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:

LYMPHOMA

Establishment and molecular characterisation of patient-derived organoids for primary central nervous system lymphoma

Leukemia volume 39, pages 1169–1183 (2025)Cite this article

Subjects

Abstract

Primary central nervous system lymphoma (PCNSL) exhibits substantial intratumoural and intertumoural heterogeneity, complicating the development of effective treatment methods. Existing in vitro models fail to simulate the cellular and mutational diversity of native tumours and require prolonged generation times. Therefore, we developed a culture method for patient-derived PCNSL organoids (CLOs) and evaluated the organoids through extensive molecular characterisation, histopathological analysis, single-nucleus RNA sequencing, bulk RNA sequencing and whole-exome sequencing. These CLOs accurately mimicked the histological attributes, gene expression landscapes and mutational profiles of their original tumours. Single-nucleus RNA sequencing also revealed that CLOs maintained cell-type heterogeneity and the molecular signatures of their original tumours. CLOs were generated within 2 weeks, demonstrating rapid development and reliability. Therapeutic profiling was performed on three selected CLOs treated with four standard drugs. The CLOs exhibited specific sensitivity to methotrexate, and resistance to dexamethasone, ibrutinib and rituximab, suggesting that CLOs may be valuable tools for reflecting drug sensitivities. Taken together, these results emphasise that CLOs effectively emulate the key characteristics of PCNSL, increasing the understanding of the genetic landscape of this complex disease. CLOs provide a rapid and reliable platform for exploring individualised treatment strategies, potentially accelerating the transition of research findings to clinical practice.

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: Study design and generation of organoids from primary tissue samples.
Fig. 2: The genetic fidelity of PCNSL organoids (CLOs) mirrors that of the corresponding parental tumours.
Fig. 3: Preservation of inter- and intratumoural gene expression heterogeneity in PCNSL organoids (CLOs) relative to parental tumours.
Fig. 4: CLO maintenance of cell type heterogeneity of parental tumours by single-nucleus RNA-seq analyses.
Fig. 5: CLO maintenance of the molecular signatures of parental tumours by single-nucleus RNA-seq analyses.
Fig. 6: Evaluating CLO responses to ibrutinib, methotrexate, dexamethasone, and rituximab treatments.

Similar content being viewed by others

Data availability

The WES, RNA-seq, and snRNA-seq raw sequence data have been deposited in the Genome Sequence Archive [62] of the National Genomics Data Centre [63], China National Centre for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences (GSA-Human: HRA005755; HRA009621; https://ngdc.cncb.ac.cn/gsa-human). Any additional information required to reanalyse the data is available from the lead contact upon request.

References

  1. Ferreri AJM, Calimeri T, Cwynarski K, Dietrich J, Grommes C, Hoang-Xuan K, et al. Primary central nervous system lymphoma. Nat Rev Dis Prim. 2023;9:29.

    PubMed  Google Scholar 

  2. Chen T, Liu Y, Wang Y, Chang Q, Wu J, Wang Z, et al. Evidence-based expert consensus on the management of primary central nervous system lymphoma in China. J Hematol Oncol. 2022;15:136.

    PubMed  PubMed Central  Google Scholar 

  3. Schaff LR, Grommes C. Primary central nervous system lymphoma. Blood. 2022;140:971–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. DeAngelis LM, Yahalom J, Thaler HT, Kher U. Combined modality therapy for primary CNS lymphoma. J Clin Oncol. 1992;10:635–43.

    CAS  PubMed  Google Scholar 

  5. Rubenstein JL, Hsi ED, Johnson JL, Jung S-H, Nakashima MO, Grant B, et al. Intensive chemotherapy and immunotherapy in patients with newly diagnosed primary CNS lymphoma: CALGB 50202 (Alliance 50202). J Clin Oncol. 2013;31:3061–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Glass J, Gruber ML, Cher L, Hochberg FH. Preirradiation methotrexate chemotherapy of primary central nervous system lymphoma: long-term outcome. J Neurosurg. 1994;81:188–95.

