Clin Chem. 2015 Mar;61(3):514-22. doi: 10.1373/clinchem.2014.235457. Epub 2015 Jan 20.

Brain tumor mutations detected in cerebral spinal fluid.

Pan W¹, Gu W², Nagpal S³, Gephart MH⁴, Quake SR⁵.

Author information

¹Department of Bioengineering.
²Department of Bioengineering, Department of Pathology and Laboratory Medicine, University of California-San Francisco, San Francisco, CA.
³Department of Neurology, Stanford University, Stanford, CA;
⁴Department of Neurosurgery, and quake@stanford.edu mghayden@stanford.edu.
⁵Department of Bioengineering, quake@stanford.edu mghayden@stanford.edu.

Abstract

BACKGROUND:

Detecting tumor-derived cell-free DNA (cfDNA) in the blood of brain tumor patients is challenging, presumably owing to the blood-brain barrier. Cerebral spinal fluid (CSF) may serve as an alternative "liquid biopsy" of brain tumors by enabling measurement of circulating DNA within CSF to characterize tumor-specific mutations. Many aspects about the characteristics and detectability of tumor mutations in CSF remain undetermined.

METHODS:

We used digital PCR and targeted amplicon sequencing to quantify tumor mutations in the cfDNA of CSF and plasma collected from 7 patients with solid brain tumors. Also, we applied cancer panel sequencing to globally characterize the somatic mutation profile from the CSF of 1 patient with suspected leptomeningeal disease.

RESULTS:

We detected tumor mutations in CSF samples from 6 of 7 patients with solid brain tumors. The concentration of the tumor mutant alleles varied widely between patients, from <5 to nearly 3000 copies/mL CSF. We identified 7 somatic mutations from the CSF of a patient with leptomeningeal disease by use of cancer panel sequencing, and the result was concordant with genetic testing on the primary tumor biopsy.

CONCLUSIONS:

Tumor mutations were detectable in cfDNA from the CSF of patients with different primary and metastatic brain tumors. We designed 2 strategies to characterize tumor mutations in CSF for potential clinical diagnosis: the targeted detection of known driver mutations to monitor brain metastasis and the global characterization of genomic aberrations to direct personalized cancer care.