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.

Advertisement

npj Precision Oncology
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. npj precision oncology
  3. articles
  4. article
Multimodal single-cell profiling reveals crosstalk between macrophages and stromal cells in poor prognostic cholangiocarcinoma patients
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 28 January 2026

Multimodal single-cell profiling reveals crosstalk between macrophages and stromal cells in poor prognostic cholangiocarcinoma patients

  • Lara Heij1,2,3,4 na1,
  • Sikander Hayat3,5 na1,
  • Konrad Reichel1,6,7 na1,
  • Sidrah Maryam3,
  • Colm J. O’Rourke8,
  • Xiuxiang Tan9,
  • Marlous van den Braber6,10,
  • Jan Verhoeff6,10,11,
  • Maurice Halder3,
  • Fabian Peisker3,
  • Georg Wiltberger9,12,
  • Jan Bednarsch1,
  • Daniel Heise1,
  • Julia Campello Deierl9,
  • Sven A. Lang1,
  • Florian Ulmer1,
  • Tom Luedde13,
  • Edgar Dahl14,15,
  • Danny Jonigk14,15,16,17,
  • Jochen Nolting1,
  • Shivan Sivakumar18,
  • Jens Siveke19,
  • Florian Vondran9,
  • Flavio G. Rocha20,
  • Hideo A. Baba2,
  • Sylvia Hartmann2,
  • Jesper B. Andersen8,
  • Zaynab Hobloss21,
  • Ahmed Ghallab21,22,
  • Jan G. Hengstler21,
  • Juan J. Garcia Vallejo6,10 na2,
  • Rafael Kramann3 na2 &
  • …
  • Ulf Neumann1,12 na2 

npj Precision Oncology , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Cancer
  • Computational biology and bioinformatics
  • Immunology
  • Oncology

Abstract

Cholangiocarcinoma (CCA) is a deadly cancer, characterized by abundant stroma. The tumor microenvironment (TME) plays an important role in its aggressive behavior and poor response to therapeutics; however, the underlying pathways are unknown. To fill this gap, we used multiplexed immunohistochemistry, high-dimensional cytometry, and single cell transcriptomics. Our findings confirm an abundance of regulatory T cells (Tregs) and a lack of effector memory T cells within the tumor. Tumor-infiltrating T cells show signs of exhaustion. Using our transcriptomic data, we revealed cellular crosstalk in poor prognosis patients. This crosstalk is driven by stromal cells and macrophages. Among the responsible receptor-ligand pairs are GAS6-AXL, VCAN-TLR2, and EGFR-TGF-β. The multiple mechanisms leading to the exclusion of relevant immune cells needed for an anti-cancer response and mechanisms leading to active immune suppression are part of complex cell-cell crosstalk. This study provides a deeper insight into the immune exhausted phenotype in CCA.

Similar content being viewed by others

Single-cell multi-omics uncovers CPS1 as a breast cancer immune evasion therapeutic target

Article Open access 16 October 2025

Characterisation of human in vitro tumour-associated macrophage models to define translational relevance

Article Open access 28 November 2025

Integrated analysis of single-cell and bulk RNA sequencing data reveals an immunostimulatory microenvironment in tumor thrombus of osteosarcoma

Article Open access 27 May 2023

Data availability

The code used in analyzing this data is available at https://github.com/hayatlab/cholangiocarcinoma_ici. The raw data generated in this study using single nuclei RNA-sequencing will be made available via the European Nucleotide Archive (ENA) under the accession code PRJEB97203. Bulk transcriptomic data was retrieved from the Gene Expression Omnibus (GEO) dataset GSE132305.

References

  1. Bertuccio, P. et al. Global trends in mortality from intrahepatic and extrahepatic cholangiocarcinoma. J. Hepatol. 71, 104–114 (2019).

    Google Scholar 

  2. Banales, J. M. et al. Cholangiocarcinoma 2020: the next horizon in mechanisms and management. Nat. Rev. Gastroenterol. Hepatol. 17, 557–588 (2020).