    CAS  PubMed  Google Scholar 

  7. Mulazzani M, Fräßle SP, von Mücke-Heim I, Langer S, Zhou X, Ishikawa-Ankerhold H, et al. Long-term in vivo microscopy of CAR T cell dynamics during eradication of CNS lymphoma in mice. Proc Natl Acad Sci USA. 2019;116:24275–84.

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Qiu Y, Li Z, Pouzoulet F, Vishnu P, Copland JA, Knutson KL, et al. Immune checkpoint inhibition by anti-PDCD1 (anti-PD1) monoclonal antibody has significant therapeutic activity against central nervous system lymphoma in an immunocompetent preclinical model. Br J Haematol. 2018;183:674–8.

    PubMed  Google Scholar 

  9. Takashima Y, Hayano A, Yamanaka R. Metabolome analysis reveals excessive glycolysis via PI3K/AKT/mTOR and RAS/MAPK signaling in methotrexate-resistant primary CNS lymphoma-derived cells. Clin Cancer Res. 2020;26:2754–66.

    CAS  PubMed  Google Scholar 

  10. Tateishi K, Miyake Y, Kawazu M, Sasaki N, Nakamura T, Sasame J, et al. A hyperactive RelA/p65-hexokinase 2 signaling axis drives primary central nervous system lymphoma. Cancer Res. 2020;80:5330–43.

    PubMed  Google Scholar 

  11. Lee J, Kotliarova S, Kotliarov Y, Li A, Su Q, Donin NM, et al. Tumor stem cells derived from glioblastomas cultured in bFGF and EGF more closely mirror the phenotype and genotype of primary tumors than do serum-cultured cell lines. Cancer Cell. 2006;9:391–403.

    CAS  PubMed  Google Scholar 

  12. Isbell LK, Tschuch C, Doostkam S, Waldeck S, Andrieux G, Shoumariyeh K, et al. Patient-derived xenograft mouse models to investigate tropism to the central nervous system and retina of primary and secondary central nervous system lymphoma. Neuropathol Appl Neurobiol. 2023;49:e12899.

    CAS  PubMed  Google Scholar 

  13. Liu N, Jiang C, Yao X, Fang M, Qiao X, Zhu L, et al. Single-cell landscape of primary central nervous system diffuse large B-cell lymphoma. Cell Discov. 2023;9:55.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Xia Y, Sun T, Li G, Li M, Wang D, Su X, et al. Spatial single cell analysis of tumor microenvironment remodeling pattern in primary central nervous system lymphoma. Leukemia. 2023;37:1499–510.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Hernández-Verdin I, Kirasic E, Wienand K, Mokhtari K, Eimer S, Loiseau H, et al. Molecular and clinical diversity in primary central nervous system lymphoma. Ann Oncol. 2023;34:186–99.

    PubMed  Google Scholar 

  16. Fukumura K, Kawazu M, Kojima S, Ueno T, Sai E, Soda M, et al. Genomic characterization of primary central nervous system lymphoma. Acta Neuropathol. 2016;131:865–75.

    CAS  PubMed  Google Scholar 

  17. Braggio E, Van Wier S, Ojha J, McPhail E, Asmann YW, Egan J, et al. Genome-wide analysis uncovers novel recurrent alterations in primary central nervous system lymphomas. Clin Cancer Res. 2015;21:3986–94.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Mulazzani M, Huber M, Borchard S, Langer S, Angele B, Schuh E, et al. APRIL and BAFF: novel biomarkers for central nervous system lymphoma. J Hematol Oncol. 2019;12:102.

    PubMed  PubMed Central  Google Scholar 

  19. Corsini NS, Knoblich JA. Human organoids: New strategies and methods for analyzing human development and disease. Cell. 2022;185:2756–69.

    CAS  PubMed  Google Scholar 

  20. Xu H, Jiao D, Liu A, Wu K. Tumor organoids: applications in cancer modeling and potentials in precision medicine. J Hematol Oncol. 2022;15:58.

    PubMed  PubMed Central  Google Scholar 

  21. Jacob F, Salinas RD, Zhang DY, Nguyen PTT, Schnoll JG, Wong SZH, et al. A patient-derived glioblastoma organoid model and biobank recapitulates inter- and intra-tumoral heterogeneity. Cell. 2020;180:188–204.e22.

