Abstract
Abstract Meningiomas are mostly benign CNS tumors however, a subset of these tumors may become atypical or malignant. The standard of care to monitor patients after diagnosis requires serial MRI assessments, which have limited value in distinguishing malignant tumors from benign disease. Therefore the discovery of non-invasive methodologies that reflect meningioma tumor burden and its dynamic evolution in real-time is highly desirable. Liquid biopsy (LB) could be used to fine-tune surveillance and treatment with minimal risk to patients. Evidence of circulating tumor cells and cell-free (cf) tumor DNA in the blood has been shown in several tumor types however, limited progress has been made for brain tumors with known biomarkers; possibly due to the unlikelihood of capturing point mutations in circulating DNA fragments. On the other hand, DNA methylation signatures are maintained even in small DNA fragments, which suggests that DNA methylation is an attractive biomarker to be studied in liquid biopsy of brain cancers. In order to identify DNA methylation-based biomarkers using archival serum and tissue specimens, we generated and analyzed the epigenome (Illumina Human EPIC array) of patients with meningioma (including primary (n=6); recurrent (n=8)) and non-meningioma (including non-tumor patients (n=5), pituitary tumor (n=13), colorectal cancer (n=2) and other CNS diseases (n=6), such as inflammatory tissue and radiation necrosis). cfDNA fragment size distribution revealed peaks with 150~200bp on average. By randomly selecting 70% of our cohort as a discovery set, we identified 500 CpGs (FDR<0.05) differentially methylated between meningiomas and non-meningiomas, which show a DNA methylation profile similar to the matched meningioma tissue. Then, we trained a random-forest machine learning using the same signature and applied the model to the remaining 30% samples (validation set) from our cohort. The model was able to correctly classify samples into meningioma and non-meningiomas with a sensitivity of 100% and specificity of 100%. From this pilot data, we were able to investigate the LB methylome of meningioma patients and identify potential markers to detect tumor cells in the serum of these patients, which could eventually allow clinicians to monitor impending disease progression and recurrence. Citation Format: Thais S. Sabedot, Tathiane M. Malta, Ruicong She, James Snyder, Tobias Walbert, Ian Lee, Steven Kalkanis, James Ewing, AnaValeria Castro, Houtan Noushmehr. Methylation-based liquid biopsy of meningioma primary and recurrent samples [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 781.
Published Version
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