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Fibroblast-derived prolargin is a tumor suppressor in hepatocellular carcinoma

Oncogene volume 41, pages 1410–1420 (2022)Cite this article

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Abstract

Cancer-associated fibroblasts (CAF) are important constituents of the tumor microenvironment (TME) and are major drivers of tumorigenesis. Yet, therapies aiming at eliminating CAF have failed to cure patients. This setback has raised questions regarding whether CAF exclusively favour cancer progression, or if they may also assume tumor-suppressor functions. In the present study, we used proteomics and single cell RNA-sequencing analysis to examine the CAF landscape in hepatocellular carcinoma (HCC). We thereby unveil three major CAF populations in HCC, one of which specifically expressing the prolargin protein. This CAF subpopulation (further termed as CAF_Port) shared a strong transcriptomic signature with portal liver fibroblasts. We further show that CAF_Port deposit prolargin in the TME and that its levels are lower in tumors as compared to the peritumoral region. Mechanistically, aggressive cancer cells degraded prolargin using matrix metalloprotease activity. Survival analysis of 188 patients revealed that high prolargin protein levels correlate with good patient outcome (HR = 0.37; p = 0.01). In vivo, co-injection of cancer cells with fibroblasts silenced for prolargin, led to faster tumor development (5-fold; p = 0.01), mainly due to stronger angiogenesis. Using protein-protein interaction study and structural modelling, we further demonstrate that prolargin binds and inhibits the activity of several pro-agiogenic proteins, including hepatocyte and fibroblast growth factors. In conclusion, prolargin is angiogenesis modulator and CAF-derived tumor suppressor in HCC. Stabilizing prolargin levels in the CAF_Port subpopulation may revert their tumor-antagonizing properties, warranting exploration in further pre-clinical studies.

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Fig. 1: Prolargin is expressed by CAF deriving from portal fibroblasts.
Fig. 2: Extracellular prolargin levels depend on cancer cell MMP1 and MMP3 expression.
Fig. 3: Prolargin inhibits tumor growth by suppressing angiogenesis.
Fig. 4: Prolargin binds pro-angiogenic growth factors and inhibits their activity.
Fig. 5: Combination of MMP inhibitor batimastat with sorafenib results in strong tumor control of HCC.

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References

  1. El-Serag HB, Rudolph KL. Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology. 2007;132:2557–76.

    Article  CAS  PubMed  Google Scholar 

  2. Wong MC, Jiang JY, Goggins WB, Liang M, Fang Y, Fung FDH, et al. International incidence and mortality trends of liver cancer: a global profile. Sci Rep. 2017;7:45846.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Altekruse SF, McGlynn KA, Reichman ME. Hepatocellular carcinoma incidence, mortality, and survival trends in the United States from 1975 to 2005. J Clin Oncol. 2009;27:1485–91.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Morse MA, Sun W, Kim R, He AR, Abada PB, Mynderse M, et al. The Role of Angiogenesis in Hepatocellular Carcinoma. Clin Cancer Res. 2019;25:912–20.

    Article  CAS  PubMed  Google Scholar 

  5. Llovet JM, Ricci S, Mazzaferro V, Hilgard P, Gane E, Blanc JF, et al. Sorafenib in advanced hepatocellular carcinoma. N. Engl J Med. 2008;359:378–90.

    Article  CAS  PubMed  Google Scholar 

  6. Finn RS, Qin S, Ikeda M, Galle PR, Ducreux M, Kim TY, et al. Atezolizumab plus Bevacizumab in Unresectable Hepatocellular Carcinoma. N. Engl J Med. 2020;382:1894–905.

    Article  CAS  PubMed  Google Scholar 

  7. Voron T, Colussi O, Marcheteau E, Pernot S, Nizard M, Pointet AL, et al. VEGF-A modulates expression of inhibitory checkpoints on CD8+ T cells in tumors. J Exp Med. 2015;212:139–48.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Quail DF, Joyce JA. Microenvironmental regulation of tumor progression and metastasis. Nat Med. 2013;19:1423–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Ronca R, Van Ginderachter JA, Turtoi A. Paracrine interactions of cancer-associated fibroblasts, macrophages and endothelial cells: Tumor allies and foes. Curr Opin Oncol. 2018;30:45–53.

    Article  CAS  PubMed  Google Scholar 

  10. Chiavarina B, Turtoi A. Collaborative and defensive fibroblasts in tumor progression and therapy resistance. Curr Med Chem. 2017;24:2846–59.

