Detection of genes mutations in cerebrospinal fluid circulating tumor DNA from neoplastic meningitis patients using next generation sequencing.

BACKGROUND: This study profiled the somatic genes mutations and the copy number variations (CNVs) in cerebrospinal fluid (CSF)-circulating tumor DNA (ctDNA) from patients with neoplastic meningitis (NM). METHODS: A total of 62 CSF ctDNA samples were collected from 58 NM patients for the next generation sequencing. The data were bioinformatically analyzed by (Database for Annotation, Visualization and Integrated Discovery) DAVID software. RESULTS: The most common mutated gene was TP53 (54/62; 87.10%), followed by EGFR (44/62; 70.97%), PTEN (39/62; 62.90%), CDKN2A (32/62; 51.61%), APC (27/62: 43.55%), TET2 (27/62; 43.55%), GNAQ (18/62; 29.03%), NOTCH1 (17/62; 27.42%), VHL (17/62; 27.42%), FLT3 (16/62; 25.81%), PTCH1 (15/62; 24.19%), BRCA2 (13/62; 20.97%), KDR (10/62; 16.13%), KIT (9/62; 14.52%), MLH1 (9/62; 14.52%), ATM (8/62; 12.90%), CBL (8/62; 12.90%), and DNMT3A (7/62; 11.29%). The mutated genes were enriched in the PI3K-Akt signaling pathway by the KEGG pathway analysis. Furthermore, the CNVs of these genes were also identified in these 62 samples. The mutated genes in CSF samples receiving intrathecal chemotherapy and systemic therapy were enriched in the ERK1/2 signaling pathway. CONCLUSIONS: This study identified genes mutations in all CSF ctDNA samples, indicating that these mutated genes may be acted as a kind of biomarker for diagnosis of NM, and these mutated genes may affect meningeal metastasis through PI3K-Akt signaling pathway.

Evaluating the cerebrospinal fluid ctDNA detection by next-generation sequencing in the diagnosis of meningeal Carcinomatosis.

BACKGROUND: Meningeal carcinomatosis (MC) is the most severe form of brain metastasis and causes significant morbidity and mortality. Currently, the diagnosis of MC is routinely confirmed on the basis of clinical manifestation, positive cerebrospinal fluid (CSF) cytology, and/or neuroimaging features. However, negative rate of CSF cytology and neuroimaging findings often result in a failure to diagnose MC from the patients who actually have the disease. Here we evaluate the CSF circulating tumor DNA (ctDNA) in the diagnosis of MC. METHODS: A total of 35 CSF samples were collected from 35 patients with MC for CSF cytology examination, CSF ctDNA extraction and cancer-associated gene mutations detection by next-generation sequencing (NGS) at the same time. RESULTS: The most frequent primary tumor in this study was lung cancer (26/35, 74%), followed by gastric cancer (2/35, 6%), breast cancer (2/35, 6%), prostatic cancer (1/35, 3%), parotid gland carcinoma (1/35, 3%) and lymphoma (1/35, 3%) while no primary tumor could be found in the remaining 2 patients in spite of using various inspection methods. Twenty-five CSF samples (25/35; 71%) were found neoplastic cells in CSF cytology examination while all of the 35 CSF samples (35/35; 100%) were revealed having detectable ctDNA in which cancer-associated gene mutations were detected. All of 35 patients with MC in the study underwent contrast-enhanced brain MRI and/or CT and 22 neuroimaging features (22/35; 63%) were consistent with MC. The sensitivity of the neuroimaging was 88% (95% confidence intervals [95% CI], 75 to 100) (p = 22/25) and 63% (95% CI, 47 to 79) (p = 22/35) compared to those of CSF cytology and CSF ctDNA, respectively. The sensitivity of the CSF cytology was 71% (95% CI, 56 to 86) (n = 25/35) compared to that of CSF ctDNA. CONCLUSIONS: This study suggests a higher sensitivity of CSF ctDNA than those of CSF cytology and neuroimaging findings. We find cancer-associated gene mutations in ctDNA from CSF of patients with MC at 100% of our cohort, and utilizing CSF ctDNA as liquid biopsy technology based on the detection of cancer-associated gene mutations may give additional information to diagnose MC with negative CSF cytology and/or negative neuroimaging findings.