    Google Scholar 

  3. Goeppert, B. [Cholangiocarcinoma-diagnosis, classification, and molecular alterations]. Pathologe 41, 488–494 (2020).

    Google Scholar 

  4. Bagante, F. et al. Assessment of the lymph node status in patients undergoing liver resection for intrahepatic cholangiocarcinoma: the New Eighth Edition AJCC staging system. J. Gastrointest. Surg. 22, 52–59 (2018).

    Google Scholar 

  5. Zhou, G. et al. Reduction of immunosuppressive tumor microenvironment in cholangiocarcinoma by ex vivo targeting immune checkpoint molecules. J. Hepatol. 71, 753–762 (2019).

    Google Scholar 

  6. Bednarsch, J. et al. The presence of small nerve fibers in the tumor microenvironment as predictive biomarker of oncological outcome following partial hepatectomy for intrahepatic cholangiocarcinoma. Cancers 13, 3661 (2021).

    Google Scholar 

  7. Bednarsch, J. et al. Nerve fibers in the tumor microenvironment as a novel biomarker for oncological outcome in patients undergoing surgery for perihilar cholangiocarcinoma. Liver Cancer 10, 260–274 (2021).

    Google Scholar 

  8. Loeuillard, E., Conboy, C. B., Gores, G. J. & Rizvi, S. Immunobiology of cholangiocarcinoma. JHEP Rep. Innov. Hepatol. 1, 297–311 (2019).

    Google Scholar 

  9. Fabris, L., Sato, K., Alpini, G. & Strazzabosco, M. The tumor microenvironment in cholangiocarcinoma progression. Hepatology 73, 75–85 (2021).

    Google Scholar 

  10. Fabris, L. et al. The tumour microenvironment and immune milieu of cholangiocarcinoma. Liver Int. 39, 63–78 (2019).

    Google Scholar 

  11. Alvisi, G. et al. Multimodal single-cell profiling of intrahepatic cholangiocarcinoma defines hyperactivated Tregs as a potential therapeutic target. J. Hepatol. 77, 1359–1372 (2022).

    Google Scholar 

  12. Zhang, M. et al. Single-cell transcriptomic architecture and intercellular crosstalk of human intrahepatic cholangiocarcinoma. J. Hepatol. 73, 1118–1130 (2020).

    Google Scholar 

  13. Clark, C. E. et al. Dynamics of the immune reaction to pancreatic cancer from inception to invasion. Cancer Res. 67, 9518–9527 (2007).

    Google Scholar 

  14. Kasper, H. U., Drebber, U., Stippel, D. L., Dienes, H. P. & Gillessen, A. Liver tumor infiltrating lymphocytes: comparison of hepatocellular and cholangiolar carcinoma. World J. Gastroenterol. 15, 5053–5057 (2009).

    Google Scholar 

  15. Asahi, Y. et al. Prognostic impact of CD8+ T cell distribution and its association with the HLA class I expression in intrahepatic cholangiocarcinoma. Surg. Today 50, 931–940 (2020).

    Google Scholar 

  16. Konduri, V. et al. CD8(+)CD161(+) T-Cells: cytotoxic memory cells with high therapeutic potential. Front. Immunol. 11, 613204 (2020).

    Google Scholar 

  17. Li, Z. et al. The identification and functional analysis of CD8+PD-1+CD161+ T cells in hepatocellular carcinoma. NPJ Precis. Oncol. 4, 28 (2020).

    Google Scholar 

  18. Zhou, X. et al. A pan-cancer analysis of CD161, a potential new immune checkpoint. Front. Immunol. 12, 688215 (2021).

    Google Scholar 

  19. Tian, L. et al. PD-1/PD-L1 expression profiles within intrahepatic cholangiocarcinoma predict clinical outcome. World J. Surg. Oncol. 18, 303 (2020).

    Google Scholar 

  20. Ma, L. et al. Single-cell atlas of tumor cell evolution in response to therapy in hepatocellular carcinoma and intrahepatic cholangiocarcinoma. J. Hepatol. 75, 1397–1408 (2021).

