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BACKGROUND One quarter of lung adenocarcinoma (LUAD) patients develop brain metastases (BM) and experience a poorer median survival of 12 months despite treatment. Clinical variables do not robustly predict who will develop BM and targeted preventative treatments are limited. Tumour DNA methylation signatures predict outcomes in other cancers and can be detected in circulating tumour DNA (ctDNA). This work predicts BM development from LUAD using methylation data, identifies novel potential treatment targets to prevent metastases, and detects LUAD-BM ctDNA non-invasively. METHODS DNA methylation profiling was undertaken on N=124 LUAD tumours. A gradient boosted regression model built on differentially methylated CpGs (DMCs) between tumours with and without BM in 70% of samples was validated in an independent 30% testing cohort. Nine paired BM samples were profiled and DMCs between their corresponding LUAD tissue were identified along with copy number (CN) alterations. A total of 47 LUAD-BM plasma samples underwent sequencing of immunoprecipitated methylated ctDNA and differentially methylated regions (DMRs) between LUAD-BM and intrinsic brain lesions were identified. RESULTS The methylation-based model significantly predicted time to brain metastasis development within the testing cohort independently from cancer stage in a multivariate analysis (HR=4.3, 95%CI 1.1–17, p=0.038). Genes/pathways involved in the process of brain metastasis were identified through assessment of 83K DMCs (FDR&amp;lt; 0.2, mean difference &amp;gt;|0.1|) between paired samples as well as the CN losses found in chromosome 12q/19 of BM samples. A total of 5.5K DMRs were identified that distinguish BM samples from gliomas or primary CNS lymphomas (FDR&amp;lt; 0.05, logFC &amp;gt;1). CONCLUSIONS DNA methylation signatures in lung adenocarcinomas predict brain metastasis development independently from prognostic clinical factors. Genes and pathways involved in metastasis were identified as novel potential therapeutic targets. Methylated circulating tumor DNA signatures differentiate lung brain metastases from other ring-enhancing brain lesions and may have potential for non-invasive diagnosis.

neuro-oncology

EPCO-01. LUNG ADENOCARCINOMA BRAIN METASTASIS PREDICTION, PREVENTION, AND NON-INVASIVE DIAGNOSIS USING METHYLATION SIGNATURES WITHIN TISSUE AND CIRCULATING TUMOUR DNA