The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Increased Expression of P-Glycoprotein and Doxorubicin Chemoresistance of Metastatic Breast Cancer Is Regulated by miR-298
Open accessAbstract
MicroRNAs (miRNAs) are short, noncoding RNA molecules that regulate the expression of a number of genes involved in cancer; therefore, they offer great diagnostic and therapeutic targets. We have developed doxorubicin-resistant and -sensitive metastatic human breast cancer cell lines (MDA-MB-231) to study the chemoresistant mechanisms regulated by miRNAs. We found that doxorubicin localized exclusively to the cytoplasm and was unable to reach the nuclei of resistant tumor cells because of the increased nuclear expression of MDR1/P-glycoprotein (P-gp). An miRNA array between doxorubicin-sensitive and -resistant breast cancer cells showed that reduced expression of miR-298 in doxorubicin-resistant human breast cancer cells was associated with increased expression of P-gp. In a transient transfection experiment, miR-298 directly bound to the MDR1 3' untranslated region and regulated the expression of firefly luciferase reporter in a dose-dependent manner. Overexpression of miR-298 down-regulated P-gp expression, increasing nuclear accumulation of doxorubicin and cytotoxicity in doxorubicin-resistant breast cancer cells. Furthermore, down-regulation of miR-298 increased P-gp expression and induced doxorubicin resistance in sensitive breast cancer cells. In summary, these results suggest that miR-298 directly modulates P-gp expression and is associated with the chemoresistant mechanisms of metastatic human breast cancer. Therefore, miR-298 has diagnostic and therapeutic potential for predicting doxorubicin chemoresistance in human breast cancer.
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
Multidrug resistance in cancer: role of ATP–dependent transporters
Gottesman, M. M., Fojo, T., & Bates, S. E. (2002) · Nature Reviews Cancer · doi:10.1038/nrc706 · Cited by 5,536
Targeting multidrug resistance in cancer
Szakács, G., Paterson, J. K., Ludwig, J. A., Booth-Genthe, C., & Gottesman, M. M. (2006) · Nature Reviews Drug Discovery · doi:10.1038/nrd1984 · Cited by 3,609
Processing of primary microRNAs by the Microprocessor complex
Denli, A. M., Tops, B. B. J., Plasterk, R. H. A., Ketting, R. F., & Hannon, G. J. (2004) · Nature · doi:10.1038/nature03049 · Cited by 2,784
Stark, A., Brennecke, J., Bushati, N., Russell, R. B., & Cohen, S. M. (2005) · Cell · doi:10.1016/j.cell.2005.11.023 · Cited by 1,080
Epigenetics as a mechanism driving polygenic clinical drug resistance
Glasspool, R. M., Teodoridis, J. M., & Brown, R. (2006) · British Journal of Cancer · doi:10.1038/sj.bjc.6603024 · Cited by 236
Cited by
Li, W., Zhang, H., Assaraf, Y. G., Zhao, K., Xu, X., Xie, J., Yang, D.-H., & Chen, Z.-S. (2016) · Drug Resistance Updates · doi:10.1016/j.drup.2016.05.001 · Cited by 673
Genovese, I., Ilari, A., Assaraf, Y. G., Fazi, F., & Colotti, G. (2017) · Drug Resistance Updates · doi:10.1016/j.drup.2017.10.003 · Cited by 156
Maiti, C., Parida, S., Kayal, S., Maiti, S., Mandal, M., & Dhara, D. (2018) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.7b18245 · Cited by 75
MiR-139-5p: promising biomarker for cancer
Zhang, H.-D., Jiang, L.-H., Sun, D.-W., Li, J., & Tang, J.-H. (2015) · Tumor Biology · doi:10.1007/s13277-015-3199-3 · Cited by 69
Lal, S., Sutiman, N., Ooi, L. L., Wong, Z. W., Wong, N. S., Ang, P. C. S., & Chowbay, B. (2017) · The Pharmacogenomics Journal · doi:10.1038/tpj.2016.17 · Cited by 26
Breast cancer: miRNAs monitoring chemoresistance and systemic therapy
Singh, S., Saini, H., Sharma, A., Gupta, S., Huddar, V. G., & Tripathi, R. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1155254 · Cited by 25
Wang, Y., Tu, M.-J., & Yu, A.-M. (2024) · Frontiers in Pharmacology · doi:10.3389/fphar.2024.1423416 · Cited by 21
Metadata
- Authors
- Bao, L., Hazari, S., Mehra, S., Kaushal, D., Moroz, K., & Dash, S.
- Venue
- The American Journal of Pathology
- Publisher
- Elsevier BV
- Published
- 2012-06
- Volume
- 180
- Issue
- 6
- Pages
- 2490-2503
- ISSN
- 0002-9440 (ISSN-L)
- OpenAlex
- W2064840895
- Cited by
- 275
- References
- 5
- FWCI
- 8.52
- Type
- journal article
- Language
- en
- Open access
- hybrid
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.