    Google Scholar 

  21. Zhou, M. et al. Tumor-associated macrophages in cholangiocarcinoma: complex interplay and potential therapeutic target. EBioMedicine 67, 103375 (2021).

    Google Scholar 

  22. Hasita, H. et al. Significance of alternatively activated macrophages in patients with intrahepatic cholangiocarcinoma. Cancer Sci. 101, 1913–1919 (2010).

    Google Scholar 

  23. Atanasov, G. et al. Tumor necrosis and infiltrating macrophages predict survival after curative resection for cholangiocarcinoma. Oncoimmunology 6, e1331806 (2017).

    Google Scholar 

  24. Sun, D. et al. CD86(+)/CD206(+) tumor-associated macrophages predict prognosis of patients with intrahepatic cholangiocarcinoma. PeerJ 8, e8458 (2020).

    Google Scholar 

  25. Loeuillard, E. et al. Targeting tumor-associated macrophages and granulocytic myeloid-derived suppressor cells augments PD-1 blockade in cholangiocarcinoma. J. Clin. Investig. 130, 5380–5396 (2020).

    Google Scholar 

  26. Tauriello, D. V. F. et al. TGFbeta drives immune evasion in genetically reconstituted colon cancer metastasis. Nature 554, 538–543 (2018).

    Google Scholar 

  27. Kalluri, R. The biology and function of fibroblasts in cancer. Nat. Rev. Cancer 16, 582–598 (2016).

    Google Scholar 

  28. Huang, B. et al. CD8(+)CD57(+) T cells exhibit distinct features in human non-small cell lung cancer. J Immunother Cancer 8, e000639 (2020).

    Google Scholar 

  29. Strioga, M., Pasukoniene, V. & Characiejus, D. CD8+ CD28- and CD8+ CD57+ T cells and their role in health and disease. Immunology 134, 17–32 (2011).

    Google Scholar 

  30. Ohue, Y. & Nishikawa, H. Regulatory T (Treg) cells in cancer: can Treg cells be a new therapeutic target? Cancer Sci. 110, 2080–2089 (2019).

    Google Scholar 

  31. Flippe, L., Bezie, S., Anegon, I. & Guillonneau, C. Future prospects for CD8(+) regulatory T cells in immune tolerance. Immunol. Rev. 292, 209–224 (2019).

    Google Scholar 

  32. Chaput, N. et al. Identification of CD8+CD25+Foxp3+ suppressive T cells in colorectal cancer tissue. Gut 58, 520–529 (2009).

    Google Scholar 

  33. Jusakul, A. et al. Whole-genome and epigenomic landscapes of etiologically distinct subtypes of cholangiocarcinoma. Cancer Discov. 7, 1116–1135 (2017).

    Google Scholar 

  34. Nagai, J. S., Leimkühler, N. B., Schaub, M. T., Schneider, R. K. & Costa, I. G. CrossTalkeR: analysis and visualization of ligand–receptorne tworks. Bioinformatics 37, 4263–4265 (2021).

    Google Scholar 

  35. Papadas, A., Arauz, G., Cicala, A., Wiesner, J. & Asimakopoulos, F. Versican and versican-matrikines in cancer progression, inflammation, and immunity. J. Histochem. Cytochem. 68, 871–885 (2020).

    Google Scholar 

  36. Yang, L., Pang, Y. & Moses, H. L. TGF-beta and immune cells: an important regulatory axis in the tumor microenvironment and progression. Trends Immunol. 31, 220–227 (2010).

    Google Scholar 

  37. Montal, R. et al. Molecular classification and therapeutic targets in extrahepatic cholangiocarcinoma. J. Hepatol. 73, 315–327 (2020).

    Google Scholar 

  38. Newman, A. M. et al. Determining cell type abundance and expression from bulk tissues with digital cytometry. Nat. Biotechnol. 37, 773–782 (2019).

    Google Scholar 

  39. Rizvi, S., Khan, S. A., Hallemeier, C. L., Kelley, R. K. & Gores, G. J. Cholangiocarcinoma - evolving concepts and therapeutic strategies. Nat. Rev. Clin. Oncol. 15, 95–111 (2018).

