WNT-dependent interaction between inflammatory fibroblasts and FOLR2+ macrophages promotes fibrosis in chronic kidney disease.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
25 Jan 2024
25 Jan 2024
Historique:
received:
06
03
2023
accepted:
08
01
2024
medline:
26
1
2024
pubmed:
26
1
2024
entrez:
25
1
2024
Statut:
epublish
Résumé
Chronic kidney disease (CKD) is a public health problem driven by myofibroblast accumulation, leading to interstitial fibrosis. Heterogeneity is a recently recognized characteristic in kidney fibroblasts in CKD, but the role of different populations is still unclear. Here, we characterize a proinflammatory fibroblast population (named CXCL-iFibro), which corresponds to an early state of myofibroblast differentiation in CKD. We demonstrate that CXCL-iFibro co-localize with macrophages in the kidney and participate in their attraction, accumulation, and switch into FOLR2+ macrophages from early CKD stages on. In vitro, macrophages promote the switch of CXCL-iFibro into ECM-secreting myofibroblasts through a WNT/β-catenin-dependent pathway, thereby suggesting a reciprocal crosstalk between these populations of fibroblasts and macrophages. Finally, the detection of CXCL-iFibro at early stages of CKD is predictive of poor patient prognosis, which shows that the CXCL-iFibro population is an early player in CKD progression and demonstrates the clinical relevance of our findings.
Identifiants
pubmed: 38272907
doi: 10.1038/s41467-024-44886-z
pii: 10.1038/s41467-024-44886-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
743Subventions
Organisme : Institut National Du Cancer (French National Cancer Institute)
ID : INCa_11692
Informations de copyright
© 2024. The Author(s).
Références
Collaboration GBDCKD. Global, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 395, 709–733 (2020).
doi: 10.1016/S0140-6736(20)30045-3
Duffield, J. S. Cellular and molecular mechanisms in kidney fibrosis. J. Clin. Invest. 124, 2299–2306 (2014).
pubmed: 24892703
pmcid: 4038570
doi: 10.1172/JCI72267
Humphreys, B. D. et al. Fate tracing reveals the pericyte and not epithelial origin of myofibroblasts in kidney fibrosis. Am. J. Pathol. 176, 85–97 (2010).
pubmed: 20008127
pmcid: 2797872
doi: 10.2353/ajpath.2010.090517
Kramann, R., DiRocco, D. P. & Humphreys, B. D. Understanding the origin, activation and regulation of matrix-producing myofibroblasts for treatment of fibrotic disease. J. Pathol. 231, 273–289 (2013).
pubmed: 24006178
doi: 10.1002/path.4253
Kramann, R. & Humphreys, B. D. Kidney pericytes: roles in regeneration and fibrosis. Semin. Nephrol. 34, 374–383 (2014).
pubmed: 25217266
pmcid: 4163198
doi: 10.1016/j.semnephrol.2014.06.004
Kramann, R. et al. Perivascular Gli1+ progenitors are key contributors to injury-induced organ fibrosis. Cell Stem Cell 16, 51–66 (2015).
pubmed: 25465115
doi: 10.1016/j.stem.2014.11.004
Chang-Panesso, M., Kadyrov, F. F., Machado, F. G., Kumar, A. & Humphreys, B. D. Meis1 is specifically upregulated in kidney myofibroblasts during aging and injury but is not required for kidney homeostasis or fibrotic response. Am. J. Physiol. Renal Physiol. 315, F275–f290 (2018).
pubmed: 29592525
pmcid: 6139520
doi: 10.1152/ajprenal.00030.2018
Kuppe, C. et al. Decoding myofibroblast origins in human kidney fibrosis. Nature 589, 281–286 (2021).
pubmed: 33176333
doi: 10.1038/s41586-020-2941-1
Kuppe, C. et al. Spatial multi-omic map of human myocardial infarction. Nature 608, 766–777 (2022).
