Skip to content
2000
image of A Metastasis-competent CAF Subpopulation Defined by MFAP5+THY1+ Co-expression Drives Prostate Cancer Metastasis via EMT Activation

Abstract

Background

The tumor microenvironment, particularly cancer-associated fibroblasts (CAFs), contributes to prostate cancer (PCa) metastasis, however, the role of CAF heterogeneity remains incompletely characterized. The study aims to identify and functionally characterize a metastasis-competent CAF subpopulation in PCa and evaluate its potential as a biomarker for predicting metastatic progression.

Methods

We integrated single-cell RNA sequencing data from 1,214 CAFs across 14 PCa specimens. Metastasis-derived CAFs were functionally validated . Stromal marker expression was assessed by multiplex immunofluorescence in 78 PCa tissues samples.

Results

A 20-gene signature stratified CAFs into three subsets, with the -expressing subset (CAFa) enriched in metastatic patients. Co-expression of and specifically identified CAFa with 96.2% specificity. MFAP5 secretion was associated with AKT phosphorylation, Slug upregulation, and epithelial-mesenchymal transition (EMT). Stromal ++ co-localization predicted postoperative metastasis risk independently of Gleason score (multivariate HR = 5.69, < 0.001).

Discussion

Our findings establish stromal ++ co-localization as a potential prognostic biomarker that could complement Gleason scoring. Further validation in multi-center cohorts is required to confirm its clinical independence.

Conclusion

We identified a metastasis-competent CAF subpopulation defined by ++ co-expression, where serves as a spatial anchor for MFAP5 detection and MFAP5 secretion is functionally linked to AKT/EMT pathway activation.

Loading

Article metrics loading...

/content/journals/pra/10.2174/0115748928439833251118072935
2025-11-26
2026-02-26
Loading full text...

Full text loading...