    Article  CAS  PubMed  Google Scholar 

  11. Olive KP, Jacobetz MA, Davidson CJ, Gopinathan A, McIntyre D, Honess D, et al. Inhibition of Hedgehog signaling enhances delivery of chemotherapy in a mouse model of pancreatic cancer. Science. 2009;324:1457–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Provenzano PP, Cuevas C, Chang AE, Goel VK, Von Hoff DD, Hingorani SR. Enzymatic targeting of the stroma ablates physical barriers to treatment of pancreatic ductal adenocarcinoma. Cancer Cell. 2012;21:418–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Catenacci DV, Junttila MR, Karrison T, Bahary N, Horiba MN, Nattam SR, et al. Randomized Phase Ib/II Study of Gemcitabine Plus Placebo or Vismodegib, a Hedgehog pathway inhibitor, in patients with metastatic pancreatic cancer. J Clin Oncol. 2015;33:4284–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ozdemir BC, Pentcheva-Hoang T, Carstens JL, Zheng X, Wu CC, Simpson TR, et al. Depletion of carcinoma-associated fibroblasts and fibrosis induces immunosuppression and accelerates pancreas cancer with reduced survival. Cancer Cell. 2014;25:719–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Rhim AD, Oberstein PE, Thomas DH, Mirek ET, Palermo CF, Sastra SA, et al. Stromal elements act to restrain, rather than support, pancreatic ductal adenocarcinoma. Cancer Cell. 2014;25:735–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Dolberg DS, Bissell MJ. Inability of Rous sarcoma virus to cause sarcomas in the avian embryo. Nature. 1984;309:552–6.

    Article  CAS  PubMed  Google Scholar 

  17. Dotto GP, Weinberg RA, Ariza A. Malignant transformation of mouse primary keratinocytes by Harvey sarcoma virus and its modulation by surrounding normal cells. Proc Natl Acad Sci USA. 1988;85:6389–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Bissell MJ, Hines WC. Why don’t we get more cancer? A proposed role of the microenvironment in restraining cancer progression. Nat Med. 2011;17:320–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Froeling FE, Feig C, Chelala C, Dobson R, Mein CE, Tuveson DA, et al. Retinoic acid-induced pancreatic stellate cell quiescence reduces paracrine Wnt-beta-catenin signaling to slow tumor progression. Gastroenterology. 2011;141:1486–97. 1497 e1–14.

    Article  CAS  PubMed  Google Scholar 

  20. Sherman MH, Yu RT, Engle DD, Ding N, Atkins AR, Tiriac H, et al. Vitamin D receptor-mediated stromal reprogramming suppresses pancreatitis and enhances pancreatic cancer therapy. Cell. 2014;159:80–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Ohlund D, Handly-Santana A, Biffi G, Elyada E, Almeida AS, Ponz-Sarvise M, et al. Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer. J Exp Med. 2017;214:579–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Costa A, Kieffer Y, Scholer-Dahirel A, Pelon F, Bourachot B, Cardon M, et al. Fibroblast heterogeneity and immunosuppressive environment in human breast cancer. Cancer Cell. 2018;33:463–79 e10.

    Article  CAS  PubMed  Google Scholar 

  23. Su S, Chen J, Yao H, Liu J, Yu S, Lao L, et al. CD10(+)GPR77(+) cancer-associated fibroblasts promote cancer formation and chemoresistance by sustaining cancer stemness. Cell. 2018;172:841–56 e16.

    Article  CAS  PubMed  Google Scholar 

  24. Chang PH, Hwang-Verslues WW, Chang YC, Chen CC, Hsiao M, Jeng YM, et al. Activation of Robo1 signaling of breast cancer cells by Slit2 from stromal fibroblast restrains tumorigenesis via blocking PI3K/Akt/beta-catenin pathway. Cancer Res. 2012;72:4652–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. DeFilippis RA, Chang H, Dumont N, Rabban JT, Chen YY, Fontenay GV, et al. CD36 repression activates a multicellular stromal program shared by high mammographic density and tumor tissues. Cancer Disco. 2012;2:826–39.

    Article  CAS  Google Scholar 

  26. Neill T, Schaefer L, Iozzo RV. Decorin: A guardian from the matrix. Am J Pathol. 2012;181:380–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Maris P, Blomme A, Palacios AP, Costanza B, Bellahcène A, Bianchi E, et al. Asporin Is a Fibroblast-Derived TGF-beta1 inhibitor and a tumor suppressor associated with good prognosis in breast cancer. PLoS Med. 2015;12:e1001871.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Turtoi A, Dumont B, Greffe Y, Blomme A, Mazzucchelli G, Delvenne P, et al. Novel comprehensive approach for accessible biomarker identification and absolute quantification from precious human tissues. J Proteome Res. 2011;10:3160–82.