pubmed: 35948637
pmcid: 9364862
doi: 10.1038/s41586-022-05060-x
Sugimoto, H., Mundel, T. M., Kieran, M. W. & Kalluri, R. Identification of fibroblast heterogeneity in the tumor microenvironment. Cancer Biol. Ther. 5, 1640–1646 (2006).
pubmed: 17106243
doi: 10.4161/cbt.5.12.3354
Su, S. et al. CD10(+)GPR77(+) Cancer-associated fibroblasts promote cancer formation and chemoresistance by sustaining cancer stemness. Cell 172, 841–856 e816 (2018).
pubmed: 29395328
doi: 10.1016/j.cell.2018.01.009
Ishii, G., Ochiai, A. & Neri, S. Phenotypic and functional heterogeneity of cancer-associated fibroblast within the tumor microenvironment. Adv. Drug Deliv. Rev. 99, 186–196 (2016).
pubmed: 26278673
doi: 10.1016/j.addr.2015.07.007
Ohlund, D. et al. Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer. J. Exp. Med. 214, 579–596 (2017).
pubmed: 28232471
pmcid: 5339682
doi: 10.1084/jem.20162024
Bartoschek, M. et al. Spatially and functionally distinct subclasses of breast cancer-associated fibroblasts revealed by single cell RNA sequencing. Nat. Commun. 9, 5150 (2018).
pubmed: 30514914
pmcid: 6279758
doi: 10.1038/s41467-018-07582-3
Costa, A. et al. Fibroblast heterogeneity and immunosuppressive environment in human breast cancer. Cancer Cell 33, 463–479.e410 (2018).
pubmed: 29455927
doi: 10.1016/j.ccell.2018.01.011
Givel, A. M. et al. miR200-regulated CXCL12beta promotes fibroblast heterogeneity and immunosuppression in ovarian cancers. Nat. Commun. 9, 1056 (2018).
pubmed: 29535360
pmcid: 5849633
doi: 10.1038/s41467-018-03348-z
Elyada, E. et al. Cross-species single-cell analysis of pancreatic ductal adenocarcinoma reveals antigen-presenting cancer-associated fibroblasts. Cancer Discov. 9, 1102–1123 (2019).
pubmed: 31197017
pmcid: 6727976
doi: 10.1158/2159-8290.CD-19-0094
Bonneau, C. et al. A subset of activated fibroblasts is associated with distant relapse in early luminal breast cancer. Breast Cancer Res. 22, 76 (2020).
pubmed: 32665033
pmcid: 7362513
doi: 10.1186/s13058-020-01311-9
Pelon, F. et al. Cancer-associated fibroblast heterogeneity in axillary lymph nodes drives metastases in breast cancer through complementary mechanisms. Nat. Commun. 11, 404 (2020).
pubmed: 31964880
pmcid: 6972713
doi: 10.1038/s41467-019-14134-w
Wu, S. Z. et al. Stromal cell diversity associated with immune evasion in human triple-negative breast cancer. Embo. J. 39, e104063 (2020).
pubmed: 32790115
pmcid: 7527929
doi: 10.15252/embj.2019104063
Biffi, G. & Tuveson, D. A. Diversity and biology of cancer-associated fibroblasts. Physiol. Rev. 101, 147–176 (2021).
pubmed: 32466724
doi: 10.1152/physrev.00048.2019
Galbo, P. M. Jr, Zang, X. & Zheng, D. Molecular features of cancer-associated fibroblast subtypes and their implication on cancer pathogenesis, prognosis, and immunotherapy resistance. Clin. Cancer Res. 27, 2636–2647 (2021).
pubmed: 33622705
pmcid: 8102353
doi: 10.1158/1078-0432.CCR-20-4226
Hu, H. et al. Three subtypes of lung cancer fibroblasts define distinct therapeutic paradigms. Cancer Cell 39, 1531–1547.e1510 (2021).
pubmed: 34624218
pmcid: 8578451
doi: 10.1016/j.ccell.2021.09.003
Luo, H. et al. Pan-cancer single-cell analysis reveals the heterogeneity and plasticity of cancer-associated fibroblasts in the tumor microenvironment. Nat. Commun. 13, 6619 (2022).
