Abstract BACKGROUND Diffuse midline gliomas (DMG) are aggressive and universally fatal with a median survival rate of only 9-12 months. MRIs can be difficult to interpret due to diffuse disease and radiation-induced swelling. Recent work has shown that liquid biopsy of cell-free tumor DNA (cf-tDNA) in patient plasma using digital droplet PCR (ddPCR) might help supplement radiographic monitoring, and enable more quantitative, low-cost, rapid tests. Nanopore sequencing has been employed to quickly and affordably measure and track treatment response in DMG patient cerebrospinal fluid (CSF) where cf-tDNA variant allele fractions are high ( >1%). However, plasma cf-tDNA signal is much lower than CSF (typically < 0.5%), and no platforms have demonstrated the feasibility of quickly (< 1day) sequencing brain tumor cf-tDNA in plasma samples to our knowledge. METHODS To solve these problems, we have developed a same-day, multiplexed, concatemeric consensus error corrected (CCEC-Seq) assay approach for Nanopore sequencing. We combine multiplex PCR and loop-mediated isothermal amplification (LAMP) to capture short cf-tDNA fragments and concatemerize them. Sequenced concatemer segments should agree, and allow informatic consensus error correction, reducing Nanopore error rates. RESULTS We generated a multiplex (n = 8) DMG hotspot loci panel, which was able to reduce sequencing false positive call rates by 3.1x-10.8x. We were able to employ the CCEC-Seq technique on serial plasma samples from a patient with DMG with H3.3K27M mutation undergoing treatment with ONC201 with results comparable to a previously validated ddPCR assay. Ongoing work will apply this multiplex CCEC-Seq panel to a larger cohort of serial DMG plasma samples. CONCLUSION To our knowledge, this is the first demonstration of same-day, sequencing-based, liquid biopsy protocol for a plasma sample from a brain tumor patient. This approach has the potential to greatly reduce resource requirements, and ease of operation for liquid biopsy for DMG and other brain tumor disease monitoring.