OVERALL PROJECT SUMMARY
IDENTIFYING METABOLIC VULNERABILITIES IN LUNG CANCER
Lung Cancer is the most common cause of cancer deaths world-wide. Tyrosine kinase inhibitors and
immunotherapy have been shown to be effective in a subset of patients; however, the overall survival rate for
this disease remains low especially for metastatic disease. Moreover, small cell lung cancer (SCLC) patients
have a poor prognosis, and there especially exists a gap in knowledge in understanding SCLC and identifying
effective therapeutic strategies. Our goal in this proposal is to understand the underlying biology of key drivers
in lung cancer by identifying metabolic vulnerabilities that can ultimately be used as single agents or combined
with immunotherapy to target lung cancer therapeutically. We will achieve this goal by engaging experts that
have developed preclinical models with common molecular signatures in non-small cell (NSCLC) and small cell
lung cancer (SCLC) and cutting-edge metabolomics. We have an active and collaborative group that meets twice
monthly with projects and manuscripts that are co-authored by the leaders of each project and core. Additionally,
our Program Project Grant (PPG) team is located at Moffitt Cancer Center, which is an ideal place to study the
pathogenesis of lung cancer. Florida is number 2 in the country in terms of newly diagnosed lung cancer patients.
Moffitt treats 10% of these cases. The PPG consists of four projects and four cores. These projects and cores
collaborate and synergize to meet four objectives: i. To identify metabolic vulnerabilities in lung cancers through
integrative analysis of in vivo and ex vivo models with common molecular signatures, including p53,
NRF2/KEAP1, and MYC (Project #1, led by Dr. Flores, Project #2, led by Dr. DeNicola, Project #3, led by Drs.
Cleveland and Haura, and Project #4, led by Dr. Rodriguez with support from the Administrative Core #1, led
by Drs. Flores and Haura, Preclinical Models and Pathology Core #2, led by Drs. Cress and Karreth, Metabolism
Core #3, led by Dr. Koomen, and Data Science Core #4, led by Dr. Fridley), ii. To identify metabolic
vulnerabilities that synergize with immunotherapy through examining the tumor microenvironment and gaining a
deep molecular understanding of myeloid derived suppressor cells (MDSCs). (Project #4 in collaboration with
Projects #1 and #2 and Core #2), iii. To build mouse models as a platform to understand the metabolic pathways
utilized by lung cancers with different genetic signatures and to assess therapeutic strategies for lung cancer.
(Core #2 supporting Projects #1-4), and iv. To share resources and data locally and globally to obtain an
integrated molecular understanding of metabolic vulnerabilities in lung cancer. (Core #4 leading efforts from All
Projects and Cores).