The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
The microRNA miR-34a inhibits prostate cancer stem cells and metastasis by directly repressing CD44
Open accessAbstract
Cancer stem cells (CSCs), or tumor-initiating cells, are involved in tumor progression and metastasis. MicroRNAs (miRNAs) regulate both normal stem cells and CSCs, and dysregulation of miRNAs has been implicated in tumorigenesis. CSCs in many tumors—including cancers of the breast, pancreas, head and neck, colon, small intestine, liver, stomach, bladder and ovary—have been identified using the adhesion molecule CD44, either individually or in combination with other marker(s). Prostate CSCs with enhanced clonogenic and tumor-initiating and metastatic capacities are enriched in the CD44+ cell population, but whether miRNAs regulate CD44+ prostate cancer cells and prostate cancer metastasis remains unclear. Here we show, through expression analysis, that miR-34a, a p53 target, was underexpressed in CD44+ prostate cancer cells purified from xenograft and primary tumors. Enforced expression of miR-34a in bulk or purified CD44+ prostate cancer cells inhibited clonogenic expansion, tumor regeneration, and metastasis. In contrast, expression of miR-34a antagomirs in CD44− prostate cancer cells promoted tumor development and metastasis. Systemically delivered miR-34a inhibited prostate cancer metastasis and extended survival of tumor-bearing mice. We identified and validated CD44 as a direct and functional target of miR-34a and found that CD44 knockdown phenocopied miR-34a overexpression in inhibiting prostate cancer regeneration and metastasis. Our study shows that miR-34a is a key negative regulator of CD44+ prostate cancer cells and establishes a strong rationale for developing miR-34a as a novel therapeutic agent against prostate CSCs.
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
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
Transactivation 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
The miR-34 family in cancer and apoptosis
Hermeking, H. (2010) · Cell Death & Differentiation · doi:10.1038/cdd.2009.56 · Cited by 1,236
Cited by
MicroRNA therapeutics: towards a new era for the management of cancer and other diseases
Rupaimoole, R., & Slack, F. J. (2017) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2016.246 · Cited by 4,741
The role of non-coding RNAs in oncology
Slack, F. J., & Chinnaiyan, A. M. (2019) · Cell · doi:10.1016/j.cell.2019.10.017 · Cited by 1,619
Noncoding RNA therapeutics—Challenges and potential solutions
Winkle, M., El-Daly, S. M., Fabbri, M., & Calin, G. A. (2021) · Nature Reviews Drug Discovery · doi:10.1038/s41573-021-00219-z · Cited by 1,551
The translational landscape of mTOR signalling steers cancer initiation and metastasis
Hsieh, A. C., Liu, Y., Edlind, M. P., Ingolia, N. T., Janes, M. R., Sher, A., Shi, E. Y., Stumpf, C. R., Christensen, C., Bonham, M. J., et al. (2012) · Nature · doi:10.1038/nature10912 · Cited by 1,313
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
Extracellular matrix and its therapeutic potential for cancer treatment
Huang, J., Zhang, L., Wan, D., Zhou, L., Zheng, S., Lin, S., & Qiao, Y. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00544-0 · Cited by 962
MicroRNAs en route to the clinic: progress in validating and targeting microRNAs for cancer therapy
Kasinski, A. L., & Slack, F. J. (2011) · Nature Reviews Cancer · doi:10.1038/nrc3166 · Cited by 936
microRNAs in cancer management
Kong, Y. W., Ferland-McCollough, D., Jackson, T. J., & Bushell, M. (2012) · The Lancet Oncology · doi:10.1016/s1470-2045(12)70073-6 · Cited by 734
MicroRNAs in the p53 network: micromanagement of tumour suppression
Hermeking, H. (2012) · Nature Reviews Cancer · doi:10.1038/nrc3318 · Cited by 518
Translational Control in Cancer Etiology
Ruggero, D. (2013) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a012336 · Cited by 367
