The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Snail1-induced partial epithelial-to-mesenchymal transition drives renal fibrosis in mice and can be targeted to reverse established disease
Open accessAbstract
Progressive kidney fibrosis contributes greatly to end-stage renal failure, and no specific treatment is available to preserve organ function. During renal fibrosis, myofibroblasts accumulate in the interstitium of the kidney, leading to massive deposition of extracellular matrix and organ dysfunction. The origin of myofibroblasts is manifold, but the contribution of an epithelial-to-mesenchymal transition (EMT) undergone by renal epithelial cells during kidney fibrosis is still debated. We show that the reactivation of Snai1 (encoding snail family zinc finger 1, known as Snail1) in mouse renal epithelial cells is required for the development of fibrosis in the kidney. Damage-mediated Snail1 reactivation induces a partial EMT in tubular epithelial cells that, without directly contributing to the myofibroblast population, relays signals to the interstitium to promote myofibroblast differentiation and fibrogenesis and to sustain inflammation. We also show that Snail1-induced fibrosis can be reversed in vivo and that obstructive nephropathy can be therapeutically ameliorated in mice by targeting Snail1 expression. These results reconcile conflicting data on the role of the EMT in renal fibrosis and provide avenues for the design of novel anti-fibrotic therapies.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The basics of epithelial-mesenchymal transition
Kalluri, R., & Weinberg, R. A. (2009) · Journal of Clinical Investigation · doi:10.1172/jci39104 · Cited by 10,196
Macrophage plasticity and interaction with lymphocyte subsets: cancer as a paradigm
Biswas, S. K., & Mantovani, A. (2010) · Nature Immunology · doi:10.1038/ni.1937 · Cited by 3,840
NF-κB in the liver—linking injury, fibrosis and hepatocellular carcinoma
Luedde, T., & Schwabe, R. F. (2011) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/nrgastro.2010.213 · Cited by 1,345
Cited by
Nieto, M. A., Huang, R. Y.-J., Jackson, R. A., & Thiery, J. P. (2016) · Cell · doi:10.1016/j.cell.2016.06.028 · Cited by 4,492
Self-citationNew insights into the mechanisms of epithelial–mesenchymal transition and implications for cancer
Dongre, A., & Weinberg, R. A. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0080-4 · Cited by 3,876
TGF-β: the master regulator of fibrosis
Meng, X.-M., Nikolic-Paterson, D. J., & Lan, H. Y. (2016) · Nature Reviews Nephrology · doi:10.1038/nrneph.2016.48 · Cited by 3,528
Guidelines and definitions for research on epithelial-mesenchymal transition
Yang, J., Antin, P., Berx, G., Blanpain, C., Brabletz, T., Bronner, M., Campbell, K., Cano, A., Casanova, J., Christofori, G., et al. (2020) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-020-0237-9 · Cited by 2,226
Self-citationTargeting the progression of chronic kidney disease
Ruiz-Ortega, M., Rayego-Mateos, S., Lamas, S., Ortiz, A., & Rodrigues-Diez, R. R. (2020) · Nature Reviews Nephrology · doi:10.1038/s41581-019-0248-y · Cited by 979
Renal tubule injury: a driving force toward chronic kidney disease
Liu, B.-C., Tang, T.-T., Lv, L.-L., & Lan, H.-Y. (2018) · Kidney International · doi:10.1016/j.kint.2017.09.033 · Cited by 913
TGF-β1 Signaling and Tissue Fibrosis
Kim, K. K., Sheppard, D., & Chapman, H. A. (2018) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a022293 · Cited by 800
Endothelial to Mesenchymal Transition in Cardiovascular Disease
Kovacic, J. C., Dimmeler, S., Harvey, R. P., Finkel, T., Aikawa, E., Krenning, G., & Baker, A. H. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.09.089 · Cited by 631
Chen, T., You, Y., Jiang, H., & Wang, Z. Z. (2017) · Journal of Cellular Physiology · doi:10.1002/jcp.25797 · Cited by 560
Cellular and molecular pathways of renal repair after acute kidney injury
Kumar, S. (2018) · Kidney International · doi:10.1016/j.kint.2017.07.030 · Cited by 271
Emerging role of tumor cell plasticity in modifying therapeutic response
Qin, S., Jiang, J., Lu, Y., Nice, E. C., Huang, C., Zhang, J., & He, W. (2020) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-020-00313-5 · Cited by 268
Epithelial to Mesenchymal Transition: A Mechanism that Fuels Cancer Radio/Chemoresistance
Dudás, J., Ladányi, A., Ingruber, J., Steinbichler, T. B., & Riechelmann, H. (2020) · Cells · doi:10.3390/cells9020428 · Cited by 213
Epithelial plasticity, epithelial-mesenchymal transition, and the TGF-β family
Katsuno, Y., & Derynck, R. (2021) · Developmental Cell · doi:10.1016/j.devcel.2021.02.028 · Cited by 187
Cyclin G1 and TASCC regulate kidney epithelial cell G 2 -M arrest and fibrotic maladaptive repair
Canaud, G., Brooks, C. R., Kishi, S., Taguchi, K., Nishimura, K., Magassa, S., Scott, A., Hsiao, L.-L., Ichimura, T., Terzi, F., et al. (2019) · Science Translational Medicine · doi:10.1126/scitranslmed.aav4754 · Cited by 139
Li, S., Lin, Q., Shao, X., Zhu, X., Wu, J., Wu, B., Zhang, M., Zhou, W., Zhou, Y., Jin, H., et al. (2020) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2019.12.005 · Cited by 112
Profibrotic epithelial phenotype: a central role for MRTF and TAZ
Bialik, J. F., Ding, M., Speight, P., Dan, Q., Miranda, M. Z., Di Ciano-Oliveira, C., Kofler, M. M., Rotstein, O. D., Pedersen, S. F., Szászi, K., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-40764-7 · Cited by 41
Liu, J.-H., He, L., Zou, Z.-M., Ding, Z.-C., Zhang, X., Wang, H., Zhou, P., Xie, L., Xing, S., & Yi, C.-Z. (2018) · Kidney and Blood Pressure Research · doi:10.1159/000494745 · Cited by 32
Short and dysfunctional telomeres sensitize the kidneys to develop fibrosis
Saraswati, S., Martínez, P., Graña-Castro, O., & Blasco, M. A. (2021) · Nature Aging · doi:10.1038/s43587-021-00040-8 · Cited by 28
Candidate rejuvenating factor GDF11 and tissue fibrosis: friend or foe?
Frohlich, J., & Vinciguerra, M. (2020) · GeroScience · doi:10.1007/s11357-020-00279-w · Cited by 28
Tampe, B., Tampe, D., Nyamsuren, G., Klöpper, F., Rapp, G., Kauffels, A., Lorf, T., Zeisberg, E. M., Müller, G. A., Kalluri, R., et al. (2018) · Journal of Clinical Investigation · doi:10.1172/jci89632 · Cited by 24
Metadata
- Authors
- Grande, M. T., Sánchez-Laorden, B., López-Blau, C., De Frutos, C. A., Boutet, A., Arévalo, M., Rowe, R. G., Weiss, S. J., López-Novoa, J. M., & Nieto, M. A.
- Venue
- Nature Medicine
- Published
- 2015-08-03
- Volume
- 21
- Issue
- 9
- Pages
- 989-997
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W1215049722
- Cited by
- 783
- References
- 3
- FWCI
- 52.63
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.