Integrative analysis of lung multiparametric flow cytometry data to study immune cell dynamics in tumors.

Abstract

Lung cancer remains a leading cause of cancer-related deaths, highlighting the importance of understanding the lung's immune landscape, which plays a key role in tumor progression and response to therapy. As an organ constantly exposed to environmental and microbial challenges, the lung's unique tumor microenvironment is shaped by these additional stimuli, influencing immune responses. Here, we present a standardized protocol to examine dynamic changes in the lung immune cell compartment in response to bacterial challenges in a genetically engineered mouse model of lung cancer. This method ensures efficient tissue processing and dissociation while preserving cell viability for high-throughput flow cytometry. Additionally, we describe an integrative analysis approach to systematically analyze data across tissues and conditions, providing a comprehensive framework for studying immune cell dynamics in lung carcinoma.