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Single-nucleus and spatial transcriptomics analyses reveal interplay between evolutionary dynamics and energy metabolism in primary cardiac lymphoma

Cancer Gene Therapy (2026) Cite this article

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Abstract

Primary cardiac lymphoma (PCL), a rare B-cell non-Hodgkin’s lymphoma, has shown a rising incidence, yet the lack of clarity regarding its molecular basis continues to hinder the development of effective targeted therapies. In this study, we utilized single-nucleus RNA sequencing and Visium CytAssist spatial transcriptomics in two patients with PCL to examine the metabolic and immune landscape of PCL. Our data implicate chromosomal instability (CIN) as a potential driver of disease progression, likely by modulating cellular sensitivity to metabolic stress. Single-cell analysis identified five distinct malignant B-cell states, including a B3 subset defined by subclonal diversification and enriched fatty acid metabolism-MAPK signaling. NFYA was also noted as a transcription factor potentially involved in this lipid reprogramming. Spatial observations suggest that B3 cells may contribute to an immunosuppressive microenvironment, with the CD44-LGALS9 axis acting as a possible mediator of endothelial cell remodeling and T-cell suppression. Ultimately, this study provides fresh insights into the clonal evolution and metabolic adaptations of PCL. These findings suggest that fatty acid metabolic reprogramming and CD44-LGALS9-mediated immune evasion play roles in tumor maintenance within the cardiac environment, offering a preliminary basis for future targeted therapeutic intervention.

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Fig. 1: Single-cell transcriptomic landscape of primary cardiac lymphoma (PCL).
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Fig. 2: Significant correlation between PCL tumor progression and subclonal evolution.
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Fig. 3: Identification of specific cellular subpopulations in two patients with PCL.
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Fig. 4: The B3 subpopulation promotes PCL progression via activation of the MAPK pathway through fatty acid metabolism.
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Fig. 5: Identification of NFYA as a key transcription factor in the B3 cell subset.
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Fig. 6: NFYA Expression and Fatty Acid Metabolism in B-Cell Subpopulations.
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Fig. 7: Spatial distribution of cell subpopulations and changes in cell-cell communication in two patients with PCL.
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Fig. 8: Changes in the immune microenvironment in two patients with PCL during subclonal progression.
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Data availability

The data are available from the corresponding author on reasonable request.

References

  1. Patel J, Melly L, Sheppard MN. Primary cardiac lymphoma: B- and T-cell cases at a specialist UK centre. Ann Oncol. 2010;21:1041–5.

    Article  CAS  PubMed  Google Scholar 

  2. Sultan I, Bianco V, Habertheuer A, Kilic A, Gleason TG, Aranda-Michel E, et al. Long-term outcomes of primary cardiac malignancies: multi-institutional results from the national cancer database. J Am Coll Cardiol. 2020;75:2338–47.

    Article  PubMed  Google Scholar 

  3. Jeudy J, Burke AP, Frazier AA. Cardiac lymphoma. Radio Clin North Am. 2016;54:689–710.

    Article  Google Scholar 

  4. Yin K, Brydges H, Lawrence KW, Wei Y, Karlson KJ, McAneny DB, et al. Primary cardiac lymphoma. J Thorac Cardiovasc Surg. 2022;164:573–80.

    Article  PubMed  Google Scholar 

  5. Xiong J, Zhao WL. Targetable metabolic vulnerability in diffuse large B-cell lymphoma. EBioMedicine. 2018;28:5–6.

    Article  PubMed  PubMed Central  Google Scholar 

  6. McGranahan N, Swanton C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell. 2015;27:15–26.

    Article  CAS  PubMed  Google Scholar 

  7. Zhou Y, Sun H, Xu Y. Metabolic reprogramming in cancer: the bridge that connects intracellular stresses and cancer behaviors. Natl Sci Rev. 2020;7:1270–3.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Zhu Y, Lin X, Zhou X, Prochownik EV, Wang F, Li Y. Posttranslational control of lipogenesis in the tumor microenvironment. J Hematol Oncol. 2022;15:120.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Hao JW, Wang J, Guo H, Zhao YY, Sun HH, Li YF, et al. CD36 facilitates fatty acid uptake by dynamic palmitoylation-regulated endocytosis. Nat Commun. 2020;11:4765.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Lopaschuk GD, Karwi QG, Tian R, Wende AR, Abel ED. Cardiac energy metabolism in heart failure. Circ Res. 2021;128:1487–513.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Koundouros N, Poulogiannis G. Reprogramming of fatty acid metabolism in cancer. Br J Cancer. 2020;122:4–22.

