Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Clinical Studies

Cyst fluid ctDNA as a biomarker for genetic profiling and treatment monitoring in cystic brain metastases

British Journal of Cancer (2025)Cite this article

Subjects

Abstract

Background

Cystic brain metastases (CBM) present significant clinical challenges due to their heterogeneity and the limitations of current diagnostic methods in guiding treatment. Traditional tissue biopsies are invasive and may not capture tumour heterogeneity, while plasma circulating tumour DNA (ctDNA) analysis is impeded by the blood-brain barrier, leading to low sensitivity for detecting intracranial lesions. These limitations create a critical gap in the personalised management of patients with CBM.

Methods

We evaluated the utility of cyst fluid ctDNA as a minimally invasive biomarker for genetic profiling and treatment monitoring in CBM patients. ctDNA was extracted from cyst fluid, tumour tissue, plasma, and cerebrospinal fluid (CSF) samples collected from 18 patients. NGS was performed to analyse genetic mutations. Mutation detection rates and genetic heterogeneity were compared across different sample types. Dynamic changes in ctDNA mutation abundance in cyst fluid were assessed in relation to treatment responses.

Results

Cyst fluid ctDNA demonstrated a higher mutation detection rate and captured more significant genetic heterogeneity than plasma ctDNA and, in some cases, even matched tissue samples. Clinically significant mutations, including actionable driver genes such as EGFR and TP53, were identified in cyst fluid ctDNA but were undetectable in plasma. Moreover, dynamic changes in the abundance of ctDNA mutations in cyst fluid correlated with treatment responses, indicating its potential for real-time therapeutic efficacy monitoring.

Conclusions

Cyst fluid ctDNA provides a sensitive and comprehensive method for capturing the genetic landscape of CBM, effectively overcoming the limitations of tissue biopsies and plasma ctDNA analysis. By establishing a real-time molecular surveillance network, cyst fluid ctDNA analysis redefines precision neuro-oncology paradigms, transitioning CBM management from static histomolecular snapshots to adaptive therapeutic ecosystems.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Genetic landscape and pathway enrichment analysis of cystic brain metastases.
Fig. 2: Comparative analysis of genetic mutations between brain tumour tissue and cyst fluid ctDNA.
Fig. 3: Consistency of genomic alterations across different sample types.
Fig. 4: Comparison of genetic mutations and cfDNA concentrations between cyst fluid and plasma samples.
Fig. 5: Cyst fluid ctDNA as a biomarker for treatment monitoring in patients with cystic brain metastases.

Similar content being viewed by others

Data availability

The datasets generated during and/or analysed during the current study are not publicly available due to being part of an ongoing long-term study but are available from the corresponding author on reasonable request.

References

  1. Nayak L, Lee EQ, Wen PY. Epidemiology of brain metastases. Curr Oncol Rep. 2012;14:48–54.

    Article  PubMed  Google Scholar 

  2. Rehman AU, Khan P, Maurya SK, Siddiqui JA, Santamaria-Barria JA, Batra SK, et al. Liquid biopsies to occult brain metastasis. Mol Cancer. 2022;21:113.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Aizer AA, Lamba N, Ahluwalia MS, Aldape K, Boire A, Brastianos PK, et al. Brain metastases: a Society for Neuro-Oncology (SNO) consensus review on current management and future directions. Neuro Oncol. 2022;24:1613–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Xu YB, Zhang Y, Song Z, Wang W, Shao L. Treatment and prognosis of solid and cystic brain metastases in patients with non-small-cell lung cancer. Cancer Manag Res. 2021;13:6309–17.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Brigell RH, Cagney DN, Martin AM, Besse LA, Catalano PJ, Lee EQ, et al. Local control after brain-directed radiation in patients with cystic versus solid brain metastases. J Neurooncol. 2019;142:355–63.

    Article  PubMed  Google Scholar 

  6. Lin X, DeAngelis LM. Treatment of brain metastases. J Clin Oncol. 2015;33:3475–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Tabouret E, Chinot O, Metellus P, Tallet A, Viens P, Gonçalves A. Recent trends in epidemiology of brain metastases: an overview. Anticancer Res. 2012;32:4655–62.

    PubMed  Google Scholar 

  8. Boire A, Brastianos PK, Garzia L, Valiente M. Brain metastasis. Nat Rev Cancer. 2020;20:4–11.

    Article  CAS  PubMed  Google Scholar 

  9. Barnholtz-Sloan JS, Sloan AE, Davis FG, Vigneau FD, Lai P, Sawaya RE. Incidence proportions of brain metastases in patients diagnosed (1973 to 2001) in the Metropolitan Detroit Cancer Surveillance System. J Clin Oncol. 2004;22:2865–72.