References

  1. Siegel R.L. Kratzer T.B. Giaquinto A.N. Sung H. Jemal A. Cancer statistics, 2025. CA Cancer J. Clin. 2025 75 1 10 45 10.3322/caac.21871 39817679
    [Google Scholar]
  2. Barragan-Carrillo R. Asirwa F.C. Dienstmann R. Pendhakar D. Ruiz-Garcia E. Global oncology: Tackling disparities and promoting innovations in low- and middle-income countries. Am. Soc. Clin. Oncol. Educ. Book 2025 45 3 473930 10.1200/EDBK‑25‑473930 40526883
    [Google Scholar]
  3. Ito K Mori K Kumar R Global viewpoints: Evolving epidemiology and treatment patterns of prostate cancer in Asia. BJU Int 2025 bju.16900. 10.1111/bju.16900 40851349
    [Google Scholar]
  4. Bray F. Laversanne M. Sung H. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2024 74 3 229 263 10.3322/caac.21834 38572751
    [Google Scholar]
  5. Xu Y. Zhang G. Liu Y. Molecular mechanisms and targeted therapy for the metastasis of prostate cancer to the bones.(Review) Int. J. Oncol. 2024 65 5 104 10.3892/ijo.2024.5692 39301646
    [Google Scholar]
  6. Johnston T.J. Shaw G.L. Lamb A.D. Mortality among men with advanced prostate cancer excluded from the protect trial. Eur. Urol. 2017 71 3 381 388 10.1016/j.eururo.2016.09.040 27720537
    [Google Scholar]
  7. Arner E.N. Rathmell J.C. Metabolic programming and immune suppression in the tumor microenvironment. Cancer Cell 2023 41 3 421 433 10.1016/j.ccell.2023.01.009 36801000
    [Google Scholar]
  8. Bonollo F. Thalmann G.N. Kruithof-de Julio M. Karkampouna S. The role of cancer-associated fibroblasts in prostate cancer tumorigenesis. Cancers 2020 12 7 1887 10.3390/cancers12071887 32668821
    [Google Scholar]
  9. Brown T.J. Rutland C.S. Choi K.K. Modulation of the pre-metastatic bone niche: Molecular changes mediated by bone-homing prostate cancer extracellular vesicles. Front. Cell Dev. Biol. 2024 12 1354606 10.3389/fcell.2024.1354606 38455075
    [Google Scholar]
  10. Hudson B.D. Kulp K.S. Loots G.G. Prostate cancer invasion and metastasis: Insights from mining genomic data. Brief. Funct. Genomics 2013 12 5 397 410 10.1093/bfgp/elt021 23878130
    [Google Scholar]
  11. Bedeschi M. Marino N. Cavassi E. Piccinini F. Tesei A. Cancer-associated fibroblast: Role in prostate cancer progression to metastatic disease and therapeutic resistance. Cells 2023 12 5 802 10.3390/cells12050802 36899938
    [Google Scholar]
  12. Zhao J. Shen J. Mao L. Yang T. Liu J. Hongbin S. Cancer associated fibroblast secreted miR-432-5p targets CHAC1 to inhibit ferroptosis and promote acquired chemoresistance in prostate cancer. Oncogene 2024 43 27 2104 2114 10.1038/s41388‑024‑03057‑6 38769193
    [Google Scholar]
  13. Song X. Li T. Zhou W. CAF-derived exosomal miR-196b-5p after androgen deprivation therapy promotes epithelial-mesenchymal transition in prostate cancer cells through HOXC8/NF-κB signaling pathway. Biol. Direct 2025 20 1 80 10.1186/s13062‑025‑00667‑2 40615904
    [Google Scholar]
  14. Pan S. Yin R. Zhu H. Shen S. Li Z. Liu B. Prostate cancer cancer‐associated fibroblasts with stable markers post‐androgen deprivation therapy associated with tumor progression and castration resistant prostate cancer. Cancer Sci. 2024 115 9 2893 2907 10.1111/cas.16267 38970292
    [Google Scholar]
  15. Di Carlo E. Sorrentino C. The multifaceted role of the stroma in the healthy prostate and prostate cancer. J. Transl. Med. 2024 22 1 825 10.1186/s12967‑024‑05564‑2 39238004
    [Google Scholar]