pubmed: 36333338
pmcid: 9636408
doi: 10.1038/s41467-022-34395-2
Cremasco, V. et al. FAP delineates heterogeneous and functionally divergent stromal cells in immune-excluded breast tumors. Cancer Immunol Res 6, 1472–1485 (2018).
pubmed: 30266714
pmcid: 6597261
doi: 10.1158/2326-6066.CIR-18-0098
Biffi, G. et al. IL1-Induced JAK/STAT signaling is antagonized by TGFβ to shape CAF heterogeneity in pancreatic ductal adenocarcinoma. Cancer Discov. 9, 282–301 (2019).
pubmed: 30366930
doi: 10.1158/2159-8290.CD-18-0710
Davidson, S. et al. Single-Cell RNA sequencing reveals a dynamic stromal niche that supports tumor growth. Cell Rep. 31, 107628 (2020).
pubmed: 32433953
pmcid: 7242909
doi: 10.1016/j.celrep.2020.107628
Dominguez, C. X. et al. Single-cell RNA sequencing reveals stromal evolution into LRRC15(+) myofibroblasts as a determinant of patient response to cancer immunotherapy. Cancer Discov. 10, 232–253 (2020).
pubmed: 31699795
doi: 10.1158/2159-8290.CD-19-0644
Kieffer, Y. et al. Single-cell analysis reveals fibroblast clusters linked to immunotherapy resistance in cancer. Cancer Discov. 10, 1330–1351 (2020).
pubmed: 32434947
doi: 10.1158/2159-8290.CD-19-1384
Sebastian, A. et al. Single-cell transcriptomic analysis of tumor-derived fibroblasts and normal tissue-resident fibroblasts reveals fibroblast heterogeneity in breast cancer. Cancers 12, 1307 (2020).
pubmed: 32455670
pmcid: 7281266
doi: 10.3390/cancers12051307
Hutton, C. et al. Single-cell analysis defines a pancreatic fibroblast lineage that supports anti-tumor immunity. Cancer Cell 39, 1227–1244.e1220 (2021).
pubmed: 34297917
pmcid: 8443274
doi: 10.1016/j.ccell.2021.06.017
Obradovic, A. et al. Immunostimulatory cancer-associated fibroblast subpopulations can predict immunotherapy response in head and neck cancer. Clin Cancer Res 28, 2094–2109 (2022).
pubmed: 35262677
pmcid: 9161438
doi: 10.1158/1078-0432.CCR-21-3570
Peltier, A., Seban, R. D., Buvat, I., Bidard, F. C. & Mechta-Grigoriou, F. Fibroblast heterogeneity in solid tumors: from single cell analysis to whole-body imaging. Semin. Cancer Biol. 86, 262–272 (2022).
pubmed: 35489628
doi: 10.1016/j.semcancer.2022.04.008
Wu, S. Z. et al. A single-cell and spatially resolved atlas of human breast cancers. Nat. Genet. 53, 1334–1347 (2021).
pubmed: 34493872
pmcid: 9044823
doi: 10.1038/s41588-021-00911-1
Krishnamurty, A. T. et al. LRRC15(+) myofibroblasts dictate the stromal setpoint to suppress tumour immunity. Nature 611, 148–154 (2022).
pubmed: 36171287
pmcid: 9630141
doi: 10.1038/s41586-022-05272-1
Bhattacharjee, S. et al. Tumor restriction by type I collagen opposes tumor-promoting effects of cancer-associated fibroblasts. J. Clin. Invest. 131, e146987 (2021).
pubmed: 33905375
pmcid: 8159701
doi: 10.1172/JCI146987
Nicolas, A. M. et al. Inflammatory fibroblasts mediate resistance to neoadjuvant therapy in rectal cancer. Cancer Cell 40, 168–184.e113 (2022).
pubmed: 35120600
doi: 10.1016/j.ccell.2022.01.004
Pavkovic, M. et al. Multi omics analysis of fibrotic kidneys in two mouse models. Sci. Data 6, 92 (2019).
