The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Upregulated METTL3 promotes metastasis of colorectal Cancer via miR-1246/SPRED2/MAPK signaling pathway
Open accessAbstract
BACKGROUND: m6A modification has been proved to play an important role in many biological processes. METTL3 as the main methyltransferase for methylation process has been found to be upregulated in many cancers, including CRC. Here, we investigate m6A modification and the underlying mechanism of METTL3 in the development of CRC. METHODS: The expression of METTL3 was detected in large clinical patient samples. To evaluate the function of METTL3 in vitro and in vivo, colony formation, CCK-8, cell migration and invasion assays were performed. To find out the downstream target of METTL3, GEO dataset was re-mined. We analyzed expression and metastasis-related miRNA by Pearson correlation, and miR-1246 was selected. Here, to identify the downstream target of miR-1246, Targetscan and miRWalk were used. RIP and luciferase reporter assay further confirmed SPRED2 as the direct target of miR-1246. RESULTS: We found that upregulated METTL3 is responsible for abnormal m6A modification in CRC and correlates positively with tumor metastasis. The gain- and loss-of-function indicates that METTL3 promotes cell migration and invasion in vitro and in vivo. Additionally, we confirmed that METTL3 can methylate pri-miR-1246, which further promotes the maturation of pri-miR-1246. By using bioinformatics tools, anti-oncogene SPRED2 was identified as the downstream target of miR-1246, wherein downregulated SPRED2 further reverses the inhibition of the MAPK pathway. CONCLUSIONS: The present study demonstrates that the METTL3/miR-1246/SPRED2 axis plays an important role in tumor metastasis and provides a new m6A modification pattern in CRC development.
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
Bray, F., Ferlay, J., Soerjomataram, I., Siegel, R. L., Torre, L. A., & Jemal, A. (2018) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21492 · Cited by 84,109
Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq
Dominissini, D., Moshitch-Moshkovitz, S., Schwartz, S., Salmon-Divon, M., Ungar, L., Osenberg, S., Cesarkas, K., Jacob-Hirsch, J., Amariglio, N., Kupiec, M., et al. (2012) · Nature · doi:10.1038/nature11112 · Cited by 4,884
Regulation of mRNA Translation and Stability by microRNAs
Fabian, M. R., Sonenberg, N., & Filipowicz, W. (2010) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-060308-103103 · Cited by 3,214
miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions
Chou, C.-H., Shrestha, S., Yang, C.-D., Chang, N.-W., Lin, Y.-L., Liao, K.-W., Huang, W.-C., Sun, T.-H., Tu, S.-J., Lee, W.-H., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1067 · Cited by 1,811
m6A RNA methylation promotes XIST-mediated transcriptional repression
Patil, D. P., Chen, C.-K., Pickering, B. F., Chow, A., Jackson, C., Guttman, M., & Jaffrey, S. R. (2016) · Nature · doi:10.1038/nature19342 · Cited by 1,747
The m(6)A Methyltransferase METTL3 Promotes Translation in Human Cancer Cells
Lin, S., Choe, J., Du, P., Triboulet, R., & Gregory, R. I. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.03.021 · Cited by 1,531
Chen, M., Wei, L., Law, C., Tsang, F. H., Shen, J., Cheng, C. L., Tsang, L., Ho, D. W., Chiu, D. K., Lee, J. M., et al. (2018) · Hepatology · doi:10.1002/hep.29683 · Cited by 1,376
Cunningham, D., Atkin, W., Lenz, H.-J., Lynch, H. T., Minsky, B., Nordlinger, B., & Starling, N. (2010) · The Lancet · doi:10.1016/s0140-6736(10)60353-4 · Cited by 1,351
N6-methyladenosine marks primary microRNAs for processing
Alarcón, C. R., Lee, H., Goodarzi, H., Halberg, N., & Tavazoie, S. F. (2015) · Nature · doi:10.1038/nature14281 · Cited by 1,315
Rethinking m6A Readers, Writers, and Erasers
Meyer, K. D., & Jaffrey, S. R. (2017) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-100616-060758 · Cited by 1,150
Cited by
The potential role of RNA N6-methyladenosine in Cancer progression
Wang, T., Kong, S., Tao, M., & Ju, S. (2020) · Molecular Cancer · doi:10.1186/s12943-020-01204-7 · Cited by 1,013
The role of m6A RNA methylation in cancer metabolism
An, Y., & Duan, H. (2022) · Molecular Cancer · doi:10.1186/s12943-022-01500-4 · Cited by 871
RNA N6-methyladenosine reader IGF2BP3 regulates cell cycle and angiogenesis in colon cancer
Yang, Z., Wang, T., Wu, D., Min, Z., Tan, J., & Yu, B. (2020) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-020-01714-8 · Cited by 264
Wu, S., Yun, J., Tang, W., Familiari, G., Relucenti, M., Wu, J., Li, X., Chen, H., & Chen, R. (2023) · ACS Nano · doi:10.1021/acsnano.3c03050 · Cited by 102
Self-citationLiu, T., Zhao, J., & Lin, C. (2022) · Bioengineered · doi:10.1080/21655979.2022.2086351 · Cited by 12
Metadata
- Authors
- Peng, W., Li, J., Chen, R., Gu, Q., Yang, P., Qian, W., Ji, D., Wang, Q., Zhang, Z., Tang, J., & Sun, Y.
- Venue
- Journal of Experimental & Clinical Cancer Research
- Published
- 2019-09-06
- Volume
- 38
- Issue
- 1
- Pages
- 393-393
- ISSN
- 0392-9078 (ISSN-L)
- 1756-9966
- OpenAlex
- W2972178290
- Cited by
- 373
- References
- 37
- FWCI
- 14.47
- Type
- journal article
- Language
- en
- Open access
- gold
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: Upregulated METTL3 promotes metastasis of colorectal Cancer via miR-1246/SPRED2/MAPK signaling pathway. https://app.cochat.ai/papers/10.1186/s13046-019-1408-4
- The paper
- Peng, W., Li, J., Chen, R., Gu, Q., Yang, P., Qian, W., Ji, D., Wang, Q., Zhang, Z., Tang, J., & Sun, Y. (2019). Upregulated METTL3 promotes metastasis of colorectal Cancer via miR-1246/SPRED2/MAPK signaling pathway. Journal of Experimental & Clinical Cancer Research. https://doi.org/10.1186/s13046-019-1408-4
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.