    Article  CAS  PubMed  Google Scholar 

  29. Turtoi A, De Pauw E, Castronovo V. Innovative proteomics for the discovery of systemically accessible cancer biomarkers suitable for imaging and targeted therapies. Am J Pathol. 2011;178:12–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Ma L, Hernandez MO, Zhao Y, Mehta M, Tran B, Kelly M, et al. Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer. Cancer Cell. 2019;36:418–.e6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Dobie R, Wilson-Kanamori JR, Henderson BEP, Smith JR, Matchett KP, Portman JR, et al. Single-cell transcriptomics uncovers zonation of function in the mesenchyme during liver fibrosis. Cell Rep. 2019;29:1832–.e8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Cabello-Aguilar S, Alame M, Kon-Sun-Tack F, Fau C, Lacroix M, Colinge J. SingleCellSignalR: Inference of intercellular networks from single-cell transcriptomics. Nucleic Acids Res. 2020;48:e55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Lawrence MC, Colman PM. Shape complementarity at protein/protein interfaces. J Mol Biol. 1993;234:946–50.

    Article  CAS  PubMed  Google Scholar 

  34. Rämisch S, Weininger U, Martinsson J, Akke M, André I. Computational design of a leucine-rich repeat protein with a predefined geometry. Proc Natl Acad Sci USA. 2014;111:17875–80.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Adnane L, Trail PA, Taylor I, Wilhelm SM. Sorafenib (BAY 43-9006, Nexavar), A dual-action inhibitor that targets RAF/MEK/ERK pathway in tumor cells and tyrosine kinases VEGFR/PDGFR in tumor vasculature. Meth Enzymol. 2006;407:597–612.

    Article  CAS  Google Scholar 

  36. Wilhelm SM, Adnane L, Newell P, Villanueva A, Llovet JM, Lynch M. Preclinical overview of sorafenib, a multikinase inhibitor that targets both Raf and VEGF and PDGF receptor tyrosine kinase signaling. Mol Cancer Ther. 2008;7:3129–40.

    Article  CAS  PubMed  Google Scholar 

  37. Hwang RF, Moore T, Arumugam T, Ramachandran V, Amos KD, Rivera A, et al. Cancer-associated stromal fibroblasts promote pancreatic tumor progression. Cancer Res. 2008;68:918–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Orimo A, Weinberg RA. Heterogeneity of stromal fibroblasts in tumors. Cancer Biol Ther. 2007;6:618–9.

    Article  CAS  PubMed  Google Scholar 

  39. Li H, Courtois ET, Sengupta D, Tan Y, Chen KH, Goh JJL, et al. Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors. Nat Genet. 2017;49:708–18.

    Article  CAS  PubMed  Google Scholar 

  40. Winer A, Adams S, Mignatti P. Matrix metalloproteinase inhibitors in cancer therapy: Turning past failures into future successes. Mol Cancer Ther. 2018;17:1147–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Fields GB. Mechanisms of action of novel drugs targeting angiogenesis-promoting matrix metalloproteinases. Front Immunol. 2019;10:1278.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Stuart T, Butler A, Hoffman P, Hafemeister C, Papalexi E, Mauck WM 3rd, et al. Comprehensive Integration of Single-Cell Data. Cell. 2019;177:1888–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Waltregny D, Bellahcene A, Van Riet I, Fisher LW, Young M, Fernandez P, et al. Prognostic value of bone sialoprotein expression in clinically localized human prostate cancer. J Natl Cancer Inst. 1998;90:1000–8.