  16. Olumi A.F. Grossfeld G.D. Hayward S.W. Carroll P.R. Tlsty T.D. Cunha G.R. Carcinoma-associated fibroblasts direct tumor progression of initiated human prostatic epithelium. Cancer Res. 1999 59 19 5002 5011 10519415
    [Google Scholar]
  17. Thalmann G.N. Rhee H. Sikes R.A. Human prostate fibroblasts induce growth and confer castration resistance and metastatic potential in LNCaP Cells. Eur. Urol. 2010 58 1 162 172 10.1016/j.eururo.2009.08.026 19747763
    [Google Scholar]
  18. Zheng H. An M. Luo Y. PDGFRα+ITGA11+ fibroblasts foster early-stage cancer lymphovascular invasion and lymphatic metastasis via ITGA11-SELE interplay. Cancer Cell 2024 42 4 682 700.e12 10.1016/j.ccell.2024.02.002 38428409
    [Google Scholar]
  19. Elyada E. Bolisetty M. Laise P. Cross-species single-cell analysis of pancreatic ductal adenocarcinoma reveals antigen-presenting cancer-associated fibroblasts. Cancer Discov. 2019 9 8 1102 1123 10.1158/2159‑8290.CD‑19‑0094 31197017
    [Google Scholar]
  20. Kato M. Placencio-Hickok V.R. Madhav A. Heterogeneous cancer-associated fibroblast population potentiates neuroendocrine differentiation and castrate resistance in a CD105-dependent manner. Oncogene 2019 38 5 716 730 10.1038/s41388‑018‑0461‑3 30177832
    [Google Scholar]
  21. Tirosh I. Izar B. Prakadan S.M. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 2016 352 6282 189 196 10.1126/science.aad0501 27124452
    [Google Scholar]
  22. Owen J.S. Clayton A. Pearson H.B. Cancer-associated fibroblast heterogeneity, activation and function: Implications for prostate cancer. Biomolecules 2022 13 1 67 10.3390/biom13010067 36671452
    [Google Scholar]
  23. Wang S. Fan G. Li L. Integrative analyses of bulk and single-cell RNA-seq identified cancer-associated fibroblasts-related signature as a prognostic factor for immunotherapy in NSCLC. Cancer Immunol. Immunother. 2023 72 7 2423 2442 10.1007/s00262‑023‑03428‑0 37010552
    [Google Scholar]
  24. Liu Y. Sinjab A. Min J. Conserved spatial subtypes and cellular neighborhoods of cancer-associated fibroblasts revealed by single-cell spatial multi-omics. Cancer Cell 2025 43 5 905 924.e6 10.1016/j.ccell.2025.03.004 40154487
    [Google Scholar]
  25. Jia H. Chen X. Zhang L. Chen M. Cancer associated fibroblasts in cancer development and therapy. J. Hematol. Oncol. 2025 18 1 36 10.1186/s13045‑025‑01688‑0 40156055
    [Google Scholar]
  26. Geng X. Chen H. Zhao L. Cancer-associated fibroblast (CAF) heterogeneity and targeting therapy of CAFS in pancreatic cancer. Front. Cell Dev. Biol. 2021 9 655152 10.3389/fcell.2021.655152 34336821
    [Google Scholar]
  27. Hu B. Wu C. Mao H. Subpopulations of cancer-associated fibroblasts link the prognosis and metabolic features of pancreatic ductal adenocarcinoma. Ann. Transl. Med. 2022 10 5 262 10.21037/atm‑22‑407 35402584
    [Google Scholar]
  28. Bartoschek M. Oskolkov N. Bocci M. Spatially and functionally distinct subclasses of breast cancer-associated fibroblasts revealed by single cell RNA sequencing. Nat. Commun. 2018 9 1 5150 10.1038/s41467‑018‑07582‑3 30514914
    [Google Scholar]
  29. Bian X. Wang W. Abudurexiti M. Integration analysis of single‐cell multi‐omics reveals prostate cancer heterogeneity. Adv. Sci. 2024 11 18 2305724 10.1002/advs.202305724 38483933
    [Google Scholar]
  30. Chen S. Zhu G. Yang Y. Single-cell analysis reveals transcriptomic remodellings in distinct cell types that contribute to human prostate cancer progression. Nat. Cell Biol. 2021 23 1 87 98 10.1038/s41556‑020‑00613‑6 33420488
    [Google Scholar]