pubmed: 31201317
pmcid: 6570759
doi: 10.1038/s41597-019-0095-5
Naba, A. et al. Characterization of the extracellular matrix of normal and diseased tissues using proteomics. J. Proteome Res. 16, 3083–3091 (2017).
pubmed: 28675934
pmcid: 8078728
doi: 10.1021/acs.jproteome.7b00191
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. Cancer 3, 505–517 (2022).
pubmed: 35469013
pmcid: 9046084
doi: 10.1038/s43018-022-00356-3
Forbes, M. S. et al. Fight-or-flight: murine unilateral ureteral obstruction causes extensive proximal tubular degeneration, collecting duct dilatation, and minimal fibrosis. Am. J. Physiol. Renal Physiol. 303, F120–F129 (2012).
pubmed: 22535799
pmcid: 3431140
doi: 10.1152/ajprenal.00110.2012
Conway, B. R. et al. Kidney single-cell atlas reveals myeloid heterogeneity in progression and regression of kidney disease. J. Am. Soc. Nephrol. 31, 2833–2854 (2020).
pubmed: 32978267
pmcid: 7790206
doi: 10.1681/ASN.2020060806
Grande, M. T. et al. Snail1-induced partial epithelial-to-mesenchymal transition drives renal fibrosis in mice and can be targeted to reverse established disease. Nat. Med. 21, 989–997 (2015).
pubmed: 26236989
doi: 10.1038/nm.3901
Lovisa, S. et al. Epithelial-to-mesenchymal transition induces cell cycle arrest and parenchymal damage in renal fibrosis. Nat. Med. 21, 998–1009 (2015).
pubmed: 26236991
pmcid: 4587560
doi: 10.1038/nm.3902
Guiteras, R., Flaquer, M. & Cruzado, J. M. Macrophage in chronic kidney disease. Clin. Kidney J. 9, 765–771 (2016).
pubmed: 27994852
pmcid: 5162417
doi: 10.1093/ckj/sfw096
Tang, P. M., Nikolic-Paterson, D. J. & Lan, H. Y. Macrophages: versatile players in renal inflammation and fibrosis. Nat. Rev. Nephrol. 15, 144–158 (2019).
pubmed: 30692665
doi: 10.1038/s41581-019-0110-2
Wang, X. et al. The role of macrophages in kidney fibrosis. Front. Physiol. 12, 705838 (2021).
pubmed: 34421643
pmcid: 8378534
doi: 10.3389/fphys.2021.705838
Bell, R. M. B. & Conway, B. R. Macrophages in the kidney in health, injury and repair. Int. Rev. Cell Mol. Biol. 367, 101–147 (2022).
pubmed: 35461656
doi: 10.1016/bs.ircmb.2022.01.005
Vlasschaert, C., Moran, S. M. & Rauh, M. J. The myeloid-kidney interface in health and disease. Clin. J. Am. Soc. Nephrol. 17, 323–331 (2022).
pubmed: 34507968
pmcid: 8823925
doi: 10.2215/CJN.04120321
Casanova-Acebes, M. et al. Tissue-resident macrophages provide a pro-tumorigenic niche to early NSCLC cells. Nature 595, 578–584 (2021).
pubmed: 34135508
pmcid: 8923521
doi: 10.1038/s41586-021-03651-8
Nalio Ramos, R. et al. Tissue-resident FOLR2(+) macrophages associate with CD8(+) T cell infiltration in human breast cancer. Cell 185, 1189–1207.e1125 (2022).
pubmed: 35325594
doi: 10.1016/j.cell.2022.02.021
Timperi, E. et al. Lipid-associated macrophages are induced by cancer-associated fibroblasts and mediate immune suppression in breast cancer. Cancer Res. 82, 3291–3306 (2022).
pubmed: 35862581
doi: 10.1158/0008-5472.CAN-22-1427
Zimmerman, K. A. et al. Single-cell RNA sequencing identifies candidate renal resident macrophage gene expression signatures across species. J. Am. Soc. Nephrol. 30, 767–781 (2019).
