Rapid Tumor DNA Analysis of Cerebrospinal Fluid Accelerates Treatment of Central Nervous System Lymphoma.

Delays and risks associated with neurosurgical biopsies preclude timely diagnosis and treatment of central nervous system (CNS) lymphoma and other CNS neoplasms. We prospectively integrated targeted rapid genotyping of cerebrospinal fluid (CSF) into the evaluation of 70 patients with CNS lesions of unknown etiology. Participants underwent genotyping of CSF-derived DNA using a qPCR-based approach for parallel detection of single-nucleotide variants in the MYD88, TERT promoter, IDH1, IDH2, BRAF and H3F3A genes within 80 minutes of sample acquisition. Canonical mutations were detected in 42% of patients with neoplasms, including cases of primary and secondary CNS lymphoma, glioblastoma, IDH-mutant brainstem glioma and H3K27M-mutant diffuse midline glioma. Genotyping results eliminated the need for surgical biopsies in 7/33 (21.2%) cases of newly diagnosed neoplasms, resulting in significantly accelerated initiation of disease-directed treatment (median 3 vs 12 days; p = 0.027). This assay was then implemented in a Clinical Laboratory Improvement Amendments (CLIA) environment, with 2-day median turnaround for diagnosis of central nervous system lymphoma from 66 patients across 4 clinical sites. Our study prospectively demonstrates that targeted rapid CSF genotyping influences oncologic management for suspected CNS tumors.

Cerebrospinal fluid cfDNA sequencing for classification of central nervous system glioma.

PURPOSE: Primary central nervous system (CNS) gliomas can be classified by characteristic genetic alterations. In addition to solid tissue obtained via surgery or biopsy, cell-free DNA (cfDNA) from cerebrospinal fluid (CSF) is an alternative source of material for genomic analyses. EXPERIMENTAL DESIGN: We performed targeted next-generation sequencing (NGS) of CSF cfDNA in a representative cohort of 85 patients presenting at two neurooncological centers with suspicion of primary or recurrent glioma. Copy-number variation (CNV) profiles, single nucleotide variants (SNVs), and small insertions/ deletions (indels) were combined into a molecular-guided tumor classification. Comparison with the solid tumor was performed for 38 cases with matching solid tissue available. RESULTS: Cases were stratified into four groups: glioblastoma (n = 32), other glioma (n = 19), non-malignant (n = 17) and non-diagnostic (n = 17). We introduced a molecular-guided tumor classification, which enabled identification of tumor entities and/ or cancer specific alterations in 75.0 % (n = 24) of glioblastoma and 52.6 % (n = 10) of other glioma cases. The overlap between CSF and matching solid tissue was highest for CNVs (26-48 %) and SNVs at pre-defined gene loci (44 %), followed by SNVs/ indels identified via uninformed variant calling (8-14 %). A molecular-guided tumor classification was possible for 23.5 % (n = 4) of non-diagnostic cases. CONCLUSIONS: We developed a targeted sequencing workflow for CSF cfDNA as well as a strategy for interpretation and reporting of sequencing results based on a molecular-guided tumor classification in glioma.