The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
A positive feedback between p53 and miR-34 miRNAs mediates tumor suppression
Open accessAbstract
As bona fide p53 transcriptional targets, miR-34 microRNAs (miRNAs) exhibit frequent alterations in many human tumor types and elicit multiple p53 downstream effects upon overexpression. Unexpectedly, miR-34 deletion alone fails to impair multiple p53-mediated tumor suppressor effects in mice, possibly due to the considerable redundancy in the p53 pathway. Here, we demonstrate that miR-34a represses HDM4 , a potent negative regulator of p53, creating a positive feedback loop acting on p53. In a Kras -induced mouse lung cancer model, miR-34a deficiency alone does not exhibit a strong oncogenic effect. However, miR-34a deficiency strongly promotes tumorigenesis when p53 is haploinsufficient, suggesting that the defective p53– miR-34 feedback loop can enhance oncogenesis in a specific context. The importance of the p53/ miR-34 /HDM4 feedback loop is further confirmed by an inverse correlation between miR-34 and full-length HDM4 in human lung adenocarcinomas. In addition, human lung adenocarcinomas generate an elevated level of a short HDM4 isoform through alternative polyadenylation. This short HDM4 isoform lacks miR-34 -binding sites in the 3′ untranslated region (UTR), thereby evading miR-34 regulation to disable the p53- miR-34 positive feedback. Taken together, our results elucidated the intricate cross-talk between p53 and miR-34 miRNAs and revealed an important tumor suppressor effect generated by this positive feedback loop.
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Cites
MicroRNAs: Target Recognition and Regulatory Functions
Bartel, D. P. (2009) · Cell · doi:10.1016/j.cell.2009.01.002 · Cited by 20,068
The functions of animal microRNAs
Ambros, V. (2004) · Nature · doi:10.1038/nature02871 · Cited by 10,728
Prediction of Mammalian MicroRNA Targets
Lewis, B. P., Shih, I.-H., Jones-Rhoades, M. W., Bartel, D. P., & Burge, C. B. (2003) · Cell · doi:10.1016/s0092-8674(03)01018-3 · Cited by 5,199
Blinded by the Light: The Growing Complexity of p53
Vousden, K. H., & Prives, C. (2009) · Cell · doi:10.1016/j.cell.2009.04.037 · Cited by 3,163
A microRNA component of the p53 tumour suppressor network
He, L., He, X., Lim, L. P., de Stanchina, E., Xuan, Z., Liang, Y., Xue, W., Zender, L., Magnus, J., Ridzon, D., et al. (2007) · Nature · doi:10.1038/nature05939 · Cited by 2,692
Self-citationTransactivation of miR-34a by p53 broadly influences gene expression and promotes apoptosis
Chang, T.-C., Wentzel, E. A., Kent, O. A., Ramachandran, K., Mullendore, M., Lee, K. H., Feldmann, G., Yamakuchi, M., Ferlito, M., Lowenstein, C. J., et al. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.05.010 · Cited by 2,010
Transcriptional control of human p53-regulated genes
Riley, T., Sontag, E., Chen, P., & Levine, A. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2395 · Cited by 1,921
Kruse, J.-P., & Gu, W. (2009) · Cell · doi:10.1016/j.cell.2009.04.050 · Cited by 1,610 · cited 1×
“While Mdm2 acts as an ubiquitin E3 ligase that promotes p53 protein degradation via polyubiquitination (Eischen and Lozano 2009; Kruse and Gu 2009), Mdm4 does not possess E3 ubiquitin ligase activity by itself.”
BackgroundMDM2, MDMX and p53 in oncogenesis and cancer therapy
Wade, M., Li, Y.-C., & Wahl, G. M. (2013) · Nature Reviews Cancer · doi:10.1038/nrc3430 · Cited by 1,279
The miR-34 family in cancer and apoptosis
Hermeking, H. (2010) · Cell Death & Differentiation · doi:10.1038/cdd.2009.56 · Cited by 1,236
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Loss of p53 triggers WNT-dependent systemic inflammation to drive breast cancer metastasis
Wellenstein, M. D., Coffelt, S. B., Duits, D. E. M., van Miltenburg, M. H., Slagter, M., de Rink, I., Henneman, L., Kas, S. M., Prekovic, S., Hau, C.-S., et al. (2019) · Nature · doi:10.1038/s41586-019-1450-6 · Cited by 500
Therapeutic advances of miRNAs: A preclinical and clinical update
Chakraborty, C., Sharma, A. R., Sharma, G., & Lee, S.-S. (2021) · Journal of Advanced Research · doi:10.1016/j.jare.2020.08.012 · Cited by 402
miR-34/449 miRNAs are required for motile ciliogenesis by repressing CP110
Song, R., Walentek, P., Sponer, N., Klimke, A., Lee, J. S., Dixon, G., Harland, R., Wan, Y., Lishko, P., Lize, M., et al. (2014) · Nature · doi:10.1038/nature13413 · Cited by 228
Self-citationMicroRNAs in the etiology of colorectal cancer: Pathways and clinical implications
Strubberg, A. M., & Madison, B. B. (2017) · Disease Models & Mechanisms · doi:10.1242/dmm.027441 · Cited by 147
Metadata
- Authors
- Okada, N., Lin, C.-P., Ribeiro, M. C., Biton, A., Lai, G., He, X., Bu, P., Vogel, H., Jablons, D. M., Keller, A. C., Wilkinson, J. E., He, B., Speed, T. P., & He, L.
- Venue
- Genes & Development
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2014-02-14
- Volume
- 28
- Issue
- 5
- Pages
- 438-450
- ISSN
- 0890-9369 (ISSN-L)
- 1549-5477
- OpenAlex
- W2037647570
- Cited by
- 297
- References
- 17
- Type
- posted content
- Language
- en
- Open access
- diamond
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- Okada, N., Lin, C.-P., Ribeiro, M. C., Biton, A., Lai, G., He, X., Bu, P., Vogel, H., Jablons, D. M., Keller, A. C., Wilkinson, J. E., He, B., Speed, T. P., & He, L. (2014). A positive feedback between p53 and miR-34 miRNAs mediates tumor suppression. Genes & Development. https://doi.org/10.1101/gad.233585.113
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