    Google Scholar 

  40. Tumeh, P. C. et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515, 568–571 (2014).

    Google Scholar 

  41. Carapeto, F. et al. The immunogenomic landscape of resected intrahepatic cholangiocarcinoma. Hepatology 75, 297–308 (2021).

    Google Scholar 

  42. Goeppert, B. et al. Prognostic impact of tumour-infiltrating immune cells on biliary tract cancer. Br. J. Cancer 109, 2665–2674 (2013).

    Google Scholar 

  43. Kitano, Y. et al. Tumour-infiltrating inflammatory and immune cells in patients with extrahepatic cholangiocarcinoma. Br. J. Cancer 118, 171–180 (2018).

    Google Scholar 

  44. Zhu, J. et al. Increased CD4(+) CD69(+) CD25(-) T cells in patients with hepatocellular carcinoma are associated with tumor progression. J. Gastroenterol. Hepatol. 26, 1519–1526 (2011).

    Google Scholar 

  45. Gonzalez-Amaro, R., Cortes, J. R., Sanchez-Madrid, F. & Martin, P. Is CD69 an effective brake to control inflammatory diseases?. Trends Mol. Med. 19, 625–632 (2013).

    Google Scholar 

  46. Gutiérrez-Larrañaga, M. et al. Immune checkpoint inhibitors: the emerging cornerstone in cholangiocarcinoma therapy?. Liver Cancer 10, 545–560 (2021).

    Google Scholar 

  47. Okabe, H. et al. Hepatic stellate cells may relate to progression of intrahepatic cholangiocarcinoma. Ann. Surg. Oncol. 16, 2555–2564 (2009).

    Google Scholar 

  48. O'Rourke, C. J. et al. Molecular portraits of patients with intrahepatic cholangiocarcinoma who diverge as rapid progressors or long survivors on chemotherapy. Gut 73, 496–508 (2023).

    Google Scholar 

  49. Horie, S., Endo, K., Kawasaki, H. & Terada, T. Overexpression of MDM2 protein in intrahepatic cholangiocarcinoma: relationship with p53 overexpression, Ki-67 labeling, and clinicopathological features. Virchows Arch. 437, 25–30 (2000).

    Google Scholar 

  50. Wattanawongdon, W., Simawaranon Bartpho, T. & Tongtawee, T. Expression of CD44 and MDM2 in cholangiocarcinoma is correlated with poor clinicopathologic characteristics. Int. J. Clin. Exp. Pathol. 12, 3961–3967 (2019).

    Google Scholar 

  51. Liu, P. et al. High expression of PTPRM predicts poor prognosis and promotes tumor growth and lymph node metastasis in cervical cancer. Cell Death Dis. 11, 687 (2020).

    Google Scholar 

  52. Wu, G. et al. Molecular insights of Gas6/TAM in cancer development and therapy. Cell Death Dis. 8, e2700 (2017).

    Google Scholar 

  53. Ishikawa, M. et al. Higher expression of receptor tyrosine kinase Axl, and differential expression of its ligand, Gas6, predict poor survival in lung adenocarcinoma patients. Ann. Surg. Oncol. 20, S467–S476 (2013).

    Google Scholar 

  54. Yang, F. et al. Interaction with CD68 and Regulation of GAS6 expression by Endosialin in Fibroblasts drives recruitment and polarization of macrophages in hepatocellular carcinoma. Cancer Res. 80, 3892–3905 (2020).

    Google Scholar 

  55. Kasikara, C. et al. Phosphatidylserine sensing by TAM receptors regulates AKT-dependent chemoresistance and PD-L1 expression. Mol. Cancer Res. 15, 753–764 (2017).

    Google Scholar 

  56. Tsukita, Y. et al. Axl kinase drives immune checkpoint and chemokine signalling pathways in lung adenocarcinomas. Mol. Cancer 18, 24 (2019).

