Abstract
Genomic profiling of central nervous system (CNS) metastases has the potential to guide treatments. In the present study, we included 584 patients with non-small-cell lung cancer and CNS metastases and performed a comprehensive analysis of cerebrospinal fluid (CSF) circulating tumor DNA (ctDNA) with clinicopathological annotation. CSF ctDNA-positive detection was independently associated with shorter survival than negative detection (hazard ratio (HR) = 1.9, 95% confidence interval (CI) = 1.56–2.39; P < 0.0001). Matched tumor–CSF analysis characterized the CSF private molecular features causing poor survival (HR = 1.64, 95% CI = 1.15–2.32, P = 0.006). A multimetric CSF ctDNA prognostic model integrating CSF ctDNA features and clinical factors was developed for risk-stratifying CNS metastases and validated in an independent cohort. Among patients with treatment histories available, those positive for a driver alteration by CSF ctDNA showed a survival benefit from CSF-matched therapy (HR = 0.78, 95% CI = 0.65–0.92, P = 0.003). Longitudinal monitoring by CSF identified CNS-specific resistant mechanisms and a second matched targeted therapy indicating improved survival (HR = 0.56, 95% CI = 0.35–0.91, P = 0.018). These findings support the clinical value of CSF ctDNA for risk-stratifying CNS metastases and guiding therapy.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$32.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to the full article PDF.
USD 39.95
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
The raw sequence data of CSF and tumor reported in the present paper have been deposited in the Genome Sequence Archive (GSA) in the National Genomics Data Center, China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences (GSA, human accession no. HRA007298) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa-human with details on how to access the raw sequencing data for this article. Clinical and pathological data necessary for the conduct of the analyses are available within the Article and Supplementary Information. Source data are provided with this paper.
Code availability
The customized code can be assessed at https://github.com/Github0409584/CSFctDNA, SCHISM (https://github.com/KarchinLab/SCHISM) and PyClone (https://github.com/Roth-Lab/pyclone).
References
Gillespie, C. S. et al. Genomic alterations and the incidence of brain metastases in advanced and metastatic non-small cell lung cancer: a systematic review and meta-analysis. J. Thorac. Oncol. 18, 1703–1713 (2023).
Li, Y. S. et al. Leptomeningeal metastases in patients with NSCLC with EGFR mutations. J. Thorac. Oncol. 11, 1962–1969 (2016).
Zheng, M. M. et al. Clinical utility of cerebrospinal fluid cell-free DNA as liquid biopsy for leptomeningeal metastases in ALK-rearranged NSCLC. J. Thorac. Oncol. 14, 924–932 (2019).
Sperduto, P. W. et al. Estimating survival in patients With lung cancer and brain metastases: an update of the graded prognostic assessment for lung cancer using molecular markers (lung-molGPA). JAMA Oncol. 3, 827–831 (2017).
De Mattos-Arruda, L. et al. Cerebrospinal fluid-derived circulating tumour DNA better represents the genomic alterations of brain tumours than plasma. Nat. Commun. 6, 8839 (2015).
Zhang, J. T. et al. Longitudinal undetectable molecular residual disease defines potentially cured population in localized non-small cell lung cancer. Cancer Discov 12, 1690–1701 (2022).
Pan, Y. et al. Dynamic circulating tumor DNA during chemoradiotherapy predicts clinical outcomes for locally advanced non-small cell lung cancer patients. Cancer Cell 41, 1763–1773 (2023).
White, M. D. et al. Detection of leptomeningeal disease using cell-fee DNA From cerebrospinal fluid. JAMA Netw. Open 4, e2120040 (2021).
Pentsova, E. I. et al. Evaluating cancer of the central nervous system through next-generation sequencing of cerebrospinal fluid. J. Clin. Oncol. 34, 2404–2415 (2016).
Miller, A. M. et al. Tracking tumour evolution in glioma through liquid biopsies of cerebrospinal fluid. Nature 565, 654–658 (2019).
Berzero, G., Pieri, V., Mortini, P., Filippi, M. & Finocchiaro, G. The coming of age of liquid biopsy in neuro-oncology. Brain 146, 4015–4024 (2023).
Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature 545, 446–451 (2017).
Abbosh, C. et al. Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA. Nature 616, 553–562 (2023).