    Article  CAS  PubMed  Google Scholar 

  44. Kilkenny C, Browne WJ, Cuthill IC, Emerson M, Altman DG. Improving bioscience research reporting: The ARRIVE guidelines for reporting animal research. PLoS Biol. 2010;8:e1000412.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Nwosu ZC, Battello N, Rothley M, Piorońska W, Sitek B, Ebert MP, et al. Liver cancer cell lines distinctly mimic the metabolic gene expression pattern of the corresponding human tumours. J Exp Clin Cancer Res. 2018;37:211.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors acknowledge the experimental support of Naima Maloujahmoum (Metastasis Research Laboratory, University of Liege), Susumu Rokudai (Department of Molecular Pharmacology and Oncology, Gunma University), and Tadashi Handa (Pathology Dept. Gunma University). The authors are particularly thankful to Arnaud Blomme (Metastasis Research Laboratory, University of Liege) and Touko Hirano (Laboratory for Analytical Instruments, Gunma University Graduate School of Medicine) for the help concerning the MS analysis of patient material. The authors thank the Small Animal Imaging Platform of Montpellier (IPAM, http://www.ipam.cnrs.fr/) for the help with animal experiments. AT is thankful to Jacques Colinge (Bioinformatics and Systems Biology group, IRCM, Montpellier) for his R teachings and to Peter Friedl (The University of Texas MD Anderson Cancer Center, Houston, Texas, USA) for the helpful discussions. This work was supported with grants from the University of Liège, National Fund for Scientific Research (FNRS), Gunma University (GIAR Research Program for Omics-Based Medical Science). BC is supported by a Fondation de France grant (No. 00078461). RR is supported by Associazione Italiana per la Ricerca sul Cancro (AIRC), grant number MFAG 18459 and IG 2019 - ID. 23151; SR is supported by Fondazione Umberto Veronesi fellowship. AT is a senior research fellow of the French National Institute of Health and Medical Research (INSERM) and is supported by LabEx MabImprove Starting Grant. OD is supported by a grant from the “Fondation Contre le Cancer”. No funding bodies had any role in study design, data collection and analysis, decision to publish, or preparation of the paper.

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Author notes

  1. These authors contributed equally: Masahiko Nishiyama, Andrei Turtoi.

Authors and Affiliations

  1. Tumor Microenvironment and Resistance to Treatment Lab, Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, Montpellier, France

    Barbara Chiavarina, Regis Souche, Didier Pourquier, Evgenia Turtoi & Andrei Turtoi

  2. Université de Montpellier, Montpellier, France

    Barbara Chiavarina, Regis Souche, Antonio Maraver, Evgenia Turtoi & Andrei Turtoi

  3. Institut régional du Cancer de Montpellier (ICM)-Val d’Aurelle, Montpellier, France

    Barbara Chiavarina, Regis Souche, Didier Pourquier, Antonio Maraver, Lakhdar Khellaf, Evgenia Turtoi & Andrei Turtoi

  4. University of Brescia, Department of Molecular and Translational Medicine, Brescia, Italy

    Roberto Ronca, Sara Rezzola & Paola Chiodelli

  5. Department of Molecular Pharmacology and Oncology, Gunma University Graduate School of Medicine, Gunma, Japan

    Yukihiro Otaka & Masahiko Nishiyama

  6. Gunma University Initiative for Advanced Research (GIAR), Maebashi, Gunma, Japan

    Yukihiro Otaka, Takehiko Yokobori, Masahiko Nishiyama & Andrei Turtoi

  7. Department of Cell Physiology and Molecular Biophysics, Texas Tech University Health Sciences Center, Lubbock, TX, 79430, USA

    Roger Bryan Sutton

  8. Department of General Surgical Science, Graduate School of Medicine, Gunma University Maebashi, Gunma, Japan

    Takehiko Yokobori

  9. Oncogenic Pathways in Lung Cancer Lab, Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, Montpellier, France

    Antonio Maraver

  10. Department of Pathology, University Hospital San Giovanni di Dio AOU of Cagliari, University of Cagliari, Cagliari, Italy

    Gavino Faa

  11. Department of Diagnostic Pathology, Gunma University, Graduate School of Medicine, Maebashi, Gunma, Japan

    Tetsunari Oyama

  12. BIOTHEQUE, University of Liege, Liege, Belgium

    Stephanie Gofflot

  13. Metastasis Research Laboratory, GIGA Cancer, University of Liège, Liège, Belgium

    Akeila Bellahcène & Vincent Castronovo

  14. Department of Abdominal Surgery, University Hospital, University of Liège, Liège, Belgium

    Olivier Detry

  15. Department of Pathology, University Hospital, University of Liège, Liège, Belgium

    Philippe Delvenne

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  1. Barbara Chiavarina
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Contributions

Study concept and design: AT and MN; drafting of the paper: AT, MN, BC; data acquisition and evaluation: BC, RR, YO, SR, TY, PC, RS, and ET; bioinformatics analysis: AT; structure analysis and docking: RBS; statistical analysis: BC, RR, YO; provided human clinical samples: SG, OD, TO, and PD; evaluation of pathology/histology: DP, GF, LK, TO, and PD; critical revision of the paper for important intellectual content: AB, AM, VC, MN, and AT; obtained funding: VC, MN, and AT; study supervision: AT.

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Correspondence to Barbara Chiavarina or Andrei Turtoi.

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Chiavarina, B., Ronca, R., Otaka, Y. et al. Fibroblast-derived prolargin is a tumor suppressor in hepatocellular carcinoma. Oncogene 41, 1410–1420 (2022). https://doi.org/10.1038/s41388-021-02171-z

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