse models have stunted mechanistic understanding and progress in this field. A systematic investigation of immune checkpoint inhibitors in vivo is needed to illuminate genetic and immune signatures that confer response and resistance to these agents. To address this, I propose the following aims.
In Aim 1, I will establish the functional relationship between the genomic landscape and response to immune checkpoint inhibitors in lung adenocarcinomas in vivo. This will be accomplished through the generation of a carcinogen- induced murine lung tumor model that recapitulates the variable mutation burdens seen in patients? tumors. Tumor-bearing mice will be treated with immune checkpoint inhibitors to evaluate drug response in the context of variable mutation burden.
In Aim 2, I will identify and validate mechanisms of acquired resistance to immune checkpoint inhibitors. To accomplish this, I will examine sequencing data of tumor biopsies from patients who have developed acquired resistance to checkpoint inhibitors clinically as well as from tumors derived from mouse models of acquired resistance to immune checkpoint blockade that I will develop. Combined, this proposal will establish the relationship between mutation burden and response to immune checkpoint inhibitors as well as lead to the development of novel mouse models for cancer immunotherapy research. These studies will provide insight into the mechanisms of action of checkpoint inhibitors and ultimately improve outcomes for lung cancer patients.

Public Health Relevance

Despite substantial progress over the past decade in developing molecularly targeted therapeutics for genetic subtypes of lung cancer, challenges with primary and acquired resistance to these drugs demand the development of new treatment options for these refractory populations. Therapies that harness the immune system have shown incredible promise in eliciting enhanced survival benefits and durable responses in a fraction of lung cancer patients. Our efforts to create better pre-clinical models of lung cancer to test immunotherapies will enhance our understanding of what drives response and resistance to these immune modulatory agents thereby enabling us to develop better strategies to treat this disease.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
1F32CA210516-01A1
Application #
9327320
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Jakowlew, Sonia B
Project Start
2017-04-01
Project End
2020-03-31
Budget Start
2017-04-01
Budget End
2018-03-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Yale University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520