Abstracts Background Accurate glioma diagnosis relies on tissue biopsy, which is often challenging. Liquid biopsy offers an alternative, but single - component cfDNA or cfRNA approaches have limited comprehensiveness. We developed and validated GlioKit, a platform for simultaneou cfDNA and cfRNA extraction from cerebrospinal fluid (CSF) to enhance diagnostic coverage, and evaluated its accuracy by correlating CSF-derived molecular profiles with tumor characteristics. Methods We retrospectively analyzed 71 patients from the China Glioma Liquid Biopsy MultiOmics Atlas (C-Glioma) database, including 31 GBM, 36 IDH-mutant gliomas, 4 diffuse midline gliomas (DMGs). Using GlioKit, we simultaneously extracted and analyzed CSF cfDNA and cfRNA, targeting 6 mutations (IDH1, IDH2, H3F3A, HIST1H3B, TERT, BRAF) and 2 fusions (EGFR, MET). Concordance between CSF-derived mutations and matched tumor tissue features was assessed overall and stratified by CSF collection method (lumbar puncture, surgery, or Ommaya reservoir). Results Among 71 glioma CSF samples, cfDNA mutations were detected in 55 (77%), cfRNA in 15 of 44 (34%). Overall cfDNA-tumor concordance was 89%, cfRNA was 73%. Subgroup analysis revealed cfDNA detection rates of 33/41 (surgery), 11/15 (Ommaya), and 11/15 (lumbar puncture); cfRNA detection rates were 5/25, 6/11, and 4/8, respectively. Corresponding concordance rates were: cfDNA - 30/33 (surgery), 10/11 (Ommaya), 9/11 (lumbar puncture); cfRNA - 4/5, 5/6, and 2/4. Conclusions CSF-derived cfDNA and cfRNA variations closely align with tumor genomic alterations, validating CSF as a minimally invasive source for glioma molecular subtyping. GlioKit has potential for glioma diagnosis and therapy planning.
Mz et al. (2026) studied this question.