  31. Sahai E. Astsaturov I. Cukierman E. A framework for advancing our understanding of cancer-associated fibroblasts. Nat. Rev. Cancer 2020 20 3 174 186 10.1038/s41568‑019‑0238‑1 31980749
    [Google Scholar]
  32. Purcell J.W. Tanlimco S.G. Hickson J. LRRC15 is a novel mesenchymal protein and stromal target for antibody–drug conjugates. Cancer Res. 2018 78 14 4059 4072 10.1158/0008‑5472.CAN‑18‑0327 29764866
    [Google Scholar]
  33. Ucaryilmaz Metin C. Ozcan G. Comprehensive bioinformatic analysis reveals a cancer-associated fibroblast gene signature as a poor prognostic factor and potential therapeutic target in gastric cancer. BMC Cancer 2022 22 1 692 10.1186/s12885‑022‑09736‑5 35739492
    [Google Scholar]
  34. Zhu S. Ye L. Bennett S. Xu H. He D. Xu J. Molecular structure and function of microfibrillar‐associated proteins in skeletal and metabolic disorders and cancers. J. Cell. Physiol. 2021 236 1 41 48 10.1002/jcp.29893 32572962
    [Google Scholar]
  35. Sun Y. Dong J. Li J. Zhang Y. Han Y. Overexpression of MFAP5 inhibits the progression of papillary thyroid cancer and aerobic glycolysis by regulating the EFEMP2/Wnt/β-catenin pathway. Pathol. Res. Pract. 2025 268 155846 10.1016/j.prp.2025.155846 40020327
    [Google Scholar]
  36. Xu Q. Chang H. Tian X. Lou C. Ma H. Yang X. Hypoxia-induced MFAP5 promotes tumor migration and invasion via akt pathway in head and neck squamous cell carcinoma. J. Cancer 2020 11 6 1596 1605 10.7150/jca.38217 32047565
    [Google Scholar]
  37. Wu Z. Wang T. Fang M. MFAP5 promotes tumor progression and bone metastasis by regulating ERK/MMP signaling pathways in breast cancer. Biochem. Biophys. Res. Commun. 2018 498 3 495 501 10.1016/j.bbrc.2018.03.007 29526753
    [Google Scholar]
  38. Wu Y. Wu P. Zhang Q. Chen W. Liu X. Zheng W. MFAP5 promotes basal-like breast cancer progression by activating the EMT program. Cell Biosci. 2019 9 1 24 10.1186/s13578‑019‑0284‑0 30899449
    [Google Scholar]
  39. Leung C.S. Yeung T.L. Yip K.P. Calcium-dependent FAK/CREB/TNNC1 signalling mediates the effect of stromal MFAP5 on ovarian cancer metastatic potential. Nat. Commun. 2014 5 1 5092 10.1038/ncomms6092 25277212
    [Google Scholar]
  40. Zhou Z. Cui D. Sun M.H. CAFs‐derived MFAP5 promotes bladder cancer malignant behavior through NOTCH2/HEY1 signaling. FASEB J. 2020 34 6 7970 7988 10.1096/fj.201902659R 32293074
    [Google Scholar]
  41. Weinstein J.N. Collisson E.A. Mills G.B. The Cancer Genome Atlas Pan-Cancer analysis project. Nat. Genet. 2013 45 10 1113 1120 10.1038/ng.2764 24071849
    [Google Scholar]
  42. Han Y. Wang Y. Dong X. TISCH2: Expanded datasets and new tools for single-cell transcriptome analyses of the tumor microenvironment. Nucleic Acids Res. 2023 51 D1 D1425 D1431 10.1093/nar/gkac959 36321662
    [Google Scholar]
  43. Song H. Weinstein H.N.W. Allegakoen P. Single-cell analysis of human primary prostate cancer reveals the heterogeneity of tumor-associated epithelial cell states. Nat. Commun. 2022 13 1 141 10.1038/s41467‑021‑27322‑4 35013146
    [Google Scholar]
  44. Racle J. de Jonge K. Baumgaertner P. Speiser D.E. Gfeller D. Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data. eLife 2017 6 26476 10.7554/eLife.26476 29130882
    [Google Scholar]
  45. Becht E. Giraldo N.A. Lacroix L. Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression. Genome Biol. 2016 17 1 218 10.1186/s13059‑016‑1070‑5 27765066
    [Google Scholar]
  46. Aran D. Hu Z. Butte A.J. xCell: Digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 2017 18 1 220 10.1186/s13059‑017‑1349‑1 29141660
