The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Maternally Expressed Gene 3 (MEG3) Noncoding Ribonucleic Acid: Isoform Structure, Expression, and Functions
Open accessAbstract
Maternally expressed gene 3 (MEG3) is an imprinted gene highly expressed in the human pituitary. However, MEG3 expression is lost in human gonadotroph-derived pituitary adenomas and most human tumor cell lines. Expression of MEG3 in tumor cells results in growth suppression, p53 protein increase, and activation of p53 downstream targets. The MEG3 gene encodes a noncoding RNA of approximately 1700 nucleotides. There are 12 different MEG3 gene transcripts, generated by alternative splicing. They contain the common exons 1-3 and exons 8-10, but each uses one or more exons 4-7 in a different combination in the middle. MEG3 isoform expression patterns are tissue and cell type specific. Functionally, each isoform stimulates p53-mediated transactivation and suppresses tumor cell growth. We analyzed the secondary RNA folding structure of each MEG3 isoform, using the computer program mfold. All MEG3 RNA isoforms contain three distinct secondary folding motifs M1, M2, and M3. Deletion analysis showed that motifs M2 and M3 are important for p53 activation. Furthermore, a hybrid MEG3 RNA, containing a piece of artificially synthesized sequence different from the wild type but folding into a similar secondary structure, retained the functions of both p53 activation and growth suppression. These results support the hypothesis that a proper folding structure of the MEG3 RNA molecule is critical for its biological functions. This study establishes for the first time the structure-function relationship of a large noncoding RNA and provides a first look into the molecular mechanisms of the biological functions of a large noncoding RNA.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Maternally expressed gene 3 (MEG3), also known as gene trap locus 2 (Gtl2), is an imprinted gene located on chromosome 14q32.3 in humans and functions as a lncRNA19.”
From Long non-coding RNA MEG3 functions as a competing endogenous RNA to regulate ischemic neuronal death by targeting miR-21/PDCD4 signaling pathway (2017) · cites this paper as [19]
Experimental — accuracy not yet measured
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
Mfold web server for nucleic acid folding and hybridization prediction
Zuker, M. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg595 · Cited by 13,404
Mathews, D. H., Sabina, J., Zuker, M., & Turner, D. H. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.2700 · Cited by 3,795
The chemical repertoire of natural ribozymes
Doudna, J. A., & Cech, T. R. (2002) · Nature · doi:10.1038/418222a · Cited by 745
Activation of p53 by MEG3 Non-coding RNA
Zhou, Y., Zhong, Y., Wang, Y., Zhang, X., Batista, D. L., Gejman, R., Ansell, P. J., Zhao, J. C., Weng, C., & Klibanski, A. (2007) · Journal of Biological Chemistry · doi:10.1074/jbc.m702029200 · Cited by 665
Self-citationA Pituitary-Derived MEG3 Isoform Functions as a Growth Suppressor in Tumor Cells
Zhang, X., Zhou, Y., Mehta, K. R., Danila, D. C., Scolavino, S., Johnson, S. R., & Klibanski, A. (2003) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2003-030222 · Cited by 436
Self-citationMiyoshi, N., Wagatsuma, H., Wakana, S., Shiroishi, T., Nomura, M., Aisaka, K., Kohda, T., Surani, M. A., Kaneko‐Ishino, T., & Ishino, F. (2000) · Genes to Cells · doi:10.1046/j.1365-2443.2000.00320.x · Cited by 385
The Dlk1 and Gtl2 genes are linked and reciprocally imprintedPreprint
Schmidt, J. V., Matteson, P. G., Jones, B. K., Guan, X.-J., & Tilghman, S. M. (2000) · Genes & Development · doi:10.1101/gad.14.16.1997 · Cited by 310
Kagami, M., Sekita, Y., Nishimura, G., Irie, M., Kato, F., Okada, M., Yamamori, S., Kishimoto, H., Nakayama, M., Tanaka, Y., et al. (2008) · Nature Genetics · doi:10.1038/ng.2007.56 · Cited by 291
Takada, S., Tevendale, M., Baker, J., Georgiades, P., Campbell, E., Freeman, T. C., Johnson, M. H., Paulsen, M., & Ferguson‐Smith, A. C. (2000) · Current Biology · doi:10.1016/s0960-9822(00)00704-1 · Cited by 226
Takada, S. (2002) · Human Molecular Genetics · doi:10.1093/hmg/11.1.77 · Cited by 219
Flagged first, then by citations
Cited by
Sorted by citations
Items 301–326 of 326