pubmed: 30948627
pmcid: 6493978
doi: 10.1681/ASN.2018090931
Fu, J. et al. The single-cell landscape of kidney immune cells reveals transcriptional heterogeneity in early diabetic kidney disease. Kidney Int. 102, 1291–1304 (2022).
pubmed: 36108806
pmcid: 9691617
doi: 10.1016/j.kint.2022.08.026
Kleshchevnikov, V. et al. Cell2location maps fine-grained cell types in spatial transcriptomics. Nat. Biotechnol. 40, 661–671 (2022).
pubmed: 35027729
doi: 10.1038/s41587-021-01139-4
Doke, T. et al. Single-cell analysis identifies the interaction of altered renal tubules with basophils orchestrating kidney fibrosis. Nat. Immunol. 23, 947–959 (2022).
pubmed: 35552540
doi: 10.1038/s41590-022-01200-7
Wu, H. et al. Mapping the single-cell transcriptomic response of murine diabetic kidney disease to therapies. Cell Metab. 34, 1064–1078.e1066 (2022).
pubmed: 35709763
pmcid: 9262852
doi: 10.1016/j.cmet.2022.05.010
O’Sullivan, E. D. et al. Indian Hedgehog release from TNF-activated renal epithelia drives local and remote organ fibrosis. Sci. Transl. Med. 15, eabn0736 (2023).
pubmed: 37256934
doi: 10.1126/scitranslmed.abn0736
Wu, X. et al. CXCL12/CXCR4: an amazing challenge and opportunity in the fight against fibrosis. Ageing Res. Rev. 83, 101809 (2023).
pubmed: 36442720
doi: 10.1016/j.arr.2022.101809
Van Damme, J. et al. Homogeneous interferon-inducing 22K factor is related to endogenous pyrogen and interleukin-1. Nature 314, 266–268 (1985).
pubmed: 3920526
doi: 10.1038/314266a0
Lemos, D. R. et al. Interleukin-1beta activates a MYC-dependent metabolic switch in kidney stromal cells necessary for progressive tubulointerstitial fibrosis. J. Am. Soc. Nephrol. 29, 1690–1705 (2018).
pubmed: 29739813
pmcid: 6054344
doi: 10.1681/ASN.2017121283
Lin, H. et al. Discovery of a cytokine and its receptor by functional screening of the extracellular proteome. Science 320, 807–811 (2008).
pubmed: 18467591
doi: 10.1126/science.1154370
Mak, K. M. & Mei, R. Basement membrane type IV collagen and laminin: an overview of their biology and value as fibrosis biomarkers of liver disease. Anat. Rec. (Hoboken) 300, 1371–1390 (2017).
pubmed: 28187500
doi: 10.1002/ar.23567
Vu, R. et al. Wound healing in aged skin exhibits systems-level alterations in cellular composition and cell-cell communication. Cell Rep. 40, 111155 (2022).
pubmed: 35926463
pmcid: 9901190
doi: 10.1016/j.celrep.2022.111155
Garcia-Alonso, L., Holland, C. H., Ibrahim, M. M., Turei, D. & Saez-Rodriguez, J. Benchmark and integration of resources for the estimation of human transcription factor activities. Genome Res. 29, 1363–1375 (2019).
pubmed: 31340985
pmcid: 6673718
doi: 10.1101/gr.240663.118
Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).
pubmed: 30787437
pmcid: 6434952
doi: 10.1038/s41586-019-0969-x
Han, H. et al. TRRUST: a reference database of human transcriptional regulatory interactions. Sci. Rep. 5, 11432 (2015).
pubmed: 26066708
pmcid: 4464350
doi: 10.1038/srep11432
Lin, S. L. et al. Macrophage Wnt7b is critical for kidney repair and regeneration. Proc. Natl. Acad. Sci. USA 107, 4194–4199 (2010).
pubmed: 20160075
pmcid: 2840080
doi: 10.1073/pnas.0912228107
Saha, S. et al. Macrophage-derived extracellular vesicle-packaged WNTs rescue intestinal stem cells and enhance survival after radiation injury. Nat. Commun. 7, 13096 (2016).