    Article  PubMed  Google Scholar 

  10. Soffietti R, Rudà R, Mutani R. Management of brain metastases. J Neurol. 2002;249:1357–69.

    Article  PubMed  Google Scholar 

  11. Amidon RF, Livingston K, Kleefisch CJ, Martens M, Straza M, Puckett L, et al. Cystic brain metastasis outcomes after gamma knife radiation therapy. Adv Radiat Oncol. 2024;9:101304.

    Article  CAS  PubMed  Google Scholar 

  12. Patel KR, Prabhu RS, Kandula S, Murphy ES. Cystic brain metastases: an evidence-based review of management. Clin Neurol Neurosurg. 2014;125:30–34.

    Google Scholar 

  13. Halasz LM, Rockhill JK. Stereotactic radiosurgery for the management of brain metastases. Neurosurg Clin North Am. 2013;24:521–30.

    Google Scholar 

  14. Quigley MR, Fukui O. The impact of cystic metastases on the neurocognition of patients with brain metastases. J Neuro-Oncol. 2010;98:107–15.

    Google Scholar 

  15. Fidler IJ, Balasubramanian K, Lin Q, Kim SW. The brain microenvironment and cancer metastasis. Mol Oncol. 2020;14:2531–48.

    Google Scholar 

  16. Li YS, Jiang BY, Yang JJ, Zhang XC, Zhong WZ. 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. 2016;27:1945–50.

    Google Scholar 

  17. Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med. 2012;366:883–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Wan JCM, Massie C, Garcia-Corbacho J, Mouliere F, Brenton JD, Caldas C. Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nat Rev Cancer. 2017;17:223–38.

    Article  CAS  PubMed  Google Scholar 

  19. Lam VK, Zhang J, Wu CC, Tran HT, Li L, Diao L, et al. Genotype-specific differences in circulating tumor DNA levels in advanced NSCLC. J Thorac Oncol. 2021;16:601–9.

    Article  CAS  PubMed  Google Scholar 

  20. Laguna JC, Pastor B, Nalda I, Hijazo-Pechero S, Teixido C, Potrony M, et al. Incidental pathogenic germline alterations detected through liquid biopsy in patients with solid tumors: prevalence, clinical utility and implications. Br J Cancer. 2024;130:1420–31.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Hong TH, Hwang S, Dasgupta A, Abbosh C, Hung T, Bredno J, et al. Clinical utility of tumor-naive presurgical circulating tumor DNA detection in early-stage NSCLC. J Thorac Oncol. 2024;19:1512–24.

    Article  CAS  PubMed  Google Scholar 

  22. De Mattos-Arruda L, Mayor R, Ng CKY, Weigelt B, Martínez-Ricarte F, Torrejon D, et al. Cerebrospinal fluid-derived circulating tumour DNA better represents the genomic alterations of brain tumours than plasma. Nat Commun. 2015;6:8839.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Pentsova EI, Shah RH, Tang J, Boire A, Lin X, Kim S, et al. Evaluating cancer of the central nervous system through next-generation sequencing of cerebrospinal fluid. J Clin Oncol. 2016;34:2404–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Wang Y, Springer S, Zhang M, McMahon KW, Kinde I, Dobbyn L, et al. Detection of tumor-derived DNA in cerebrospinal fluid of patients with primary tumors of the brain and spinal cord. Proc Natl Acad Sci. 2015;112:9704–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Pan W, Gu W, Nagpal S, Gephart MH, Quake SR. Brain tumor mutations detected in cerebral spinal fluid. Clin Chem. 2015;61:514–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Wang X, Bai H, Zhang J, Wang Z, Duan J, Cai H, et al. Genetic intratumor heterogeneity remodels the immune microenvironment and induces immune evasion in brain metastasis of lung cancer. J Thorac Oncol. 2024;19:252–72.

    Article  CAS  PubMed  Google Scholar 

  27. Blumenthal DT, Fink KL. Liquid biopsy for assessment of response and resistance in primary brain tumors: challenges and prospects. Mol Diagn Ther. 2015;19:339–51.

    Google Scholar 

  28. Stallard S, Savelieff MG, Wierzbicki K, Bielas JH. Circulating tumor DNA in cerebrospinal fluid: a window into brain tumor genetic heterogeneity. Oncotarget. 2016;7:44777–90.

    Google Scholar 

  29. Piccioni DE, Achrol AS, Kharbanda S, Liebes L, Neuhaus J, Cabral M, et al. Analysis of cell-free circulating tumor DNA in cerebrospinal fluid as a surrogate for medulloblastoma tumor biopsies. Oncotarget. 2019;10:551–60.

