The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
miR-221 overexpression contributes to liver tumorigenesis
Open accessAbstract
MicroRNA (miRNAs) are negative regulators of gene expression and can function as tumor suppressors or oncogenes. Expression patterns of miRNAs and their role in the pathogenesis of hepatocellular carcinoma (HCC) are still poorly understood. We profiled miRNA expression in tissue samples (104 HCC, 90 adjacent cirrhotic livers, 21 normal livers) as well as in 35 HCC cell lines. A set of 12 miRNAs (including miR-21, miR-221/222, miR-34a, miR-519a, miR-93, miR-96, and let-7c) was linked to disease progression from normal liver through cirrhosis to full-blown HCC. miR-221/222, the most up-regulated miRNAs in tumor samples, are shown to target the CDK inhibitor p27 and to enhance cell growth in vitro. Conversely, these activities can be efficiently inhibited by an antagomiR specific for miR-221. In addition, we show, using a mouse model of liver cancer, that miR-221 overexpression stimulates growth of tumorigenic murine hepatic progenitor cells. Finally, we identified DNA damage-inducible transcript 4 (DDIT4), a modulator of mTOR pathway, as a bona fide target of miR-221. Taken together, these data reveal an important contribution for miR-221 in hepatocarcinogenesis and suggest a role for DDIT4 dysregulation in this process. Thus, the use of synthetic inhibitors of miR-221 may prove to be a promising approach to liver cancer treatment.
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
1 retracted
Zhao, J.-J., Lin, J., Yang, H., Kong, W., He, L., Ma, X., Coppola, D., & Cheng, J. Q. (2008) · Journal of Biological Chemistry · doi:10.1074/jbc.m806041200 · Cited by 509
RetractedA microRNA expression signature of human solid tumors defines cancer gene targets
Volinia, S., Calin, G. A., Liu, C.-G., Ambs, S., Cimmino, A., Petrocca, F., Visone, R., Iorio, M., Roldo, C., Ferracin, M., et al. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0510565103 · Cited by 5,697
Self-citationOrigins and Mechanisms of miRNAs and siRNAs
Carthew, R. W., & Sontheimer, E. J. (2009) · Cell · doi:10.1016/j.cell.2009.01.035 · Cited by 5,018
The impact of microRNAs on protein output
Baek, D., Villén, J., Shin, C., Camargo, F. D., Gygi, S. P., & Bartel, D. P. (2008) · Nature · doi:10.1038/nature07242 · Cited by 3,592
MicroRNA-21 Regulates Expression of the PTEN Tumor Suppressor Gene in Human Hepatocellular Cancer
Meng, F., Henson, R., Wehbe–Janek, H., Ghoshal, K., Jacob, S. T., & Patel, T. (2007) · Gastroenterology · doi:10.1053/j.gastro.2007.05.022 · Cited by 2,773
Primary liver cancer: Worldwide incidence and trends
Bosch, F. X., Ribes, J., Díaz, M., & Cléries, R. (2004) · Gastroenterology · doi:10.1053/j.gastro.2004.09.011 · Cited by 2,477
Impaired microRNA processing enhances cellular transformation and tumorigenesis
Kumar, M. S., Lu, J., Mercer, K. L., Golub, T. R., & Jacks, T. (2007) · Nature Genetics · doi:10.1038/ng2003 · Cited by 1,463
Transcriptional Activation of miR-34a Contributes to p53-Mediated Apoptosis
Raver-Shapira, N., Marciano, E., Meiri, E., Spector, Y., Rosenfeld, N., Moskovits, N., Bentwich, Z., & Oren, M. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.05.017 · Cited by 1,352
The role of microRNA genes in papillary thyroid carcinoma
He, H., Jazdzewski, K., Li, W., Liyanarachchi, S., Nagy, R., Volinia, S., Calin, G. A., Liu, C.-G., Franssila, K., Suster, S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0509603102 · Cited by 1,215
Self-citationMurakami, Y., Yasuda, T., Saigo, K., Urashima, T., Toyoda, H., Okanoue, T., & Shimotohno, K. (2006) · Oncogene · doi:10.1038/sj.onc.1209283 · Cited by 1,147
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
Bretones, G., Delgado, M. D., & León, J. (2015) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2014.03.013 · Cited by 747
microRNA-29 can regulate expression of the long non-coding RNA gene MEG3 in hepatocellular cancer
Braconi, C., Kogure, T., Valeri, N., Huang, N., Nuovo, G., Costinean, S., Negrini, M., Miotto, E., Croce, C. M., & Patel, T. (2011) · Oncogene · doi:10.1038/onc.2011.193 · Cited by 642
Self-citationXu, J., Wu, C., Che, X., Wang, L., Yu, D., Zhang, T., Huang, L., Li, H., Tan, W., Wang, C., et al. (2011) · Molecular Carcinogenesis · doi:10.1002/mc.20712 · Cited by 567
Metadata
- Authors
- Pineau, P., Volinia, S., McJunkin, K., Marchio, A., Battiston, C., Terris, B., Mazzaferro, V., Lowe, S. W., Croce, C. M., & Dejean, A.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2009-12-29
- Volume
- 107
- Issue
- 1
- Pages
- 264-269
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1987851658
- Cited by
- 699
- References
- 33
- FWCI
- 15.73
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: miR-221 overexpression contributes to liver tumorigenesis. https://app.cochat.ai/papers/10.1073/pnas.0907904107
- The paper
- Pineau, P., Volinia, S., McJunkin, K., Marchio, A., Battiston, C., Terris, B., Mazzaferro, V., Lowe, S. W., Croce, C. M., & Dejean, A. (2010). miR-221 overexpression contributes to liver tumorigenesis. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0907904107
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.