Related Experiment Video
Updated: Jun 26, 2026

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids
Published on: June 8, 2019
Longitudinal CSF Tumor Cell Enumeration and Mutational Analysis as a Driver for Leptomeningeal Disease Management
Arushi Tripathy1, Pericles Corkos2, Barbara Blouw3
1Department of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.
Background:
Leptomeningeal disease (LMD) is challenging to diagnose and monitor given the poor sensitivity of current gold-standard diagnostics. Cerebrospinal fluid tumor cells (CSF-TCs) have been studied as a biomarker for disease management because oncogene amplification of the primary, metastatic, and CNS metastatic tumors can be heterogeneous. The CNSide platform enumerates CSF-TCs and analyzes oncogene expression via immunocytochemistry (ICC), fluorescent in situ hybridization (FISH), and next-generation sequencing (NGS). We report the utility of this combined enumerative and mutational testing for LMD diagnosis and disease monitoring.
Methods:
A multicenter, retrospective analysis of commercially ordered assays from two health systems between January 2020 and July 2023 included 613 tests on 218 individual patients with suspected or confirmed LMD. To date, this is the largest cohort of patients in LMD literature evaluated using CSF-TCs.
Results:
CSF-TCs were detected in 67% (412/613) of samples. The most analyzed cancer types were breast (n = 105) and lung (n = 65). In lung cancer, anaplastic lymphoma kinase (ALK) was detected in 14% (17/118), and c-MET was detected in 61% (78/128). In breast cancer, HER2 was detected in 39% (65/168), and estrogen receptor (ER) was detected in 26% (44/168). Sixty-six patients underwent 2+ longitudinal CSF draws; among these, there were 58 flips in oncogene detection over time, and 30% (20/66) of patients had at least one biomarker change in the CSF.
Conclusions:
Longitudinal combined ICC/FISH/NGS CSF testing demonstrates a wide range in CSF-TC enumeration, which may be correlated with clinical course, and furthermore identifies actionable tumor markers that frequently fluctuate over time. Utilization of this platform would enable timely, personalized LMD-specific chemotherapy.

