Detection of Neoplasms by Metagenomic Sequencing of Cerebrospinal Fluid

Importance Malignant neoplasms of the central nervous system (CNS) are frequently not detected by cerebrospinal fluid (CSF) flow cytometry or cytology, and clinical phenotypes can overlap with inflammatory meningoencephalitis. Objective To determine whether an existing CSF metagenomic next-generation sequencing (mNGS) assay can identify a hallmark of malignant neoplasms — aneuploidy — in difficult-to-diagnose cases of CNS malignancy. Design Two retrospective, case-control studies included a total of 155 samples from patients with an eventual diagnosis of a CNS malignancy (n=59 patients) and controls with other CNS diseases (n=73 patients). The first study was used to evaluate test performance in positive and negative controls. The second study was used to assess the potential utility of aneuploidy detection in patients whose CSF was sent for mNGS because of suspected neuroinflammatory disease who were ultimately found to have a CNS malignancy. Setting This is a single site study at a large tertiary care center, University of California San Francisco, that enrolled from 2014 to 2019. Participants The test performance case-control study enrolled positive control patients with a CNS malignancy (n=47 patients) and negative controls with other neurologic diseases (n=56 patients) who had had CSF flow cytometry and/or cytology performed. The second case-control study enrolled patients with suspected neuroinflammatory disease who were ultimately diagnosed with a CNS malignancy (n=12) and other neurologic disease controls (n=17). Main Outcome(s) and Measure(s) The primary outcome measures were the performance characteristics of detecting aneuploidy in CSF by a cell-free DNA mNGS assay compared to cytology and/or flow cytometry and the tumor fraction in CSF from patients with CNS malignancies. Results Across the two case-control studies, the overall sensitivity of the CSF mNGS assay for detecting aneuploidy in patients ultimately diagnosed with a CNS malignancy was 75% (63-96%, 95% CI), and specificity was 100% (96-100%, 95% CI). Notably, CSF mNGS detected aneuploidy in 64% of the non-diagnostic cytology and flow cytometry cases in the test performance study and in 55% of the cases with suspected neuroinflammatory disease who were ultimately diagnosed with a CNS malignancy. Of the cases in whom aneuploidy was detected, 90% had multiple chromosomal copy number variants with tumor fractions ranging from 31% to 49%. Conclusions and Relevance Metagenomic NGS of CSF, originally designed to diagnose neurologic infections, detects evidence of CNS malignancies (i.e., aneuploidy) in cases where CSF flow cytometry and/or cytology were negative with a low risk of false positive results. Question Can CSF metagenomic NGS, a test designed to diagnose infections, also detect genetic signatures of cancer in patients with suspected neuroinflammatory disease? Findings Across two case-control studies of patients with negative CSF cytology and/or flow cytometry, CSF mNGS detected genetic evidence for a malignancy with a sensitivity of 75% (63-85%, 95% CI) and specificity of 100% (96-100%, 95% CI). Meaning CSF mNGS, an assay with low sample volume requirements that does not require the preservation of cell integrity, has the potential to complement cancer detection by CSF flow cytometry and cytology. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement Funding/Support: Dr. Gu is supported by the National Institutes of Health National Institute of Cancer grant K08CA230156 and a Burroughs-Wellcome Award. Dr. Wilson is supported by the National Institutes of Health National Institute of Neurological Disorders and Stroke grant K08NS096117, and a Rachleff family endowment. Drs. Wilson, DeRisi, and Gelfand, and Ms. Sample and Zorn are supported by grants from the Sandler Foundation and the William K. Bowes, Jr. Foundation. Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics Statement and Sample Collection CSF samples from the Test Performance case-control study were originally collected at the UCSF Clinical Laboratories between 2017-2019 as part of routine clinical testing and retrospectively enrolled through protocols approved by the UCSF Institutional Review Board (18-25287). For the Suspected Neuroinflammatory Disease study, written and informed consent was obtained from UCSF patients with suspected neuroinflammatory disease (or surrogate representatives) who enrolled in an IRB-approved prospective study between 2014-2019 at UCSF protocols (13-12236). All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Data Availability Raw sequencing data is available on SRA under BioProject PRJNA678570 for all patients who consented to genomic data sharing. All other metadata, including copy ratio plots, raw data linked to those plots, and human-subtracted metagenomics data are located at: .