Early lung cancer
Oncogenic activation of ERK in alveolar epithelium initiates the cells’ transformation into lung adenocarcinoma (LUAD), the most common type of lung cancer. The early tumors can lie dormant for decades. Once awakened, if the cancer is caught early as stage I or II disease, patients have a better prognosis. We have identified how some LUAD’s circumvent ERK pathway negative feedback loops to increase ERK activity to levels that promote progression. We found that loss of the transcription factor NKX2-1 removes its induction of the ERK phosphatase DUSP6. This signal allows for increased ERK activity in vivo and promotes lung cancer cell line invasion and lung cancer progression in genetically-engineered mouse models and tumor xenografts.
- Ingram, et al. Oncogene (2022).
RAS/ERK and microenvironment crosstalk for invasion
Invasion is present in the earliest detectable stages of LUAD and promotes tumor progression to metastasis. Invading cancer cells must overcome the structural restraints of tissue organization to move through the stroma and into the vasculature. The cells crawl along, degrade, and squeeze between the extracellular matrix (ECM) fibrils. The fibers, in turn, signal to the tumor cells to promote invasion.
Current projects: extracellular matrix signaling for ERK and LUAD invasion
Cancer-associated fibroblasts in the tumor microenvironment express new extracellular matrix proteins, such as Tenascin-C in lung cancer. Tenascin-C promotes LUAD metastasis in mice and portends poor prognosis in patients. We are interrogating the signal that induces Tenascin-C expression in early LUAD and how the tumor cells sense and navigate the modified extracellular matrix environment. We are also probing how the altered stiffness and composition of tumor microenvironments promote tumor cell ERK signaling and ERK signaling for invasion. This project is funded by R01CA255790.
Collaborations
The Mendoza lab has a funded collaborations with the Weiss lab in the Biomedical Engineering department. The collaboration applies computational modeling to understand the mechanics of tumor growth within the lung.