    Google Scholar 

  57. Hope, C. et al. Immunoregulatory roles of versican proteolysis in the myeloma microenvironment. Blood 128, 680–685 (2016).

    Google Scholar 

  58. Kim, S. et al. Carcinoma-produced factors activate myeloid cells through TLR2 to stimulate metastasis. Nature 457, 102–106 (2009).

    Google Scholar 

  59. Du, W. W. et al. The role of versican in modulating breast cancer cell self-renewal. Mol. Cancer Res. 11, 443–455 (2013).

    Google Scholar 

  60. Yoshikawa, D. et al. Clinicopathological and prognostic significance of EGFR, VEGF, and HER2 expression in cholangiocarcinoma. Br. J. Cancer 98, 418–425 (2008).

    Google Scholar 

  61. Song, J., Wei, R., Huo, S., Liu, C. & Liu, X. Versican enrichment predicts poor prognosis and response to adjuvant therapy and immunotherapy in gastric cancer. Front. Immunol. 13, 960570 (2022).

    Google Scholar 

  62. Xiang, X., Wang, J., Lu, D. & Xu, X. Targeting tumor-associated macrophages to synergize tumor immunotherapy. Signal Transduct. Target Ther. 6, 75 (2021).

    Google Scholar 

  63. Fan, Q. M. et al. Tumor-associated macrophages promote cancer stem cell-like properties via transforming growth factor-beta1-induced epithelial-mesenchymal transition in hepatocellular carcinoma. Cancer Lett. 352, 160–168 (2014).

    Google Scholar 

  64. Thomas, D. A. & Massague, J. TGF-beta directly targets cytotoxic T cell functions during tumor evasion of immune surveillance. Cancer Cell 8, 369–380 (2005).

    Google Scholar 

  65. Sivakumar, S. et al. Activated regulatory T-Cells, dysfunctional and senescent T-Cells hinder the immunity in pancreatic cancer. Cancers 13, 1776 (2021).

    Google Scholar 

  66. Van Gassen, S., Gaudilliere, B., Angst, M. S., Saeys, Y. & Aghaeepour, N. CytoNorm: a normalization algorithm for cytometry data. Cytom. A 97, 268–278 (2020).

    Google Scholar 

  67. Van Gassen, S. et al. FlowSOM: using self-organizing maps for visualization and interpretation of cytometry data. Cytom. A 87, 636–645 (2015).

    Google Scholar 

  68. Levine, J. H. et al. Data-driven phenotypic dissection of aml reveals progenitor-like cells that correlate with prognosis. Cell 162, 184–197 (2015).

    Google Scholar 

  69. Tan, X. et al. PD-1. T-cells correlate with nerve fiber density as a prognostic biomarker in patients with resected perihilar cholangiocarcinoma. Cancers 14, 2190 (2022).

    Google Scholar 

  70. Habib, N. et al. Massively parallel single-nucleus RNA-seq with DroNc-seq. Nat. Methods 14, 955–958 (2017).

    Google Scholar 

  71. Ghallab, A. et al. Inhibition of the renal apical sodium dependent bile acid transporter prevents cholemic nephropathy in mice with obstructive cholestasis. J. Hepatol. 80, 268–281 (2024).

    Google Scholar 

  72. Ghallab, A. et al. Spatio-temporal multiscale analysis of western diet-fed mice reveals a translationally relevant sequence of events during NAFLD progression. Cells 10, 2516 (2021).

    Google Scholar 

Download references

Acknowledgements

This study was funded by Deutsche Forschungsgesellschaft (DFG, German Research Foundation) – Project ID 403224013 – SFB 1382 (UN and TL). This research project was supported by the START Program of the Faculty of Medicine of the RWTH Aachen University, Project ID 19/23 (LH).

Funding

Open Access funding enabled and organized by Projekt DEAL.

Author information

Author notes
  1. These authors contributed equally: Lara Heij, Sikander Hayat, Konrad Reichel.