Le Rhun, E. et al. EANO-ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up of patients with leptomeningeal metastasis from solid tumours. Ann. Oncol. 28, iv84–iv99 (2017).
Shih, D. et al. Genomic characterization of human brain metastases identifies drivers of metastatic lung adenocarcinoma. Nat. Genet. 52, 371–377 (2020).
Li, Y. S. et al. Unique genetic profiles from cerebrospinal fluid cell-free DNA in leptomeningeal metastases of EGFR-mutant non-small-cell lung cancer: a new medium of liquid biopsy. Ann. Oncol. 29, 945–952 (2018).
Jee, J. et al. Overall survival with circulating tumor DNA-guided therapy in advanced non-small-cell lung cancer. Nat. Med. 28, 2353–2363 (2022).
Wang, H. et al. Genes associated with increased brain metastasis risk in non-small cell lung cancer: comprehensive genomic profiling of 61 resected brain metastases versus primary non-small cell lung cancer (Guangdong Association Study of Thoracic Oncology 1036). Cancer 125, 3535–3544 (2019).
Skakodub, A. et al. Genomic analysis and clinical correlations of non-small cell lung cancer brain metastasis. Nat. Commun. 14, 4980 (2023).
Bettegowda, C. et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci. Transl. Med. 6, 224r (2014).
Tivey, A., Church, M., Rothwell, D., Dive, C. & Cook, N. Circulating tumour DNA—looking beyond the blood. Nat. Rev. Clin. Oncol. 19, 600–612 (2022).
Piccioni, D. E. et al. Analysis of cell-free circulating tumor DNA in 419 patients with glioblastoma and other primary brain tumors. CNS Oncol. 8, CNS34 (2019).
Tan, A. C. & Tan, D. Targeted therapies for lung cancer patients with oncogenic driver molecular alterations. J. Clin. Oncol. 40, 611–625 (2022).
Rangachari, D. et al. Brain metastases in patients with EGFR-mutated or ALK-rearranged non-small-cell lung cancers. Lung Cancer 88, 108–111 (2015).
Chikly, B. & Quaghebeur, J. Reassessing cerebrospinal fluid (CSF) hydrodynamics: a literature review presenting a novel hypothesis for CSF physiology. J. Bodyw. Mov. Ther. 17, 344–354 (2013).
Li, M. et al. Utilizing phenotypic characteristics of metastatic brain tumors to improve the probability of detecting circulating tumor DNA from cerebrospinal fluid in non-small-cell lung cancer patients: development and validation of a prediction model in a prospective cohort study. ESMO Open 7, 100305 (2022).
Li, M. et al. Dynamic monitoring of cerebrospinal fluid circulating tumor DNA to identify unique genetic profiles of brain metastatic tumors and better predict intracranial tumor responses in non-small cell lung cancer patients with brain metastases: a prospective cohort study (GASTO 1028). BMC Med. 20, 398 (2022).
Lee, E. Q., Camidge, D. R. & Mehta, G. Extending our reach: expanding enrollment in brain metastases and primary brain tumor clinical trials. Am. Soc. Clin. Oncol. Educ. Book 42, 1–9 (2022).
Liu, S. M. et al. First-line pyrotinib in advanced HER2-mutant non-small-cell lung cancer: a patient-centric phase 2 trial. Nat. Med. 29, 2079–2086 (2023).
Mehta, G. U. et al. US Food and Drug Administration regulatory updates in neuro-oncology. J. Neuro-Oncol. 153, 375–381 (2021).
Liu, A. et al. Serial assessment of measurable residual disease in medulloblastoma liquid biopsies. Cancer Cell 39, 1519–1530 (2021).
Prakadan, S. M. et al. Genomic and transcriptomic correlates of immunotherapy response within the tumor microenvironment of leptomeningeal metastases. Nat. Commun. 12, 5955 (2021).
Paik, P. K. et al. Next-generation sequencing of stage IV squamous cell lung cancers reveals an association of PI3K aberrations and evidence of clonal heterogeneity in patients with brain metastases. Cancer Discov. 5, 610–621 (2015).
Clarke, J. L., Perez, H. R., Jacks, L. M., Panageas, K. S. & Deangelis, L. M. Leptomeningeal metastases in the MRI era. Neurology 74, 1449–1454 (2010).
Jiang, B. Y. et al. Detection of driver and resistance mutations in leptomeningeal metastases of NSCLC by next-generation sequencing of cerebrospinal fluid circulating tumor cells. Clin. Cancer Res. 23, 5480–5488 (2017).
Nguyen, B. et al. Genomic characterization of metastatic patterns from prospective clinical sequencing of 25,000 patients. Cell 185, 563–575 (2022).
Maggie, L. S. et al. Efficacy, safety and dose selection of AZD3759 in patients with untreated EGFR-mutated non-small-cell lung cancer and central nervous system metastases in China (CTONG1702-Arm 8): a multi-center, single-arm, phase 2 trial. eCinicalMedicine 64, 102238 (2023).
Zhou, Q. et al. Safety and efficacy of epitinib for EGFR-mutant non-small cell lung cancer with brain metastases: open-label multicentre dose-expansion phase Ib study. Clin. Lung Cancer 23, e353–e361 (2022).
Zhou, Q. et al. Bevacizumab plus erlotinib in Chinese patients with untreated, EGFR-mutated, advanced NSCLC (ARTEMIS-CTONG1509): a multicenter phase 3 study. Cancer Cell 39, 1279–1291 (2021).
Yang, J. J. et al. Foritinib in advanced ROS1-rearranged non-small-cell lung cancer in China: a multicentre, open-label, single-arm, phase 2 study. Lancet Respir. Med. 12, 671–680 (2024).
Chen, H. et al. 32O first-in-human (FIH) study of SCC244, a novel potent and highly selective c- MET inhibitor, in patients (pts) with advanced non-small cell lung cancer (NSCLC). Ann. Oncol. 32, S14 (2021).
Deveson, I. W. et al. Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology. Nat. Biotechnol. 39, 1115–1128 (2021).
Zheng, M. M. et al. Genotyping of cerebrospinal fluid associated with osimertinib response and resistance for leptomeningeal metastases in EGFR-mutated NSCLC. J. Thorac. Oncol. 16, 250–258 (2021).
Turajlic, S. et al. Tracking cancer evolution reveals constrained routes to metastases: TRACERx renal. Cell 173, 581–594 (2018).
Roth, A. et al. PyClone: statistical inference of clonal population structure in cancer. Nat. Methods 11, 396–398 (2014).
Niknafs, N., Beleva-Guthrie, V., Naiman, D. Q. & Karchin, R. SubClonal hierarchy inference from somatic mutations: automatic reconstruction of cancer evolutionary trees from multi-region next generation sequencing. PLoS Comput. Biol. 11, e1004416 (2015).
Schliep, K. P. phangorn: phylogenetic analysis in R. Bioinformatics 27, 592–593 (2011).
Boiarsky, D. et al. Molecular markers of metastatic disease in KRAS-mutant lung adenocarcinoma. Ann. Oncol. 34, 589–604 (2023).
Acknowledgements
We thank the patients and families who were involved in the present study. We express special thanks to T. Hou and Z. Zhang from Burning Rock Biotech, Guangzhou, China for technical support. We also thank Nanjing Geneseeq Technology Inc., Nanjing, Jiangsu and Kanghui Biotech Co., Ltd., Liaoning, China for technical support. This work was supported by the Youth Fund of the National Natural Science Foundation of China (grant no. 82303641 to M.-M.Z.), the 73rd China Postdoctoral Science Foundation (to M.-M.Z., grant no. 323247), the Guangdong Basic and Applied Basic Research Foundation (grant nos. 2023A1515010577 to M.-M.Z. and 2023A1515010334 to Y.-S.L.), the Guangdong Association of Clinical Trials/Chinese Thoracic Oncology Group (grant no. CTONG-YC20220101 to M.-M.Z.), the Guangdong Provincial People’s Hospital Young Talent Project (grant no. KY012021191 to Y.-S.L.), the cultivation project of the National Natural Science Foundation of China (grant no. KY0120220020 to Y.-S.L.), the National Natural Science Foundation of China Major Joint Project on Key Scientific Issues of Lung Cancer (grant no. 82241235 to W.-Z.Z.) and the Guangdong Provincial Key Lab of Translational Medicine in Lung Cancer (grant no. 2017B030314120 to Y.-L.W.).
Author information
Authors and Affiliations
Contributions
Y.-L.W., M.-M.Z. and Y.-S.L. conceived the project. M.-M.Z. and S.-Y.L. performed the radiomic analysis. B.-Y.J., G.-L.J., H.S., J.-T.Z., S.-Y.L., H.-Y.T., K.Y., F.-M.X., Q.Z., J.-J.Y., X.-C.Z., W.-Z.Z., W.-B.G., Y.P., B.-C.W., H.-J.C., Z.-H.C., Z.W., C.-R.X., S.-Y.M.L., L.Z., M.-M.Z., Y.-S.L. and Y.-L.W. recruited the patients. M.-M.Z., Q.-Z., Y.-S.L., S.-L.C., G.-Q.W. and D.-Q.Z. collected and analyzed the genomic data. M.-M.Z., H.-J.C., Y.-S.L., L.-B.T., H.-H.Y. and L.Z. collected and analyzed the clinical data. Q.Z., B.-Y.J., H.-Y.T., F.-M.X., J.-J.Y., X.-C.Z., W.-Z.Z. and Y.-L.W. administered the project. M.-M.Z., Q.-Z., H.-J.C, Y.-S.L. and Y.-L.W. wrote the manuscript. All co-authors reviewed and approved the final draft of the manuscript.
Corresponding authors
Ethics declarations
Competing interests
Q.Z. declares honoraria from AstraZeneca, Boehringer Ingelheim, BMS, Eli Lilly, MSD, Pfizer, Roche and Sanofi outside the submitted work. W.Z.Z. declares honoraria from AstraZeneca, BMS, MSD, Roche and Innovent outside the submitted work. Y.L.W. declares: advisory services for AstraZeneca, Boehringer Ingelheim, Novartis and Takeda; speaker fees from AstraZeneca, Beigene, Boehringer Ingelheim, BMS, Eli Lilly, MSD, Pfizer, Roche and Sanofi; and grants from AstraZeneca, Boehringer Ingelheim, BMS, Hengrui and Roche outside the submitted work. The remaining authors declare no competing interests.
Peer review
Peer review information
Nature Medicine thanks Bob Li, Michael Schell, Ana Vivancos and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Anna Maria Ranzoni, in collaboration with the Nature Medicine team.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 CSF ctDNA risk stratified LM and BM respectively.
a, Bar plot of detection rate of each EANO ESMO LM subtype. EANO ESMO LM Type I, 208/230, 90.4%; LM Type II, 59/80, 73.8%. Fisher’s exact test with two-sided P value; b. Survival curve for OS of patient risk stratified by EANO ESMO LM subtyping model. LM Type I, n = 230; LM Type II, n = 80. Kaplan-Meier method was used for survival curve, Cox proportional hazard models were used to calculate HRs and CIs, P values are unadjusted two-sided; c. Survival curve for OS of LM patients with and without CSF ctDNA detection (only those available for EANO ESMO LM subtyping evaluation were included), CSF ctDNA+, n = 267; CSF ctDNA-, n = 43; d. Bar plot of detection rate of each GPA BM subtype. All patients were treatment-naive. GPA 0.0-1.0, 6/6, 100%; GPA 1.5-2.0, 13/23, 56.5%; GPA 2.5-3.0, 11/25, 44%; GPA 3.5-4.0, 3/7, 42.9%; e. Survival curve for OS of patients stratified by GPA BM model. GPA 0.0-1.0, n = 6; GPA 1.5-2.0, n = 23; GPA 2.5-3.0, n = 25; GPA 3.5-4.0, n = 7. Fisher’s exact test with two-sided P value; f. Survival curve for OS of treatment-naive BM patients with and without CSF ctDNA detection (only those available for GPA BM subtyping evaluation were included), CSF ctDNA+, n = 33; CSF ctDNA-, n = 28.
Extended Data Fig. 2 Prognostic implication of CSF ctDNA status in patients with positive CSF cytology.
Kaplan-Meier analysis for OS of patients with positive CSF cytology with and without CSF ctDNA detection, CSF ctDNA+, n = 209; CSF ctDNA-, n = 22. Cox proportional hazard models were used to calculate HRs, CIs, and unadjusted two-sided P value.