pubmed: 27734833
pmcid: 5065628
doi: 10.1038/ncomms13096
Gadegbeku, C. A. et al. Design of the Nephrotic Syndrome Study Network (NEPTUNE) to evaluate primary glomerular nephropathy by a multidisciplinary approach. Kidney Int 83, 749–756 (2013).
pubmed: 23325076
pmcid: 3612359
doi: 10.1038/ki.2012.428
Gillies, C. E. et al. An eQTL landscape of kidney tissue in human nephrotic syndrome. Am. J. Hum. Genet. 103, 232–244 (2018).
pubmed: 30057032
pmcid: 6081280
doi: 10.1016/j.ajhg.2018.07.004
Anders, H. J. & Ryu, M. Renal microenvironments and macrophage phenotypes determine progression or resolution of renal inflammation and fibrosis. Kidney Int. 80, 915–925 (2011).
pubmed: 21814171
doi: 10.1038/ki.2011.217
Ricardo, S. D., van Goor, H. & Eddy, A. A. Macrophage diversity in renal injury and repair. J. Clin. Invest. 118, 3522–3530 (2008).
pubmed: 18982158
pmcid: 2575702
doi: 10.1172/JCI36150
Muto, Y. et al. Defining cellular complexity in human autosomal dominant polycystic kidney disease by multimodal single cell analysis. Nat. Commun. 13, 6497 (2022).
pubmed: 36310237
pmcid: 9618568
doi: 10.1038/s41467-022-34255-z
Henderson, N. C., Rieder, F. & Wynn, T. A. Fibrosis: from mechanisms to medicines. Nature 587, 555–566 (2020).
pubmed: 33239795
pmcid: 8034822
doi: 10.1038/s41586-020-2938-9
Affo, S. et al. Promotion of cholangiocarcinoma growth by diverse cancer-associated fibroblast subpopulations. Cancer Cell 39, 866–882.e811 (2021).
pubmed: 33930309
pmcid: 8241235
doi: 10.1016/j.ccell.2021.03.012
Chang, S. K. et al. Cadherin-11 regulates fibroblast inflammation. Proc. Natl. Acad. Sci. USA 108, 8402–8407 (2011).
pubmed: 21536877
pmcid: 3100978
doi: 10.1073/pnas.1019437108
Croft, A. P. et al. Distinct fibroblast subsets drive inflammation and damage in arthritis. Nature 570, 246–251 (2019).
pubmed: 31142839
pmcid: 6690841
doi: 10.1038/s41586-019-1263-7
Mhaidly, R. & Mechta-Grigoriou, F. Role of cancer-associated fibroblast subpopulations in immune infiltration, as a new means of treatment in cancer. Immunol. Rev. 302, 259–272 (2021).
pubmed: 34013544
pmcid: 8360036
doi: 10.1111/imr.12978
Wei, K., Nguyen, H. N. & Brenner, M. B. Fibroblast pathology in inflammatory diseases. J. Clin. Invest. 131, e149538 (2021).
pubmed: 34651581
pmcid: 8516469
doi: 10.1172/JCI149538
Mizoguchi, F. et al. Functionally distinct disease-associated fibroblast subsets in rheumatoid arthritis. Nat. Commun. 9, 789 (2018).
pubmed: 29476097
pmcid: 5824882
doi: 10.1038/s41467-018-02892-y
Zhang, F. et al. Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry. Nat. Immunol. 20, 928–942 (2019).
pubmed: 31061532
pmcid: 6602051
doi: 10.1038/s41590-019-0378-1
Cantero-Navarro, E. et al. Role of macrophages and related cytokines in kidney disease. Front. Med. 8, 688060 (2021).
doi: 10.3389/fmed.2021.688060
Cassetta, L. et al. Human tumor-associated macrophage and monocyte transcriptional landscapes reveal cancer-specific reprogramming, biomarkers, and therapeutic targets. Cancer Cell 35, 588–602.e510 (2019).
