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Objective <p>To evaluate the diagnostic accuracy of copy number variations (CNVs) and metagenomic nextgeneration sequencing (mNGS) in identifying meningeal carcinomatosis (MC) within the cerebrospinal fluid (CSF).</p> Methods <p>Patients diagnosed with MC at Xuanwu Hospital, Capital Medical University, from January 2022 to January 2024, were prospectively enrolled. The diagnosis was confirmed via CSF cytology or meningeal biopsy, and a control group of encephalitis patients was used for comparative analysis. We introduced Onco-mNGS, a novel diagnostic protocol integrating mNGS with CNVs analysis to concurrently identify malignancies and pathogens from CSF specimens.</p> Results <p>The study cohort comprised 12 patients with MC, predominantly with lung cancer. Initial CSF CNVs analysis yielded a sensitivity of 83%, with all control samples testing negative for CNVs, thereby achieving 100% specificity.</p> Conclusions <p>CSF CNVs analysis, in combination with mNGS, presents a promising diagnostic modality for MC, offering high sensitivity and specificity and expanding the clinical utility of CSF mNGS in adjunctive diagnostics.</p>

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Metagenomic next-generation sequencing and chromosomal copy number variation analysis in cerebrospinal fluid for the detection of meningeal carcinomatosis

  • 期刊论文

  • 发表日期：

    2025年7月31日

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  • Weibi Chen,
  • Jing Yuan,
  • Gang Liu,
  • Lili Cui,
  • Fei Tian,
  • Yan Zhang

摘要

Objective

To evaluate the diagnostic accuracy of copy number variations (CNVs) and metagenomic nextgeneration sequencing (mNGS) in identifying meningeal carcinomatosis (MC) within the cerebrospinal fluid (CSF).

Methods

Patients diagnosed with MC at Xuanwu Hospital, Capital Medical University, from January 2022 to January 2024, were prospectively enrolled. The diagnosis was confirmed via CSF cytology or meningeal biopsy, and a control group of encephalitis patients was used for comparative analysis. We introduced Onco-mNGS, a novel diagnostic protocol integrating mNGS with CNVs analysis to concurrently identify malignancies and pathogens from CSF specimens.

Results

The study cohort comprised 12 patients with MC, predominantly with lung cancer. Initial CSF CNVs analysis yielded a sensitivity of 83%, with all control samples testing negative for CNVs, thereby achieving 100% specificity.

Conclusions

CSF CNVs analysis, in combination with mNGS, presents a promising diagnostic modality for MC, offering high sensitivity and specificity and expanding the clinical utility of CSF mNGS in adjunctive diagnostics.