    CAS  PubMed  Google Scholar 

  22. Kawasaki K, Toshimitsu K, Matano M, Fujita M, Fujii M, Togasaki K, et al. An organoid biobank of neuroendocrine neoplasms enables genotype-phenotype mapping. Cell. 2020;183:1420–1435.e21.

    CAS  PubMed  Google Scholar 

  23. van de Wetering M, Francies HE, Francis JM, Bounova G, Iorio F, Pronk A, et al. Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell. 2015;161:933–45.

    PubMed  PubMed Central  Google Scholar 

  24. Swerdlow SH, Campo E, Pileri SA, Harris NL, Stein H, Siebert R, et al. The 2016 revision of the World Health Organization classification of lymphoid neoplasms. Blood. 2016;127:2375–90.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Li S, Xia Z, Cao J, Zhang J, Chen B, Chen T, et al. Proposed new prognostic model using the systemic immune-inflammation index for primary central nervous system lymphoma: A prospective-retrospective multicohort analysis. Front Immunol. 2022;13:1039862.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Hans CP, Weisenburger DD, Greiner TC, Gascoyne RD, Delabie J, Ott G, et al. Confirmation of the molecular classification of diffuse large B-cell lymphoma by immunohistochemistry using a tissue microarray. Blood. 2004;103:275–82.

    CAS  PubMed  Google Scholar 

  27. Li Q, Ma J, Ma Y, Lin Z, Kang H, Chen B. Improvement of outcomes of an escalated high-dose methotrexate-based regimen for patients with newly diagnosed primary central nervous system lymphoma: a real-world cohort study. Cancer Manag Res. 2021;13:6115–22.

    PubMed  PubMed Central  Google Scholar 

  28. Lancaster MA, Knoblich JA. Organogenesis in a dish: modeling development and disease using organoid technologies. Science. 2014;345:1247125.

    PubMed  Google Scholar 

  29. Zylber-Katz E, Gomori JM, Schwartz A, Lossos A, Bokstein F, Siegal T. Pharmacokinetics of methotrexate in cerebrospinal fluid and serum after osmotic blood-brain barrier disruption in patients with brain lymphoma. Clin Pharm Ther. 2000;67:631–41.

    CAS  Google Scholar 

  30. Lionakis MS, Dunleavy K, Roschewski M, Widemann BC, Butman JA, Schmitz R, et al. Inhibition of B cell receptor signaling by ibrutinib in primary CNS lymphoma. Cancer Cell. 2017;31:833–843.e5.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Jackson RK, Liebich M, Berry P, Errington J, Liu J, Parker C, et al. Impact of dose and duration of therapy on dexamethasone pharmacokinetics in childhood acute lymphoblastic leukaemia-a report from the UKALL 2011 trial. Eur J Cancer. 2019;120:75–85.

    CAS  PubMed  Google Scholar 

  32. Yonezawa A, Otani Y, Kitano T, Mori M, Masui S, Isomoto Y, et al. Concentration and glycoform of rituximab in plasma of patients with B cell Non-Hodgkin’s lymphoma. Pharm Res. 2019;36:82.

    PubMed  Google Scholar 

  33. Xia W, Hu B, Li H, Shi W, Tang Y, Yu Y, et al. Deep learning for automatic differential diagnosis of primary central nervous system lymphoma and glioblastoma: multi-parametric magnetic resonance imaging based convolutional neural network model. J Magn Reson Imaging. 2021;54:880–7.

    PubMed  Google Scholar 

  34. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26:589–95.

    PubMed  PubMed Central  Google Scholar 

  35. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The genome analysis toolkit: a mapreduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20:1297–303.

    CAS  PubMed  PubMed Central  Google Scholar 

  36. li shengjie, Li D, Xia Z, Wu J, Ren J, Li Y et al. Genomic landscape and molecular subtypes of primary central nervous system lymphoma. medRxiv 2024; 2024.10.22.24315961.

  37. Wang Y, Bae T, Thorpe J, Sherman MA, Jones AG, Cho S, et al. Comprehensive identification of somatic nucleotide variants in human brain tissue. Genome Biol. 2021;22:92.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Alexandrov LB, Nik-Zainal S, Wedge DC, Campbell PJ, Stratton MR. Deciphering signatures of mutational processes operative in human cancer. Cell Rep. 2013;3:246–59.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884–i890.