    [Google Scholar]
  47. Herrera M. Berral-González A. López-Cade I. Cancer-associated fibroblast-derived gene signatures determine prognosis in colon cancer patients. Mol. Cancer 2021 20 1 73 10.1186/s12943‑021‑01367‑x 33926453
    [Google Scholar]
  48. Wu T. Wang W. Shi G. Targeting HIC1/TGF-β axis-shaped prostate cancer microenvironment restrains its progression. Cell Death Dis. 2022 13 7 624 10.1038/s41419‑022‑05086‑z 35853880
    [Google Scholar]
  49. Hao Y. Stuart T. Kowalski M.H. Dictionary learning for integrative, multimodal and scalable single-cell analysis. Nat. Biotechnol. 2024 42 2 293 304 10.1038/s41587‑023‑01767‑y 37231261
    [Google Scholar]
  50. Zhang X. Lan Y. Xu J. CellMarker: A manually curated resource of cell markers in human and mouse. Nucleic Acids Res. 2019 47 D1 D721 D728 10.1093/nar/gky900 30289549
    [Google Scholar]
  51. Sturm G. Finotello F. Petitprez F. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics 2019 35 14 i436 i445 10.1093/bioinformatics/btz363 31510660
    [Google Scholar]
  52. Gu Z. Eils R. Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 2016 32 18 2847 2849 10.1093/bioinformatics/btw313 27207943
    [Google Scholar]
  53. Jones E.A. English A. Kinsey S.E. Optimization of a flow cytometry‐based protocol for detection and phenotypic characterization of multipotent mesenchymal stromal cells from human bone marrow. Cytometry B Clin. Cytom. 2006 70B 6 391 399 10.1002/cyto.b.20118 16977637
    [Google Scholar]
  54. Fearns C. Dowdle E.B. The desmoplastic response: Induction of collagen synthesis by melanoma cells in vitro. Int. J. Cancer 1992 50 4 621 627 10.1002/ijc.2910500423 1537627
    [Google Scholar]
  55. Paull D. Sevilla A. Zhou H. Automated, high-throughput derivation, characterization and differentiation of induced pluripotent stem cells. Nat. Methods 2015 12 9 885 892 10.1038/nmeth.3507 26237226
    [Google Scholar]
  56. Jones E.A. Kinsey S.E. English A. Isolation and characterization of bone marrow multipotential mesenchymal progenitor cells. Arthritis Rheum. 2002 46 12 3349 3360 10.1002/art.10696 12483742
    [Google Scholar]
  57. Jiang K. Xu L. Cheng F. Ning J. COL10A1 facilitates prostate cancer progression by interacting with INHBA to Activate the PI3K/AKT pathway. J. Cell. Mol. Med. 2024 28 23 70249 10.1111/jcmm.70249 39656597
    [Google Scholar]
  58. Li S. Kang Y. Zeng Y. Targeting tumor and bone microenvironment: Novel therapeutic opportunities for castration-resistant prostate cancer patients with bone metastasis. Biochim. Biophys. Acta Rev. Cancer 2024 1879 1 189033 10.1016/j.bbcan.2023.189033 38040267
    [Google Scholar]
  59. Hansen S.B. Unal B. Kuzu O.F. Saatcioglu F. Immunological facets of prostate cancer and the potential of immune checkpoint inhibition in disease management. Theranostics 2024 14 18 6913 6934 10.7150/thno.100555 39629128
    [Google Scholar]
  60. Pakula H. Pederzoli F. Fanelli G.N. Nuzzo P.V. Rodrigues S. Loda M. Deciphering the tumor microenvironment in prostate cancer: A focus on the stromal component. Cancers 2024 16 21 3685 10.3390/cancers16213685 39518123
    [Google Scholar]
  61. ChallaSivaKanaka S Vickman RE, Kakarla M, Hayward SW, Franco OE. Fibroblast heterogeneity in prostate carcinogenesis. Cancer Lett. 2022 525 76 83 10.1016/j.canlet.2021.10.028 34715252
    [Google Scholar]
  62. Li T.T. Hao Q.G. Teng Z.W. SNAI2 as a prognostic biomarker based on cancer-associated fibroblasts in patients with lung adenocarcinoma. Clin. Med. Insights Oncol. 2024 18 11795549241280506 10.1177/11795549241280506 39314798