Adult-specific functions of animal microRNAs
Sun, K., & Lai, E. C. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3471 · Cited by 334
Qin, J., Liu, X., Laffin, B., Chen, X., Choy, G., Jeter, C. R., Calhoun-Davis, T., Li, H., Palapattu, G. S., Pang, S., et al. (2012) · Cell Stem Cell · doi:10.1016/j.stem.2012.03.009 · Cited by 317
Self-citationLi, L., Yuan, L., Luo, J., Gao, J., Guo, J., & Xie, X. (2013) · Clinical and Experimental Medicine · doi:10.1007/s10238-012-0186-5 · Cited by 314
Control of metastatic progression by microRNA regulatory networks
Pencheva, N., & Tavazoie, S. F. (2013) · Nature Cell Biology · doi:10.1038/ncb2769 · Cited by 295
MicroRNA-34a: a potential therapeutic target in human cancer
Li, X. J., Ren, Z. J., & Tang, J. H. (2014) · Cell Death & Disease · doi:10.1038/cddis.2014.270 · Cited by 287
Devulapally, R., Sekar, N. M., Sekar, T. V., Foygel, K., Massoud, T. F., Willmann, J. K., & Paulmurugan, R. (2015) · ACS Nano · doi:10.1021/nn507465d · Cited by 260
Cancer Stem Cell Hierarchy in Glioblastoma Multiforme
Bradshaw, A., Wickremsekera, A., Tan, S. T., Peng, L., Davis, P. F., & Itinteang, T. (2016) · Frontiers in Surgery · doi:10.3389/fsurg.2016.00021 · Cited by 258
Extracellular matrix stiffness: Mechanisms in tumor progression and therapeutic potential in cancer
Zhang, M., & Zhang, B. (2025) · Experimental Hematology & Oncology · doi:10.1186/s40164-025-00647-2 · Cited by 269
“Indirect MMP inhibitors include blockade of signal transduction pathways (such as MAPK or ERK pathways [141]), and gene therapy (such as inhibition of miRNA expression [51]) to achieve the inhibition of MMP [142].”
MicroRNA-based therapeutics in central nervous system injuries
Sun, P., Liu, D. Z., Jickling, G. C., Sharp, F. R., & Yin, K.-J. (2018) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x18773871 · Cited by 228
MiR-137: an important player in neural development and neoplastic transformation
Mahmoudi, E., & Cairns, M. J. (2017) · Molecular Psychiatry · doi:10.1038/mp.2016.150 · Cited by 198
Carvajal, L. A., Hamard, P.-J., Tonnessen, C., & Manfredi, J. J. (2012) · Genes & Development · doi:10.1101/gad.184911.111 · Cited by 151
The role of microRNAs in the regulation of cancer stem cells
Takahashi, R.-U., Miyazaki, H., & Ochiya, T. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2013.00295 · Cited by 118
The comprehensive landscape of miR-34a in cancer research
Li, S., Wei, X., He, J., Cao, Q., Du, D., Zhan, X., Zeng, Y., Yuan, S., & Sun, L. (2021) · Cancer and Metastasis Reviews · doi:10.1007/s10555-021-09973-3 · Cited by 84
MicroRNAs as therapeutic targets and their potential applications in cancer therapy
Cho, W. C. (2012) · Expert Opinion on Therapeutic Targets · doi:10.1517/14728222.2012.696102 · Cited by 70
Zhu, C., Zhang, H., Li, W., Luo, L., Guo, X., Wang, Z., Kong, F., Li, Q., Yang, J., Du, Y., et al. (2018) · Biomaterials · doi:10.1016/j.biomaterials.2018.01.043 · Cited by 53
Han, F., Huang, D., Huang, X., Wang, W., Yang, S., & Chen, S. (2020) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.15402 · Cited by 42
The emerging functions of the p53-miRNA network in stem cell biology
Lin, C.-P., Choi, Y. J., Hicks, G. G., & He, L. (2012) · Cell Cycle · doi:10.4161/cc.20207 · Cited by 38
Vidal, J.-S., Dufouil, C., Ducros, V., & Tzourio, C. (2008) · Neuroepidemiology · doi:10.1159/000126914 · Cited by 32
Metadata
- Authors
- Liu, C., Kelnar, K., Liu, B., Chen, X., Calhoun-Davis, T., Li, H., Patrawala, L., Yan, H., Jeter, C., Honorio, S., Wiggins, J. F., Bader, A. G., Fagin, R., Brown, D., & Tang, D. G.
- Venue
- Nature Medicine
- Published
- 2011-01-16
- Volume
- 17
- Issue
- 2
- Pages
- 211-215
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W2170685293
- Cited by
- 1,400
- References
- 3
- FWCI
- 46.61
- 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.