The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Fat1 deletion promotes hybrid EMT state, tumour stemness and metastasis
Open accessAbstract
FAT1, which encodes a protocadherin, is one of the most frequently mutated genes in human cancers1–5. However, the role and the molecular mechanisms by which FAT1 mutations control tumour initiation and progression are poorly understood. Here, using mouse models of skin squamous cell carcinoma and lung tumours, we found that deletion of Fat1 accelerates tumour initiation and malignant progression and promotes a hybrid epithelial-to-mesenchymal transition (EMT) phenotype. We also found this hybrid EMT state in FAT1-mutated human squamous cell carcinomas. Skin squamous cell carcinomas in which Fat1 was deleted presented increased tumour stemness and spontaneous metastasis. We performed transcriptional and chromatin profiling combined with proteomic analyses and mechanistic studies, which revealed that loss of function of FAT1 activates a CAMK2–CD44–SRC axis that promotes YAP1 nuclear translocation and ZEB1 expression that stimulates the mesenchymal state. This loss of function also inactivates EZH2, promoting SOX2 expression, which sustains the epithelial state. Our comprehensive analysis identified drug resistance and vulnerabilities in FAT1-deficient tumours, which have important implications for cancer therapy. Our studies reveal that, in mouse and human squamous cell carcinoma, loss of function of FAT1 promotes tumour initiation, progression, invasiveness, stemness and metastasis through the induction of a hybrid EMT state. In mouse and human squamous cell carcinoma, loss of function of FAT1 promotes tumour initiation, malignant progression and metastasis through the activation of a hybrid epithelial-to-mesenchymal transition phenotype.
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
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
Discovery and saturation analysis of cancer genes across 21 tumour types
Lawrence, M. S., Stojanov, P., Mermel, C. H., Robinson, J. T., Garraway, L. A., Golub, T. R., Meyerson, M., Gabriel, S. B., Lander, E. S., & Getz, G. (2014) · Nature · doi:10.1038/nature12912 · Cited by 3,096
Pan-cancer analysis of whole genomes
The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium, Aaltonen, L. A., Abascal, F., Abeshouse, A., Aburatani, H., Adams, D. J., Agrawal, N., Ahn, K. S., Ahn, S.-M., Aikata, H., et al. (2020) · Nature · doi:10.1038/s41586-020-1969-6 · Cited by 3,064
Self-citationEMT Transition States during Tumor Progression and Metastasis
Pastushenko, I., & Blanpain, C. (2019) · Trends in Cell Biology · doi:10.1016/j.tcb.2018.12.001 · Cited by 2,876
Self-citationIdentification of the tumour transition states occurring during EMT
Pastushenko, I., Brisebarre, A., Sifrim, A., Fioramonti, M., Revenco, T., Boumahdi, S., Van Keymeulen, A., Brown, D., Moers, V., Lemaire, S., et al. (2018) · Nature · doi:10.1038/s41586-018-0040-3 · Cited by 1,495
Self-citationMechanobiology of YAP and TAZ in physiology and disease
Panciera, T., Azzolin, L., Cordenonsi, M., & Piccolo, S. (2017) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2017.87 · Cited by 1,461
Planchard, D., Smit, E. F., Groen, H. J. M., Mazieres, J., Besse, B., Helland, Å., Giannone, V., D'Amelio, A. M., Zhang, P., Mookerjee, B., et al. (2017) · The Lancet Oncology · doi:10.1016/s1470-2045(17)30679-4 · Cited by 1,360
The biology and role of CD44 in cancer progression: Therapeutic implications
Chen, C., Zhao, S., Karnad, A., & Freeman, J. W. (2018) · Journal of Hematology & Oncology · doi:10.1186/s13045-018-0605-5 · Cited by 1,245
SOX2 controls tumour initiation and cancer stem-cell functions in squamous-cell carcinoma
Boumahdi, S., Driessens, G., Lapouge, G., Rorive, S., Nassar, D., Le Mercier, M., Delatte, B., Caauwe, A., Lenglez, S., Nkusi, E., et al. (2014) · Nature · doi:10.1038/nature13305 · Cited by 656
Self-citationLoss of the FAT1 Tumor Suppressor Promotes Resistance to CDK4/6 Inhibitors via the Hippo Pathway
Li, Z., Razavi, P., Li, Q., Toy, W., Liu, B., Ping, C., Hsieh, W., Sanchez-Vega, F., Brown, D. N., Da Cruz Paula, A. F., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.11.006 · Cited by 508
Cited by
Gerstberger, S., Jiang, Q., & Ganesh, K. (2023) · Cell · doi:10.1016/j.cell.2023.03.003 · Cited by 913
Rational combinations of targeted cancer therapies: background, advances and challenges
Jin, H., Wang, L., & Bernards, R. (2023) · Nature Reviews Drug Discovery · doi:10.1038/s41573-022-00615-z · Cited by 503
Zhong, Q., Xiao, X., Qiu, Y., Xu, Z., Chen, C., Chong, B., Zhao, X., Hai, S., Li, S., An, Z., et al. (2023) · MedComm · doi:10.1002/mco2.261 · Cited by 442
Tumor initiation and early tumorigenesis: molecular mechanisms and interventional targets
Zhang, S., Xiao, X., Yi, Y., Wang, X., Zhu, L., Shen, Y., Lin, D., & Wu, C. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01848-7 · Cited by 399
Metastasis-Initiating Cells and Ecosystems
Massagué, J., & Ganesh, K. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0010 · Cited by 372
Metadata
- Authors
- Pastushenko, I., Mauri, F., Song, Y., de Cock, F., Meeusen, B., Swedlund, B., Impens, F., Van Haver, D., Opitz, M., Thery, M., Bareche, Y., Lapouge, G., Vermeersch, M., Van Eycke, Y.-R., Balsat, C., Decaestecker, C., Sokolow, Y., Hassid, S., Perez-Bustillo, A., Agreda-Moreno, B., Rios-Buceta, L., Jaen, P., Redondo, P., Sieira-Gil, R., Millan-Cayetano, J. F., Sanmatrtin, O., D’Haene, N., Moers, V., Rozzi, M., Blondeau, J., Lemaire, S., Scozzaro, S., Janssens, V., De Troya, M., Dubois, C., Pérez-Morga, D., Salmon, I., Sotiriou, C., Helmbacher, F., & Blanpain, C.
- Venue
- Nature
- Published
- 2020-12-16
- Volume
- 589
- Issue
- 7842
- Pages
- 448-455
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W3111182037
- Cited by
- 429
- References
- 28
- FWCI
- 19.25
- Type
- journal article
- Language
- en
- Open access
- bronze
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Fat1 deletion promotes hybrid EMT state, tumour stemness and metastasis. https://app.cochat.ai/papers/10.1038/s41586-020-03046-1
- The paper
- Pastushenko, I., Mauri, F., Song, Y., de Cock, F., Meeusen, B., Swedlund, B., Impens, F., Van Haver, D., Opitz, M., Thery, M., Bareche, Y., Lapouge, G., Vermeersch, M., Van Eycke, Y.-R., Balsat, C., Decaestecker, C., Sokolow, Y., Hassid, S., Perez-Bustillo, A., . . . Blanpain, C. (2021). Fat1 deletion promotes hybrid EMT state, tumour stemness and metastasis. Nature. https://doi.org/10.1038/s41586-020-03046-1
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.