Pathogenesis of Pituitary Adenomas
Tang, S., Albani, A., & Theodoropoulou, M. (2022) · Springer eBooks · doi:10.1007/978-3-030-90475-3_3
Research Advancements of Long Non-Coding RNA MEG3 in Tumor
周, 晶. (2018) · Advances in Clinical Medicine · doi:10.12677/acm.2018.85075
Advances in the Research of Long Non-Coding RNA Regulation Mechanism in Liver Cancer
崔, 凯. (2018) · World Journal of Cancer Research · doi:10.12677/wjcr.2018.83016
Liu, Q., Dong, J., Li, J., Duan, Y., Wang, K., Kong, Q., & Zhang, H. (2020) · doi:10.21203/rs.3.rs-25878/v1
Hosseini, E. S., Zarei, M. A., Kashani, N. R., Kashani, H. H., & Nikzad, H. (2022) · Research Square · doi:10.21203/rs.3.rs-1912032/v1
Highlighting the role of phospholipase A2 and noncoding RNA in colorectal cancer
Shruthi, N. R., Esmeeta, A., Banerjee, A., & Pathak, S. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-95698-7.00019-x
lncRNA MALAT1, MEG3, and PANDAR Levels may be Potential Diagnostic Biomarkers in Multiple Myeloma
ÖZDİNÇ, E. E., Öztürk, K. H., İçduygu, F. M., & Özbalcı, D. (2023) · Medical Records · doi:10.37990/medr.1309886
Esmaeili, F., Amini, A., & Golpich, M. (2023) · Research Square · doi:10.21203/rs.3.rs-3370781/v1
Obesity and noncoding RNAs in epigenetic inheritance of metabolic disease
Zhang, Q., Ren, Y., Wu, Y., & Zeng, Y. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-18979-1.00010-1
Uusi-Mäkelä, J., Kauppinen, M., Seppälä, J., Jaatinen, S., Ryback, B. A., Rantapero, T., Rodriguez-Martinez, A., Nykter, M., & Rautajoki, K. J. (2025) · Scientific Reports · doi:10.1038/s41598-025-99984-9
Hashemi, M., Salimian, N., Sharifi, N., Asheghabadi, P. S., Zarearandi, Z., Abdi, F., Akbar, S. S., Shirazi, R. M., Pozve, M. B., Nikdehqan, A., et al. (2025) · Cancer Cell International · doi:10.1186/s12935-025-03999-1
Hosseini, E. S., Zarei, M. A., Shabani, Z., Kashani, H. H., & Nikzad, H. (2025) · Current Research in Pharmacology and Drug Discovery · doi:10.1016/j.crphar.2025.100243
Li, Y., Lou, S., Zhang, J., Zhao, S., & Lou, G. (2024) · Figshare · doi:10.6084/m9.figshare.26673846
Additional file 1 of DNMT1 facilitates growth of breast cancer by inducing MEG3 hyper-methylation
Zhu, X., Lv, L., Mingzheng, W., Fan, C., Lu, X., Jin, M., Li, S., & Wang, F. (2022) · Figshare · doi:10.6084/m9.figshare.19113030
Li, Y., Lou, S., Zhang, J., Zhao, S., & Lou, G. (2024) · Figshare · doi:10.6084/m9.figshare.26673855
Li, Y., Lou, S., Zhang, J., Zhao, S., & Lou, G. (2024) · Figshare · doi:10.6084/m9.figshare.26673852
Li, Y., Lou, S., Zhang, J., Zhao, S., & Lou, G. (2024) · Figshare · doi:10.6084/m9.figshare.26673849
Exploring the Role of Long Noncoding RNAs (lncRNAs) as Biomarkers in Cancers
Bashir, S., & Uzair, M. (2026) · Experientia supplementum · doi:10.1007/978-3-032-06948-1_6
Romero-Barrios, N. (2016) · theses.fr (ABES) · doi:10.70675/b27c01e8z52c7z4829zbb4cza4ca90faa331
Tachtsidi, A. (2018) · theses.fr (ABES) · doi:10.70675/2ef58956zd619z4f59z94dbz6262d6448ed1
Metadata
- Authors
- Zhang, X., Rice, K., Wang, Y., Chen, W., Zhong, Y., Nakayama, Y., Zhou, Y., & Klibanski, A.
- Affiliations
- Harvard University (US)
- Corresponding author
- Klibanski, Anne
- Venue
- Endocrinology
- Publisher
- The Endocrine Society
- Published
- 2009-12-23
- Volume
- 151
- Issue
- 3
- Pages
- 939-947
- ISSN
- 0013-7227 (ISSN-L)
- 1945-7170
- PMC
- PMC2840681
- OpenAlex
- W2066815559
- Cited by
- 325
- References
- 19
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 17 · 2023: 25 · 2022: 16 · 2021: 23 · 2020: 35 · 2019: 21 · 2018: 29 · 2017: 30 · 2016: 17 · 2015: 28 · 2014: 21 · 2013: 18 · 2012: 17
- FWCI
- 3.47
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Endocrinology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK040947, R01-DK-40947)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Keywords
- MEG3, imprinted genes, non-coding RNA, RNA isoforms, alternative splicing, p53 activation, structure-function relationship, pituitary adenoma, tumor growth inhibition
- MeSH terms
- Base Sequence, Cell Line, Humans, Molecular Sequence Data, Nucleic Acid Conformation, Pituitary Neoplasms, Proteins, Structure-Activity Relationship, Gene Expression, Tumor Suppressor Protein p53, DNA, Complementary, RNA, Untranslated, RNA, Long Noncoding
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
