OTHR-09. IDENTIFYING EPIGENETIC SIGNATURES IN LUNG ADENOCARCINOMAS THAT PREDICT DEVELOPMENT OF BRAIN METASTASIS

INTRODUCTION: Metastases are the most common adult brain tumor with half spreading from lung cancers and they reduce median overall survival from 26 to 12 months. There are no robust patient-specific predictors of brain metastasis. Epigenetic signatures predict disease recurrence in other cancers and identifying brain metastasis methylation-based signatures may allow for treatment approaches to high-risk patients that prevent their development. METHODS: In 207 lung adenocarcinomas, multivariate cox time to brain metastasis analyses including clinically-relevant variables (lung tumor size and TNM nodal score) along with significant covariates on univariate analyses were performed. DNA was extracted from 142 of these tumors and profiled on the Illumina Infinium EPIC array. A generalized boosted regression classification model used differentially methylated CpG sites significantly predicting time to brain metastasis in a 70% training cohort cox analysis (p< 0.05). Resulting methylation-based risk scores were compared to size and nodal status in a multivariate analysis of the independent 30% testing cohort. RESULTS: Of 207 patients with 72 brain metastatic events, tumor size (HR=1.5, 95%CI 1.1–2.0, p=0.01), N status (N3 vs. N0, HR=9.9, 95%CI 3.1–31, p=0.0001), EGFR status (HR=0.4, 95%CI 0.2–0.8, p=0.014), and age (HR=0.7, 95%CI 0.5–1.0, p=0.039) independently predicted their development. Methylation-based risk scores significantly predicted time to brain metastasis in a univariate analysis of the testing cohort (p=0.03). A multivariate analysis of testing cohort patients identified methylation score as the only independent predictor of brain metastasis (HR=4.3, 95%CI 1.1–17, p=0.038) accounting for tumor size and N score. CONCLUSIONS: Genome-wide DNA methylation signatures predict brain metastasis development in lung adenocarcinomas independent of tumor size and nodal disease. The design of a nomogram combining methylation profile other clinical factors may be used to determine patient specific brain metastasis risk values to guide patient counselling, extent of treatment, and screening.