Genomic Alterations Identification and Resistance Mechanisms Exploration of NSCLC With Central Nervous System Metastases Using Liquid Biopsy of Cerebrospinal Fluid: A Real-World Study - Shen, Fangfang; Liang, Naixin; Fan, Zaiwen; Zhao, Min; Kang, Jing; Wang, Xifang; Hu, Qun; Mu, Yongping; Wang, Kai; Yuan, Mingming; Chen, Rongrong; Guo, Wei; et al. (Frontiers in Oncology, 2022)
Background: Genomics profiling of cerebrospinal fluid (CSF) could be used to detect actionable mutations to guide the clinical treatment of non-small cell lung cancer (NSCLC) patients with central nervous system (CNS) metastases. Examining the performance of CSF samples in a real-world setting can be further confirmed the potential for CSF in genotyping for guiding therapy in clinical practice. Patients and methods: The cohort encompasses 1396 samples from 970 NSCLC patients with CNS metastases in a real-world setting. All samples were subjected to the targeted next-generation sequencing of 1021 cancer-relevant genes. One hundred CSF samples of 77 patients that had previously received targeted treatment were retrospectively analyzed to exploring the mechanisms of TKI-resistance. Results: For NSCLC patients with CNS metastases, CSF samples were used for genomic sequencing slightly more often in the treated patients that had distant metastases only from CNS than in the other patients (10.96% vs. 081-9.61%). The alteration rates in CSF samples were significantly higher than that in plasma, especially of CNV alterations. The MSAFs of CSF samples were significantly higher than those of plasma and tumor tissues (all p<0.001). Remarkably, the detection rates of all actionable mutations and EGFR in CSF were higher than those in plasma samples in treated patients (all p<0.0001). For concordance between paired CSF and plasma samples that tested simultaneously, the MSAF of the CSF was significantly higher than that of the matched plasma cfDNA (p<0.001). In the process of multiple comparison, it can be seen that CSF is better than plasma in detecting alterations, especially in detecting CNV and SV alteration. And CSF cfDNA in identifying mutations can confer the reason for limited the efficacy of EGFR-TKIs for 56 patients (78.87%, 56/71). Conclusions: This real-world large cohort study verified that CSF had higher sensitivity than plasma for identifying actionable mutations, and showed high potential to explore the underlying resistance mechanisms. CSF could be used in genomics profiling to facilitate the broad exploration of potential resistance mechanisms for NSCLC patients with CNS metastases.