    Article  CAS  PubMed  Google Scholar 

  12. Cable DM, Murray E, Zou LS, Goeva A, Macosko EZ, Chen F, et al. Robust decomposition of cell type mixtures in spatial transcriptomics. Nat Biotechnol. 2022;40:517–26.

    Article  CAS  PubMed  Google Scholar 

  13. Weiler P, Lange M, Klein M, Pe’er D, Theis F. CellRank 2: unified fate mapping in multiview single-cell data. Nat Methods. 2024;21:1196–205.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Setty M, Kiseliovas V, Levine J, Gayoso A, Mazutis L, Pe’er D. Characterization of cell fate probabilities in single-cell data with Palantir. Nat Biotechnol. 2019;37:451–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Jia Q, Wang A, Yuan Y, Zhu B, Long H. Heterogeneity of the tumor immune microenvironment and its clinical relevance. Exp Hematol Oncol. 2022;11:24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Pham D, Tan X, Balderson B, Xu J, Grice LF, Yoon S, et al. Robust mapping of spatiotemporal trajectories and cell-cell interactions in healthy and diseased tissues. Nat Commun. 2023;14:7739.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Steen CB, Luca BA, Esfahani MS, Azizi A, Sworder BJ, Nabet BY, et al. The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma. Cancer Cell. 2021;39:1422–37.e10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Gulati GS, Sikandar SS, Wesche DJ, Manjunath A, Bharadwaj A, Berger MJ, et al. Single-cell transcriptional diversity is a hallmark of developmental potential. Science. 2020;367:405–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Gouw AM, Margulis K, Liu NS, Raman SJ, Mancuso A, Toal GG, et al. The MYC oncogene cooperates with sterol-regulated element-binding protein to regulate lipogenesis essential for neoplastic growth. Cell Metab. 2019;30:556–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Liu Y, Su Z, Tavana O, Gu W. Understanding the complexity of p53 in a new era of tumor suppression. Cancer Cell. 2024;42:946–67.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Cui M, Bezprozvannaya S, Hao T, Elnwasany A, Szweda LI, Liu N, et al. Transcription factor NFYa controls cardiomyocyte metabolism and proliferation during mouse fetal heart development. Dev Cell. 2023;58:2867–80.e7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Okada N, Ueki C, Shimazaki M, Tsujimoto G, Kohno S, Muranaka H, et al. NFYA promotes malignant behavior of triple-negative breast cancer in mice through the regulation of lipid metabolism. Commun Biol. 2023;6:596.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Petrich A, Cho SI, Billett H. Primary cardiac lymphoma: an analysis of presentation, treatment, and outcome patterns. Cancer. 2011;117:581–9.

    Article  PubMed  Google Scholar 

  24. Ma J, Wu Y, Ma L, Yang X, Zhang T, Song G, et al. A blueprint for tumor-infiltrating B cells across human cancers. Science. 2024;384:eadj4857.

    Article  CAS  PubMed  Google Scholar 

  25. Blenk S, Engelmann J, Weniger M, Schultz J, Dittrich M, Rosenwald A, et al. Germinal center B cell-like (GCB) and activated B cell-like (ABC) type of diffuse large B cell lymphoma (DLBCL): analysis of molecular predictors, signatures, cell cycle state and patient survival. Cancer Inf. 2007;3:399–420.

    CAS  Google Scholar 

  26. Akkaya M, Kwak K, Pierce SK. B cell memory: building two walls of protection against pathogens. Nat Rev Immunol. 2020;20:229–38.

    Article  CAS  PubMed  Google Scholar 

  27. Voravud N, Foster CS, Gilbertson JA, Sikora K, Waxman J. Oncogene expression in cholangiocarcinoma and in normal hepatic development. Hum Pathol. 1989;20:1163–8.

    Article  CAS  PubMed  Google Scholar 

  28. Li X, Liu X, Xu W, Zhou P, Gao P, Jiang S, et al. c-MYC-regulated miR-23a/24-2/27a cluster promotes mammary carcinoma cell invasion and hepatic metastasis by targeting Sprouty2. J Biol Chem. 2013;288:18121–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Zhao Y, Liu X, Si F, Huang L, Gao A, Lin W, et al. Citrate promotes excessive lipid biosynthesis and senescence in tumor cells for tumor therapy. Adv Sci. 2022;9:e2101553.