    Google Scholar 

  30. Icard P, Simula L, Fournel L, Leroy K, Lupo A, Damotte D, et al. The strategic roles of four enzymes in the interconnection between metabolism and oncogene activation in non-small cell lung cancer: therapeutic implications. Drug Resist Updat. 2022;63:100852.

    Article  CAS  PubMed  Google Scholar 

  31. Fabbri L, Chakraborty A, Robert C, Vagner S. The plasticity of mRNA translation during cancer progression and therapy resistance. Nat Rev Cancer. 2021;21:558–77.

    Article  CAS  PubMed  Google Scholar 

  32. Bedard PL, Hansen AR, Ratain MJ, Siu LL. Tumour heterogeneity in the clinic. Nature. 2013;501:355–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. McGranahan N, Swanton C. Clonal heterogeneity and tumor evolution: past, present, and the future. Cell. 2017;168:613–28.

    Article  CAS  PubMed  Google Scholar 

  34. Siravegna G, Marsoni S, Siena S, Bardelli A. Integrating liquid biopsies into the management of cancer. Nat Rev Clin Oncol. 2017;14:531–48.

    Article  CAS  PubMed  Google Scholar 

  35. Dagogo-Jack I, Shaw AT. Tumour heterogeneity and resistance to cancer therapies. Nat Rev Clin Oncol. 2018;15:81–94.

    Article  CAS  PubMed  Google Scholar 

  36. Nayak L, Bettegowda C, Scherer F, Galldiks N, Ahluwalia M, Baraniskin A, et al. Liquid biopsy for improving diagnosis and monitoring of CNS lymphomas: a RANO review. Neuro Oncol. 2024;26:993–1011.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Kojic M, Maybury MK, Waddell N, Koufariotis LT, Addala V, Millar A, et al. Efficient detection and monitoring of pediatric brain malignancies with liquid biopsy based on patient-specific somatic mutation screening. Neuro Oncol. 2023;25:1507–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Pentsova E. Applications of cerebrospinal fluid circulating tumor cells and circulating tumor-derived DNA in diagnosis, prognosis, and personalized treatment of CNS metastases. Front Oncol. 2024;14:1409383.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Wu J, Liu Z, Huang T, Wang Y, Song MM, Song T, et al. Cerebrospinal fluid circulating tumor DNA depicts profiling of brain metastasis in NSCLC. Mol Oncol. 2023;17:810–24.

    Article  CAS  PubMed  Google Scholar 

  40. Pathakumari B, Prabhavathi M, Anbarasu D, Paramanandhan P, Raja A. Dynamic IgG antibody response to immunodominant antigens of M. tuberculosis for active TB diagnosis in high endemic settings. Clin Chim Acta. 2016;461:25–33.

    Article  CAS  PubMed  Google Scholar 

  41. Zhitnyuk YV, Koval AP, Alferov AA, Shtykova YA, Mamedov IZ, Kushlinskii NE, et al. Deep cfDNA fragment end profiling enables cancer detection. Mol Cancer. 2022;21:26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Miller AM, Shah RH, Pentsova EI, Pourmaleki M, Briggs S, Distefano N, et al. Tracking tumour evolution in glioma through liquid biopsies of cerebrospinal fluid. Nature. 2019;565:654–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Remon J, Besse B, Aix SP, Callejo A, Al-Rabi K, Bernabe R, et al. Osimertinib treatment based on plasma T790M monitoring in patients with EGFR-mutant non-small-cell lung cancer (NSCLC): EORTC Lung Cancer Group 1613 APPLE phase II randomized clinical trial. Ann Oncol. 2023;34:468–76.

    Article  CAS  PubMed  Google Scholar 

  44. Best MG, Wesseling P, Wurdinger T. Tumor-educated platelets as a noninvasive biomarker source for cancer detection and progression monitoring. Cancer Res. 2018;78:3407–12.

    Article  CAS  PubMed  Google Scholar 

  45. Jiang T, et al. Oncogenic drivers in brain metastases of non-small-cell lung cancer: Implications for clinical practice. J Cancer Res Clin Oncol. 2019;145:291–300.

    Google Scholar 

  46. Olsson B, Lautner R, Andreasson U, Ohrfelt A, Portelius E, Bjerke M, et al. CSF and blood biomarkers for the diagnosis of Alzheimer’s disease: a systematic review and meta-analysis. Lancet Neurol. 2016;15:673–84.

