The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Inactivation of p53 in breast cancers correlates with stem cell transcriptional signatures
Open accessAbstract
Breast cancer comprises a heterogeneous set of diseases distinguishable from one another by pathologic presentation and molecular signatures. However, each breast cancer subtype is also heterogeneous. Some of the heterogeneity may be attributable to genetic instability, but recent data emphasize that developmental plasticity may also contribute. The p53 tumor suppressor could constitute a nodal control point underlying both sources of heterogeneity because it is frequently inactivated during malignant progression and has recently been shown to function as a potent barrier preventing fully differentiated cells from reverting to pluripotent stem cells after expression of appropriate oncogenes. Using archival microarray datasets, we tested the hypothesis that a p53 mutation could allow cells within a tumor to acquire a stem cell-like state by looking for coordinate expression of stem cell identity genes. We show that breast and lung cancers with p53 mutations do exhibit stem cell-like transcriptional patterns. Such tumors were also depleted for differentiation genes regulated by the polycomb repressor complex 2. These data are consistent with a model in which loss of p53 function enables acquisition of stem cell properties, which are positively selected during tumor progression.
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
Induced Pluripotent Stem Cell Lines Derived from Human Somatic Cells
Yu, J., Vodyanik, M. A., Smuga-Otto, K., Antosiewicz-Bourget, J., Frane, J. L., Tian, S., Nie, J., Jonsdottir, G. A., Ruotti, V., Stewart, R., et al. (2007) · Science · doi:10.1126/science.1151526 · Cited by 10,310
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
Suppression of induced pluripotent stem cell generation by the p53–p21 pathway
Hong, H., Takahashi, K., Ichisaka, T., Aoi, T., Kanagawa, O., Nakagawa, M., Okita, K., & Yamanaka, S. (2009) · Nature · doi:10.1038/nature08235 · Cited by 1,301
Linking the p53 tumour suppressor pathway to somatic cell reprogramming
Kawamura, T., Suzuki, J., Wang, Y. V., Menendez, S., Morera, L. B., Raya, A., Wahl, G. M., & Belmonte, J. C. I. (2009) · Nature · doi:10.1038/nature08311 · Cited by 1,115
Self-citationA p53-mediated DNA damage response limits reprogramming to ensure iPS cell genomic integrity
Marión, R. M., Strati, K., Li, H., Murga, M., Blanco, R., Ortega, S., Fernandez-Capetillo, O., Serrano, M., & Blasco, M. A. (2009) · Nature · doi:10.1038/nature08287 · Cited by 1,028
Senescence impairs successful reprogramming to pluripotent stem cells
Banito, A., Rashid, S. T., Acosta, J. C., Li, S., Pereira, C. F., Geti, I., Pinho, S., Silva, J. C., Azuara, V., Walsh, M., et al. (2009) · Genes & Development · doi:10.1101/gad.1811609 · Cited by 642
Cited by
Greaves, M., & Maley, C. C. (2012) · Nature · doi:10.1038/nature10762 · Cited by 3,162
Kastenhuber, E. R., & Lowe, S. W. (2017) · Cell · doi:10.1016/j.cell.2017.08.028 · Cited by 1,906
Li, M., He, Y., Dubois, W., Wu, X., Shi, J., & Huang, J. (2012) · Molecular Cell · doi:10.1016/j.molcel.2012.01.020 · Cited by 264
p53-Dependent Nestin Regulation Links Tumor Suppression to Cellular Plasticity in Liver Cancer
Tschaharganeh, D. F., Xue, W., Calvisi, D. F., Evert, M., Michurina, T. V., Dow, L. E., Banito, A., Katz, S. F., Kastenhuber, E. R., Weissmueller, S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.05.051 · Cited by 227
Shy, B. R., Wu, C.-I., Khramtsova, G. F., Zhang, J. Y., Olopade, O. I., Goss, K. H., & Merrill, B. J. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.06.001 · Cited by 124
Metadata
- Authors
- Mizuno, H., Spike, B. T., Wahl, G. M., & Levine, A. J.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2010-12-13
- Volume
- 107
- Issue
- 52
- Pages
- 22745-22750
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1992817971
- Cited by
- 160
- References
- 6
- FWCI
- 7.12
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Inactivation of p53 in breast cancers correlates with stem cell transcriptional signatures. https://app.cochat.ai/papers/10.1073/pnas.1017001108
- The paper
- Mizuno, H., Spike, B. T., Wahl, G. M., & Levine, A. J. (2010). Inactivation of p53 in breast cancers correlates with stem cell transcriptional signatures. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1017001108
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.