    Article  Google Scholar 

  30. Zhang Y, Zhao M, Gao H, Yu G, Zhao Y, Yao F, et al. MAPK signalling-induced phosphorylation and subcellular translocation of PDHE1alpha promotes tumour immune evasion. Nat Metab. 2022;4:374–88.

    Article  CAS  PubMed  Google Scholar 

  31. Dolfini D, Andrioletti V, Mantovani R. Overexpression and alternative splicing of NF-YA in breast cancer. Sci Rep. 2019;9:12955.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Gurtner A, Manni I, Piaggio G. NF-Y in cancer: Impact on cell transformation of a gene essential for proliferation. Biochim Biophys Acta Gene Regul Mech. 2017;1860:604–16.

    Article  CAS  PubMed  Google Scholar 

  33. Benatti P, Chiaramonte ML, Lorenzo M, Hartley JA, Hochhauser D, Gnesutta N, et al. NF-Y activates genes of metabolic pathways altered in cancer cells. Oncotarget. 2016;7:1633–50.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Magnes T, Wagner S, Thorner AR, Neureiter D, Klieser E, Rinnerthaler G, et al. Clonal evolution in diffuse large B-cell lymphoma with central nervous system recurrence. ESMO Open. 2021;6:100012.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Melchardt T, Hufnagl C, Weinstock DM, Kopp N, Neureiter D, Trankenschuh W, et al. Clonal evolution in relapsed and refractory diffuse large B-cell lymphoma is characterized by high dynamics of subclones. Oncotarget. 2016;7:51494–502.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Sharma A, Seow JJW, Dutertre CA, Pai R, Bleriot C, Mishra A, et al. Onco-fetal reprogramming of endothelial cells drives immunosuppressive macrophages in hepatocellular carcinoma. Cell. 2020;183:377–94.

    Article  CAS  PubMed  Google Scholar 

  37. Lv Y, Ma X, Ma Y, Du Y, Feng J. A new emerging target in cancer immunotherapy: galectin-9 (LGALS9). Genes Dis. 2023;10:2366–82.

    Article  CAS  PubMed  Google Scholar 

  38. Xiao ZJ, Wang SQ, Chen JJ, Li Y, Jiang Y, Tin VP, et al. The dual role of the NFATc2/galectin-9 Axis in modulating tumor-initiating cell phenotypes and immune suppression in lung adenocarcinoma. Adv Sci (Weinh). 2024;11:e2306059.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

Graphical abstract created with BioRender.com.

Funding

This work was supported by the grants from the National Natural Science Foundation of China (32270965).

Author information

Author notes

  1. These authors contributed equally: Xiaojuan Wei, Qianbing Zhang.

Authors and Affiliations

  1. Department of Lymphoma, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China

    Xiaojuan Wei, Sichu Liu, Xinmiao Jiang, Ling Huang & Wenyu Li

  2. Cancer Research Institute, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China

    Qianbing Zhang

  3. Department of Hematology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China

    Pengjun Liao

  4. Department of Pathology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China

    Su Yao

  5. PET Center, Department of Nuclear Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China

    Hui Yuan

  6. Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangzhou, China

    Kezhen Li

  7. Department of information technology, school of biomedical engineering, Southern Medical University, Guangzhou, China

    Liwei Hao

  8. Guangdong Lung Cancer Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China

    Sipei Wu

Authors
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Contributions

XJW and QBZ analyzed and organized the data; XJW wrote and revised this manuscript; PJL, SCL, XMJ, LH, SY, HY, and KZL generated the figure and tables. WYL, LWH, and SPW designed, revised and supervised the study. All authors reviewed and approved the final manuscript.

Corresponding authors

Correspondence to Wenyu Li, Liwei Hao or Sipei Wu.

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All authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

The collection of human samples and research protocols was approved by the Medical Research Ethics Committee of Guangdong Provincial People’s Hospital (Approval No: KY2024-757-01). Written informed consent was obtained from all patients prior to enrollment.

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Wei, X., Zhang, Q., Liao, P. et al. Single-nucleus and spatial transcriptomics analyses reveal interplay between evolutionary dynamics and energy metabolism in primary cardiac lymphoma. Cancer Gene Ther (2026). https://doi.org/10.1038/s41417-026-01031-w

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