pubmed: 30930117
pmcid: 6472943
doi: 10.1016/j.ccell.2019.02.009
Kawakami, T., Ren, S. & Duffield, J. S. Wnt signalling in kidney diseases: dual roles in renal injury and repair. J. Pathol. 229, 221–231 (2013).
pubmed: 23097132
doi: 10.1002/path.4121
Xiao, L. et al. Sustained activation of Wnt/β-catenin signaling drives AKI to CKD progression. J. Am. Soc. Nephrol. 27, 1727–1740 (2016).
pubmed: 26453613
doi: 10.1681/ASN.2015040449
Zuo, Y. & Liu, Y. New insights into the role and mechanism of Wnt/β-catenin signalling in kidney fibrosis. Nephrology 23, 38–43 (2018).
pubmed: 30298654
doi: 10.1111/nep.13472
Malik, S. A., Modarage, K. & Goggolidou, P. The Role of Wnt Signalling in Chronic Kidney Disease (CKD). Genes 11, 496 (2020).
pubmed: 32365994
pmcid: 7290783
doi: 10.3390/genes11050496
Schunk, S. J., Floege, J., Fliser, D. & Speer, T. WNT-β-catenin signalling—a versatile player in kidney injury and repair. Nat. Rev. Nephrol. 17, 172–184 (2021).
pubmed: 32989282
doi: 10.1038/s41581-020-00343-w
Li, L., Fu, H. & Liu, Y. The fibrogenic niche in kidney fibrosis: components and mechanisms. Nat. Rev. Nephrol. 18, 545–557 (2022).
pubmed: 35788561
doi: 10.1038/s41581-022-00590-z
Zhou, D. et al. Fibroblast-specific β-catenin signaling dictates the outcome of AKI. J. Am. Soc. Nephrol. 29, 1257–1271 (2018).
pubmed: 29343518
pmcid: 5875957
doi: 10.1681/ASN.2017080903
Zhou, D. et al. Tubule-derived Wnts are required for fibroblast activation and kidney fibrosis. J. Am. Soc. Nephrol. 28, 2322–2336 (2017).
pubmed: 28336721
pmcid: 5533232
doi: 10.1681/ASN.2016080902
Surendran, K., Schiavi, S. & Hruska, K. A. Wnt-dependent beta-catenin signaling is activated after unilateral ureteral obstruction, and recombinant secreted frizzled-related protein 4 alters the progression of renal fibrosis. J. Am. Soc. Nephrol. 16, 2373–2384 (2005).
pubmed: 15944336
doi: 10.1681/ASN.2004110949
Feng, Y. et al. Wnt/β-catenin-promoted macrophage alternative activation contributes to kidney fibrosis. J. Am. Soc. Nephrol. 29, 182–193 (2018).
pubmed: 29021383
doi: 10.1681/ASN.2017040391
Ju, W. et al. Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker. Sci. Transl. Med. 7, 316ra193 (2015).
pubmed: 26631632
pmcid: 4861144
doi: 10.1126/scitranslmed.aac7071
Barisoni, L. et al. Digital pathology evaluation in the multicenter Nephrotic Syndrome Study Network (NEPTUNE). Clin. J. Am. Soc. Nephrol. 8, 1449–1459 (2013).
pubmed: 23393107
pmcid: 3731905
doi: 10.2215/CJN.08370812
Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587.e3529 (2021).
pubmed: 34062119
pmcid: 8238499
doi: 10.1016/j.cell.2021.04.048
Cohen, C. D., Frach, K., Schlondorff, D. & Kretzler, M. Quantitative gene expression analysis in renal biopsies: a novel protocol for a high-throughput multicenter application. Kidney Int. 61, 133–140 (2002).
pubmed: 11786093
doi: 10.1046/j.1523-1755.2002.00113.x
Zee, J. et al. Kidney biopsy features most predictive of clinical outcomes in the spectrum of minimal change disease and focal segmental glomerulosclerosis. J. Am. Soc. Nephrol. 33, 1411–1426 (2022).
pubmed: 35581011
pmcid: 9257823
doi: 10.1681/ASN.2021101396