    Article  CAS  PubMed  Google Scholar 

  47. Abbosh C, Birkbak NJ, Wilson GA, Jamal-Hanjani M, Constantin T, Salari R, et al. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature. 2017;545:446–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Diehl F, Schmidt K, Choti MA, Romans K, Goodman S, Li M, et al. Circulating mutant DNA to assess tumor dynamics. Nat Med. 2008;14:985–90.

    Article  CAS  PubMed  Google Scholar 

  49. Bosse Y, Dasgupta A, Abadier M, Guthrie V, Song F, Saavedra Armero V, et al. Prognostic implication of methylation-based circulating tumor DNA detection prior to surgery in stage I non-small cell lung cancer. Cancer Lett. 2024;594:216984.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge Prof. Xun Jin and Prof. Manqing Cao for their discussions and advice.

Funding

This work was supported by the China Postdoctoral Science Foundation (grant no. 2024M762383) and the National Natural Science Foundation of China (grant no. 82103642, 82073276, 82273100, 82302999, 82272639).

Author information

Authors and Affiliations

  1. Department of Neuro-Oncology and Neurosurgery, Tianjin Medical University Cancer Institute & Hospital,National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China

    Zhen Zhang, Qiang Yin, Peng Li, Zengfeng Sun, Wenliang Li, Qun Liu, Xiaohui Zhang, Peng Wang, Yingzhe Piao, Yalin Lu, Lianwang Li, Kaikai Yi, Chunhua She, Li Ma & Xiaoguang Wang

  2. Department of Biochemistry and Molecular Biology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin, China

    Xingyu Jin & Xun Jin

  3. Nanjing Geneseeq Technology Inc., Nanjing, China

    Jiangyan Zhang

  4. The 2nd Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China

    Manqing Cao

Authors
  1. Zhen Zhang
    View author publications

    Search author on:PubMed Google Scholar

  2. Xingyu Jin
    View author publications

    Search author on:PubMed Google Scholar

  3. Qiang Yin
    View author publications

    Search author on:PubMed Google Scholar

  4. Peng Li
    View author publications

    Search author on:PubMed Google Scholar

  5. Zengfeng Sun
    View author publications

    Search author on:PubMed Google Scholar

  6. Wenliang Li
    View author publications

    Search author on:PubMed Google Scholar

  7. Qun Liu
    View author publications

    Search author on:PubMed Google Scholar

  8. Xiaohui Zhang
    View author publications

    Search author on:PubMed Google Scholar

  9. Peng Wang
    View author publications

    Search author on:PubMed Google Scholar

  10. Yingzhe Piao
    View author publications

    Search author on:PubMed Google Scholar

  11. Yalin Lu
    View author publications

    Search author on:PubMed Google Scholar

  12. Lianwang Li
    View author publications

    Search author on:PubMed Google Scholar

  13. Kaikai Yi
    View author publications

    Search author on:PubMed Google Scholar

  14. Chunhua She
    View author publications

    Search author on:PubMed Google Scholar

  15. Li Ma
    View author publications

    Search author on:PubMed Google Scholar

  16. Jiangyan Zhang
    View author publications

    Search author on:PubMed Google Scholar

  17. Xun Jin
    View author publications

    Search author on:PubMed Google Scholar

  18. Manqing Cao
    View author publications

    Search author on:PubMed Google Scholar

  19. Xiaoguang Wang
    View author publications

    Search author on:PubMed Google Scholar

Contributions

ZZ, MQC, and JYZ analysed the data; XYJ, PL, WLL, ZFS, CHS, QL, YZP, PW, LWL, YLL, KKY LM and QY provided methodology support and performed data validation; ZZ wrote the manuscript; XGW, XJ, and MQC supervised the study. All authors have read and agreed to the published version of the manuscript.

Corresponding authors

Correspondence to Xun Jin, Manqing Cao or Xiaoguang Wang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethical approval and consent to participate

All patient samples were collected with informed consent and approved by the Medical Ethical Committee of Tianjin Medical University Cancer Institute and Hospital (bc20250569). Study participants gave informed consent and provided written consent before tissue collection. Separate written informed consent was obtained from all participants whose identifiable images (e.g., radiological images) were included in this study. This consent explicitly permits the publication of the images in print and online formats. All methods were performed in accordance with the relevant guidelines and regulations.

Consent for publication

All authors consented to the publication.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Z., Jin, X., Yin, Q. et al. Cyst fluid ctDNA as a biomarker for genetic profiling and treatment monitoring in cystic brain metastases. Br J Cancer (2025). https://doi.org/10.1038/s41416-025-03047-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41416-025-03047-9

Search

Advanced search

Quick links