Integrative data analysis to uncover genes and pathways underlying the aggressiveness and invasion patterns of lung cancer brain metastasis
Abstract
This study aims to understand the molecular processes influencing metastasis speed and invasion patterns in lung cancer brain metastasis. We used the spatial gene expression profiles and histology images from lung and brain tissues of 35 patients. Applying data integration methods, statistical tests, and gene set enrichment revealed three major categories of pathways: immunity, stemness, and metabolism pathways. To investigate invasion patterns, we developed a scoring system to assess tumor growth patterns and labeled the patients accordingly. Matrix factorization and statistical tests were used for relevant gene set discovery. We also examined the interaction between the tumor microenvironment and brain tumors. Our integrative analyses revealed the possible linked factors to be immune response, mitochondrial dysfunction, histone modification, and cellular processes. Overall, the study provides insights into the molecular processes underlying lung cancer brain metastasis and may contribute to the development of strategies to prevent or manage lung cancer brain metastasis.