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Abstract Background: Cerebrospinal fluid (CSF) is an increasingly important liquid biopsy for brain tumors, offering improved sensitivity over plasma due to proximity to the tumor and reduced peripheral DNA background. However, cfDNA concentrations in CSF are low, and extraction inefficiencies can limit the reliability of downstream molecular assays. This study evaluates cfDNA recovery performance from CSF-like matrices to support sensitive molecular profiling relevant to brain cancer applications. Methods: Synthetic CSF samples spiked with fragmented cfDNA reference material were processed using the nRichDX Revolution Max20 workflow. Low-input volumes representative of clinical CSF collections were evaluated. cfDNA yield and recovery were quantified using fluorometric and quantitative PCR-based measurements, and fragment size distributions were assessed to confirm recovery of short cfDNA fragments typical of CSF-derived material. Results: The extraction workflow consistently recovered cfDNA from synthetic CSF with high reproducibility across replicates and input volumes. Quantitative measurements demonstrated reliable cfDNA yields suitable for sensitive downstream molecular analyses. Fragment size analysis confirmed preservation of short cfDNA fragments, including those within the range relevant for mutation detection and copy number analysis. Minimal variability was observed between runs, indicating robustness of the extraction process under low-input conditions. Conclusions: Efficient and reproducible cfDNA extraction from CSF-like matrices enables molecular profiling approaches that are critical for brain cancer research and clinical translation. The performance demonstrated in this study supports clinical applications including detection of tumor-derived genetic alterations, longitudinal disease monitoring, and assessment of treatment response in central nervous system malignancies. Reliable cfDNA recovery from limited CSF volumes is a key enabling step for integrating CSF-based liquid biopsy into precision oncology workflows for brain cancer. Generative AI Disclosure: Generative AI was used solely to assist with editing and improving the clarity of this abstract; all scientific content and conclusions were reviewed and validated by the authors prior to submission. Citation Format: Nafiseh Jafari, Jason Saenz, Carlos Hernandez, Daniel Cedeno, Cameron Van Dieren, Mayer Saidian. Efficient recovery of cell-free DNA from synthetic cerebrospinal fluid enables sensitive molecular profiling in brain cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr A052.
Published in: Cancer Research
Volume 86, Issue 6_Supplement, pp. A052-A052