Abstract
BACKGROUND: Genomic profiling of cerebrospinal fluid (CSF) can be used to detect actionable mutations and guide clinical treatment of non-small cell lung cancer (NSCLC) patients with central nervous system (CNS) metastases. Examining the performance of CSF samples in real-world settings can confirm the potential of CSF genotyping for guiding therapy in clinical practice. PATIENTS AND METHODS: We included 1,396 samples from 970 NSCLC patients with CNS metastases in real-world settings. All samples underwent targeted next-generation sequencing of 1,021 cancer-relevant genes. In total, 100 CSF samples from 77 patients who had previously received targeted treatment were retrospectively analyzed to explore the mechanisms of TKI-resistance. RESULTS: For NSCLC patients with CNS metastases, CSF samples were slightly more often used for genomic sequencing in treated patients with only distant CNS metastases compared to other patients (10.96% vs. 0.81-9.61%). Alteration rates in CSF samples were significantly higher than those in plasma, especially for copy number variants (CNV). The MSAFs of CSF samples were significantly higher than those of plasma and tumor tissues (all p <0.001). Remarkably, detection rates of all actionable mutations and EGFR in CSF were higher than those in plasma samples of treated patients (all p <0.0001). For concordance between paired CSF and plasma samples that were simultaneously tested, the MSAF of the CSF was significantly higher than that of matched plasma cfDNA (p <0.001). From multiple comparisons, it can be seen that CSF better detects alterations compared to plasma, especially CNV and structural variant (SV) alterations. CSF cfDNA in identifying mutations can confer the reason for the limited efficacy of EGFR-TKIs for 56 patients (78.87%, 56/71). CONCLUSIONS: This real-world large cohort study confirmed that CSF had higher sensitivity than plasma in identifying actionable mutations and showed high potential in exploring underlying resistance mechanisms. CSF can be used in genomics profiling to facilitate the broad exploration of potential resistance mechanisms for NSCLC patients with CNS metastases.