Extended Data Fig. 3 CSF ctDNA status implicated LM development.
a, Comparison of proportion of developing LM after two-year follow up for patients who had negative CSF cytology & positive CSF ctDNA detection (16/33, 48.5%) and negative CSF cytology & positive CSF ctDNA detection (12/51, 23.5%) at baseline. Only patients with BM at baseline were included with confirmed CSF cytological results and brain MRI. Negative CSF cytology indicated that no tumor cell was found in CSF. Fisher’s exact test with two-sided P value. b, Comparison of lead time of LM diagnosis for patients who had negative CSF cytology & positive CSF ctDNA detection (n = 18, median time, 202 days) and negative CSF cytology & positive CSF ctDNA detection (n = 16, median time, 417 days) at baseline. Follow up time was not restricted to two years in this analysis. Wilcoxon rank sum test with two-sided P value.
Extended Data Fig. 4 CSF-private detection and profiles.
a, Proportion of patients with a specific gene as detected in brain metastases (n = 61, from Wang et al of Asian population18) or in CSF ctDNA (n = 396). R and P values from two-sided Spearman’s correlation coefficient. b, Proportion of patients with a specific gene as detected in paired, treatment-naive primary lung tumor or in CSF ctDNA (n = 33). Tumor and CSF sampling time interval≤30 days. c, CSF-private definition with matched CSF and tumor samples (n = 196), dark purple as CSF-private; light purple as tumor-private; lightest purple as shared alterations. In the matched analysis, alterations were defined as private if they occurred in only the CSF sample or the tumor sample of an individual patient. Shared alterations were defined as those appearing in the same patient’s CSF and tumor samples. CSF-private (+) cohort, n = 134; CSF-private (−) cohort, n = 62; d, Features (sample level, clinical level; genetic alteration level, separated by a line in order) affecting CSF-private detection in all patients (n = 196), and in several subgroups: Comparison of these features between CSF-private (+) and CSF-private (−) cohort among those with LM (n = 132); those with BM (n = 64); previously treated patients (n = 146); treatment naive patients (n = 50), those with time interval of CSF and tumor collection≤30 days (n = 112) and those with time interval of CSF and tumor collection>30 days (n = 84). Blank square indicated that the feature was not applicable in the subgroup. Fisher’s exact test with two-sided P value. Multiple comparison correction was performed using the Benjamini-Hochberg procedure with two-sided q values.
Extended Data Fig. 5 Tumor fraction of CSF private detection.
a. Comparison of tumor fraction (as highest detected VAF) between CSF and paired tumor/tissue in CSF private+ cohort. n = 134, CSF, 0.61. tumor/tissue, 0.37. Wilcoxon rank sum test with two-sided P = 6.8 × 10-7 (***); b. Comparison of tumor fraction (as highest detected VAF) between CSF and paired tumor/tissue in CSF private- cohort. n = 62, CSF, 0.12. tumor/tissue, 0.4. Two-sided P = 3.3 × 10-7 (***).
Supplementary information
Supplementary Information (download PDF )
Supplementary Figs. 1–10.
Supplementary Tables (download XLS )
Supplementary Tables 1–10.
Source data
Source Data Fig. 2 (download XLSX )
Statistical source data for Fig. 2.
Source Data Fig. 3 (download XLSX )
Statistical source data for Fig. 3.
Source Data Fig. 4 (download XLSX )
Statistical source data for Fig. 4.
Source Data Fig. 5 (download XLSX )
Statistical source data for Fig. 5.
Source Data Extended Data Fig. 1 (download XLSX )
Statistical source data for Extended Data Fig. 1.
Source Data Extended Data Figs. 2 and 3 (download XLSX )
Statistical source data for Extended Data Figs. 2 and 3.
Source Data Extended Data Fig. 4 (download XLSX )
Statistical source dataa for Extended Data Fig. 4.
Source Data Extended Data Fig. 5 (download XLSX )
Statistical source data for Extended Data Fig. 5.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Zheng, MM., Zhou, Q., Chen, HJ. et al. Cerebrospinal fluid circulating tumor DNA profiling for risk stratification and matched treatment of central nervous system metastases. Nat Med 31, 1547–1556 (2025). https://doi.org/10.1038/s41591-025-03538-5
Received:
Accepted:
Published:
Version of record:
Issue date:
DOI: https://doi.org/10.1038/s41591-025-03538-5