    [Google Scholar]
  63. Zhou Y. Lu Y. Czubayko F. Identification of cancer associated fibroblasts related genes signature to facilitate improved prediction of prognosis and responses to therapy in patients with pancreatic cancer. Int. J. Mol. Sci. 2025 26 10 4876 10.3390/ijms26104876 40430018
    [Google Scholar]
  64. Yan X. Gao X. Dong J. Integration of single-cell and bulk rna-seq data to identify the cancer-associated fibroblast subtypes and risk model in glioma. Biochem. Genet. 2025 63 2 1275 1297 10.1007/s10528‑024‑10751‑3 38536568
    [Google Scholar]
  65. Zheng S. Zou Y. Tang Y. Landscape of cancer-associated fibroblasts identifies the secreted biglycan as a protumor and immunosuppressive factor in triple-negative breast cancer. OncoImmunology 2022 11 1 2020984 10.1080/2162402X.2021.2020984 35003899
    [Google Scholar]
  66. Chu T. Wang Z. Pe’er D. Danko C.G. Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology. Nat. Can. 2022 3 4 505 517 10.1038/s43018‑022‑00356‑3 35469013
    [Google Scholar]
  67. Fan J. Lyu Y. Zhang Q. Wang X. Li M. Xiao R. MuSiC2: Cell-type deconvolution for multi-condition bulk RNA-seq data. Brief. Bioinform. 2022 23 6 bbac430 10.1093/bib/bbac430 36208175
    [Google Scholar]
  68. Xu A. Xu X.N. Luo Z. Huang X. Gong R.Q. Fu D.Y. Identification of prognostic cancer-associated fibroblast markers in luminal breast cancer using weighted gene co-expression network analysis. Front. Oncol. 2023 13 1191660 10.3389/fonc.2023.1191660 37207166
    [Google Scholar]
  69. Zou D. Xin X. Xu H. Xu Y. Xu T. Development and validation of a cancer-associated fibroblast gene signature-based model for predicting immunotherapy response in colon cancer. Sci. Rep. 2025 15 1 16550 10.1038/s41598‑025‑01185‑x 40360558
    [Google Scholar]
  70. Zheng H. Liu H. Li H. Dou W. Wang X. Weighted Gene Co-expression Network Analysis Identifies a Cancer-Associated Fibroblast Signature for Predicting Prognosis and Therapeutic Responses in Gastric Cancer. Front. Mol. Biosci. 2021 8 744677 10.3389/fmolb.2021.744677 34692770
    [Google Scholar]
  71. Gandy K.L. Domen J. Aguila H. Weissman I.L. CD8+TCR+ and CD8+TCR- cells in whole bone marrow facilitate the engraftment of hematopoietic stem cells across allogeneic barriers. Immunity 1999 11 5 579 590 10.1016/S1074‑7613(00)80133‑8 10591183
    [Google Scholar]
  72. Zhang N. Bevan M.J. CD8(+) T cells: Foot soldiers of the immune system. Immunity 2011 35 2 161 168 10.1016/j.immuni.2011.07.010 21867926
    [Google Scholar]
  73. Heimdörfer D. Artamonova N. Culig Z. Heidegger I. Unraveling molecular characteristics and tumor microenvironment dynamics of neuroendocrine prostate cancer. J. Cancer Res. Clin. Oncol. 2024 150 10 462 10.1007/s00432‑024‑05983‑0 39412660
    [Google Scholar]
  74. Messex J.K. Liou G.Y. Impact of immune cells in the tumor microenvironment of prostate cancer metastasis. Life 2023 13 2 333 10.3390/life13020333 36836690
    [Google Scholar]
  75. Singhal G. Garg P. Mohanty A. Advancing prostate cancer treatment: Innovations and challenges in immunotherapy Cancer Treat Res. 2025 129 267 91 10.1007/978‑3‑031‑97242‑3_12 40847237
    [Google Scholar]
/content/journals/pra/10.2174/0115748928439833251118072935
Loading
/content/journals/pra/10.2174/0115748928439833251118072935
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher’s website along with the published article.

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test