  2. These authors jointly supervised this work: Juan J. Garcia Vallejo, Rafael Kramann, Ulf Neumann.

Authors and Affiliations

  1. Department of Surgery and Transplantation, University Hospital Essen, Essen, Germany

    Lara Heij, Konrad Reichel, Jan Bednarsch, Daniel Heise, Sven A. Lang, Florian Ulmer, Jochen Nolting & Ulf Neumann

  2. Department of Pathology, University Hospital Essen, Essen, Germany

    Lara Heij, Hideo A. Baba & Sylvia Hartmann

  3. Department of Renal and Hypertensive Disorders, Rheumatological and Immunological Diseases (Medical Clinic II), Medical Faculty, RWTH Aachen University, Aachen, Germany

    Lara Heij, Sikander Hayat, Sidrah Maryam, Maurice Halder, Fabian Peisker & Rafael Kramann

  4. Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Roterdam, The Netherlands

    Lara Heij

  5. Cardiovascular Research Institute and Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, USA

    Sikander Hayat

  6. Amsterdam UMC – Location Vrije Universiteit Amsterdam, Molecular Cell Biology & Immunology, Amsterdam, The Netherlands

    Konrad Reichel, Marlous van den Braber, Jan Verhoeff & Juan J. Garcia Vallejo

  7. NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands

    Konrad Reichel

  8. Department of Health and Medical Sciences, Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark

    Colm J. O’Rourke & Jesper B. Andersen

  9. Department of Surgery and Transplantation, University Hospital RWTH Aachen, Aachen, Germany

    Xiuxiang Tan, Georg Wiltberger, Julia Campello Deierl & Florian Vondran

  10. Amsterdam Infection & Immunity, Cancer Immunology, Amsterdam, The Netherlands

    Marlous van den Braber, Jan Verhoeff & Juan J. Garcia Vallejo

  11. Tytgat Institute for Liver and Intestinal Research, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands

    Jan Verhoeff

  12. Department of Surgery, Maastricht University Medical Center (MUMC), Maastricht, The Netherlands

    Georg Wiltberger & Ulf Neumann

  13. Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital Duesseldorf, Düsseldorf, Germany

    Tom Luedde

  14. Institute of Pathology, University Hospital RWTH Aachen, Aachen, Germany

    Edgar Dahl & Danny Jonigk

  15. Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), Aachen, Germany

    Edgar Dahl & Danny Jonigk

  16. Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), German Center for Lung Research (DZL), Hannover, Germany

    Danny Jonigk

  17. Institute of Pathology, Hannover Medical School, Hannover, Germany

    Danny Jonigk

  18. University of Birmingham and University hospitals of Birmingham NHS Trust, Birmingham, UK

    Shivan Sivakumar

  19. Bridge Institute of Experimental Tumor Therapy, West German Cancer Center, University Hospital Essen, University Duisburg-Essen, Essen, Germany