    PubMed  PubMed Central  Google Scholar 

  40. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods. 2008;5:621–8.

    CAS  PubMed  Google Scholar 

  41. Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30:923–30.

    CAS  PubMed  Google Scholar 

  42. Garber M, Grabherr MG, Guttman M, Trapnell C. Computational methods for transcriptome annotation and quantification using RNA-seq. Nat Methods. 2011;8:469–77.

    CAS  PubMed  Google Scholar 

  43. Bray NL, Pimentel H, Melsted P, Pachter L. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol. 2016;34:525–7.

    CAS  PubMed  Google Scholar 

  44. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.

    PubMed  PubMed Central  Google Scholar 

  45. Kanehisa M. Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28:27–30.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell. 2015;161:1202–14.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Haghverdi L, Lun ATL, Morgan MD, Marioni JC. Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors. Nat Biotechnol. 2018;36:421–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  48. McCarthy DJ, Chen Y, Smyth GK. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res. 2012;40:4288–97.

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Radke J, Ishaque N, Koll R, Gu Z, Schumann E, Sieverling L, et al. The genomic and transcriptional landscape of primary central nervous system lymphoma. Nat Commun. 2022;13:2558.

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Ji AL, Rubin AJ, Thrane K, Jiang S, Reynolds DL, Meyers RM, et al. Multimodal analysis of composition and spatial architecture in human squamous cell carcinoma. Cell. 2020;182:497–514.e22.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Gjorevski N, Sachs N, Manfrin A, Giger S, Bragina ME, Ordóñez-Morán P, et al. Designer matrices for intestinal stem cell and organoid culture. Nature. 2016;539:560–4.

    CAS  PubMed  Google Scholar 

  52. Abbasi J. Patient-derived organoids predict cancer treatment response. JAMA. 2018;319:1427.

    PubMed  Google Scholar 

  53. Broutier L, Mastrogiovanni G, Verstegen MM, Francies HE, Gavarró LM, Bradshaw CR, et al. Human primary liver cancer-derived organoid cultures for disease modeling and drug screening. Nat Med. 2017;23:1424–35.

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Vlachogiannis G, Hedayat S, Vatsiou A, Jamin Y, Fernández-Mateos J, Khan K, et al. Patient-derived organoids model treatment response of metastatic gastrointestinal cancers. Science. 2018;359:920–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Yao Y, Xu X, Yang L, Zhu J, Wan J, Shen L, et al. Patient-derived organoids predict chemoradiation responses of locally advanced rectal cancer. Cell Stem Cell. 2020;26:17–26.e6.

    CAS  PubMed  Google Scholar 

  56. Pina-Oviedo S, Bellamy WT, Gokden M. Analysis of primary central nervous system large B-cell lymphoma in the era of high-grade B-cell lymphoma: detection of two cases with MYC and BCL6 rearrangements in a cohort of 12 cases. Ann Diagn Pathol. 2020;48:151610.

    PubMed  Google Scholar 

  57. Ting C-Y, Chang K-M, Kuan J-W, Sathar J, Chew L-P, Wong O-LJ, et al. Clinical significance of BCL2, C-MYC, and BCL6 genetic abnormalities, Epstein-Barr virus infection, CD5 protein expression, germinal center B cell/non-germinal center B-cell subtypes, co-expression of MYC/BCL2 proteins and co-expression of MYC/BCL2/BCL6 proteins in diffuse large B-cell lymphoma: a clinical and pathological correlation study of 120 patients. Int J Med Sci. 2019;16:556–66.

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Chapuy B, Roemer MGM, Stewart C, Tan Y, Abo RP, Zhang L, et al. Targetable genetic features of primary testicular and primary central nervous system lymphomas. Blood. 2016;127:869–81.

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Los-de Vries GT, Stathi P, Rutkens R, Hijmering NJ, Luijks JACW, Groenen PJTA, et al. Large B-cell Lymphomas of Immune-Privileged Sites Relapse via Parallel Clonal Evolution from a Common Progenitor B Cell. Cancer Res. 2023;83:1917–27.

    CAS  PubMed  Google Scholar 

  60. Brunn A, Nagel I, Montesinos-Rongen M, Klapper W, Vater I, Paulus W, et al. Frequent triple-hit expression of MYC, BCL2, and BCL6 in primary lymphoma of the central nervous system and absence of a favorable MYC(low)BCL2 (low) subgroup may underlie the inferior prognosis as compared to systemic diffuse large B cell lymphomas. Acta Neuropathol. 2013;126:603–5.

    PubMed  Google Scholar 

  61. Montesinos-Rongen M, Akasaka T, Zühlke-Jenisch R, Schaller C, Van Roost D, Wiestler OD, et al. Molecular characterization of BCL6 breakpoints in primary diffuse large B-cell lymphomas of the central nervous system identifies GAPD as novel translocation partner. Brain Pathol. 2003;13:534–8.

    CAS  PubMed  Google Scholar 

  62. Chen T, Chen X, Zhang S, Zhu J, Tang B, Wang A, et al. The genome sequence archive family: toward explosive data growth and diverse data types. Genomics Proteom Bioinforma. 2021;19:578–83.

    Google Scholar 

  63. CNCB-NGDC Members and Partners. Database resources of the national genomics data center, China national center for bioinformation in 2022. Nucleic Acids Res. 2022;50:D27–D38.

    Google Scholar 

Download references

Acknowledgements

We extend their gratitude to Yiyin Zhang from KingMed Diagnostics in Shanghai for his invaluable assistance with data processing. They also wish to express their sincere thanks to the colleagues at Huashan Hospital of Fudan University and Fudan University Shanghai Cancer Centre for their crucial support during the specimen collection process. Appreciation is also extended to ShanghaiTech University for providing the research platform.

Funding

The study was funded by the National Natural Science Foundation of China (82302582), Shanghai Municipal Health Commission Project (20224Y0317), Youth Medical Talents—Clinical Laboratory Practitioner Programme (2022-65), and Industry-University-Research Innovation Fund for Chinese Universities (2023JQ006).

Author information

Authors and Affiliations

  1. Department of Clinical Laboratory, Eye & ENT Hospital, Shanghai Medical College, Fudan University, Shanghai, China

    Shengjie Li, Jun Ren, Jianing Wu, Yingzhu Li & Wenjun Cao

  2. Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China

    Shengjie Li

  3. National Center for Neurological Disorders, Shanghai, China

    Shengjie Li

  4. Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, China

    Shengjie Li

  5. Neurosurgical Institute of Fudan University, Shanghai, China

    Shengjie Li

  6. Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China

    Shengjie Li

  7. Department of Medical Oncology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, China

    Zuguang Xia

  8. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China

    Zuguang Xia

  9. Department of Otolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China

    Chengxun Li

Authors
  1. Shengjie Li
    View author publications

    Search author on:PubMed Google Scholar

  2. Jun Ren
    View author publications

    Search author on:PubMed Google Scholar

  3. Jianing Wu
    View author publications

    Search author on:PubMed Google Scholar

  4. Zuguang Xia
    View author publications

    Search author on:PubMed Google Scholar

  5. Yingzhu Li
    View author publications

    Search author on:PubMed Google Scholar

  6. Chengxun Li
    View author publications

    Search author on:PubMed Google Scholar

  7. Wenjun Cao
    View author publications

    Search author on:PubMed Google Scholar

Contributions

WJC, and SJL conceptualized and designed this study. SJL, YZL, JNW, and JR performed most experiments. ZGX, CXL, and SJL performed partial experiments. SJL, CXL, and JR finished the acquisition and analysis of data. SJL, YZL, and JNW prepared figures, performed the statistical analysis, and wrote original draft. WJC, and SJL reviewed and supervised the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Shengjie Li, Chengxun Li or Wenjun Cao.

Ethics declarations

Competing interests

The authors declare no competing interests.

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

Li, S., Ren, J., Wu, J. et al. Establishment and molecular characterisation of patient-derived organoids for primary central nervous system lymphoma. Leukemia 39, 1169–1183 (2025). https://doi.org/10.1038/s41375-025-02562-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41375-025-02562-1

Search

Advanced search

Quick links