    Jens Siveke

  20. Division of Surgical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, OR, USA

    Flavio G. Rocha

  21. Department of Toxicology, Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany

    Zaynab Hobloss, Ahmed Ghallab & Jan G. Hengstler

  22. Department of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt

    Ahmed Ghallab

Authors
  1. Lara Heij
    View author publications

    Search author on:PubMed Google Scholar

  2. Sikander Hayat
    View author publications

    Search author on:PubMed Google Scholar

  3. Konrad Reichel
    View author publications

    Search author on:PubMed Google Scholar

  4. Sidrah Maryam
    View author publications

    Search author on:PubMed Google Scholar

  5. Colm J. O’Rourke
    View author publications

    Search author on:PubMed Google Scholar

  6. Xiuxiang Tan
    View author publications

    Search author on:PubMed Google Scholar

  7. Marlous van den Braber
    View author publications

    Search author on:PubMed Google Scholar

  8. Jan Verhoeff
    View author publications

    Search author on:PubMed Google Scholar

  9. Maurice Halder
    View author publications

    Search author on:PubMed Google Scholar

  10. Fabian Peisker
    View author publications

    Search author on:PubMed Google Scholar

  11. Georg Wiltberger
    View author publications

    Search author on:PubMed Google Scholar

  12. Jan Bednarsch
    View author publications

    Search author on:PubMed Google Scholar

  13. Daniel Heise
    View author publications

    Search author on:PubMed Google Scholar

  14. Julia Campello Deierl
    View author publications

    Search author on:PubMed Google Scholar

  15. Sven A. Lang
    View author publications

    Search author on:PubMed Google Scholar

  16. Florian Ulmer
    View author publications

    Search author on:PubMed Google Scholar

  17. Tom Luedde
    View author publications

    Search author on:PubMed Google Scholar

  18. Edgar Dahl
    View author publications

    Search author on:PubMed Google Scholar

  19. Danny Jonigk
    View author publications

    Search author on:PubMed Google Scholar

  20. Jochen Nolting
    View author publications

    Search author on:PubMed Google Scholar

  21. Shivan Sivakumar
    View author publications

    Search author on:PubMed Google Scholar

  22. Jens Siveke
    View author publications

    Search author on:PubMed Google Scholar

  23. Florian Vondran
    View author publications

    Search author on:PubMed Google Scholar

  24. Flavio G. Rocha
    View author publications

    Search author on:PubMed Google Scholar

  25. Hideo A. Baba
    View author publications

    Search author on:PubMed Google Scholar

  26. Sylvia Hartmann
    View author publications

    Search author on:PubMed Google Scholar

  27. Jesper B. Andersen
    View author publications

    Search author on:PubMed Google Scholar

  28. Zaynab Hobloss
    View author publications

    Search author on:PubMed Google Scholar

  29. Ahmed Ghallab
    View author publications

    Search author on:PubMed Google Scholar

  30. Jan G. Hengstler
    View author publications

    Search author on:PubMed Google Scholar

  31. Juan J. Garcia Vallejo
    View author publications

    Search author on:PubMed Google Scholar

  32. Rafael Kramann
    View author publications

    Search author on:PubMed Google Scholar

  33. Ulf Neumann
    View author publications

    Search author on:PubMed Google Scholar

Contributions

L.H., Si.H., K.R., J.J.G.V., R.K., and U.N. designed this study. S.L., F.U., X.T., G.W., J.B., M.B., F.P., D.H., J.N., J.V., Z.H.,. A.G., and M.H. contributed to sample collection and processing. L.H., Si.H,. K.R., S.M., C.R., Z.H., A.G., J.H., and J.J.G.V. were responsible for data analysis and interpretation. L.H., D.J., and H.B. provided histological expertise. L.H., Si.H., S.M., R.K., J.A., J.D., and C.R. performed statistical analysis and interpretation. L.H., Si.H., S.S., F.R., J.J.G.V., J.A., C.R., and K.R. contributed to the first draft of this manuscript. U.N., R.K., S.S., T.L., D.J., E.D., J.S., H.B., J.H., Sy.H., and J.J.G.V. provided the infrastructure and supervised the study. All authors contributed to the data analysis and manuscript writing.

Corresponding author

Correspondence to Lara Heij.

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

Supplementary information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Heij, L., Hayat, S., Reichel, K. et al. Multimodal single-cell profiling reveals crosstalk between macrophages and stromal cells in poor prognostic cholangiocarcinoma patients. npj Precis. Onc. (2026). https://doi.org/10.1038/s41698-026-01292-6

Download citation

  • Received: 18 September 2025

  • Accepted: 16 January 2026

  • Published: 28 January 2026

  • DOI: https://doi.org/10.1038/s41698-026-01292-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Download PDF

Advertisement

Explore content

  • Research articles
  • Reviews & Analysis
  • News & Comment
  • Collections
  • Follow us on Twitter
  • Sign up for alerts
  • RSS feed

About the journal

  • Aims & Scope
  • Content types
  • Journal Information
  • Open Access
  • About the Editors
  • Contact
  • Calls for Papers
  • Editorial policies
  • Journal Metrics
  • About the Partner

Publish with us

  • For Authors and Referees
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

npj Precision Oncology (npj Precis. Onc.)

ISSN 2397-768X (online)

nature.com sitemap

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer