The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Non-coding RNA networks in cancer
Open accessAbstract
Non-coding RNAs (ncRNAs) are functional molecules that regulate physiological programmes in developmental and disease contexts. This Review article discusses the complex networks of interactions that ncRNAs engage in and how these confer oncogenic or tumour-suppressive effects in cancer. Thousands of unique non-coding RNA (ncRNA) sequences exist within cells. Work from the past decade has altered our perception of ncRNAs from 'junk' transcriptional products to functional regulatory molecules that mediate cellular processes including chromatin remodelling, transcription, post-transcriptional modifications and signal transduction. The networks in which ncRNAs engage can influence numerous molecular targets to drive specific cell biological responses and fates. Consequently, ncRNAs act as key regulators of physiological programmes in developmental and disease contexts. Particularly relevant in cancer, ncRNAs have been identified as oncogenic drivers and tumour suppressors in every major cancer type. Thus, a deeper understanding of the complex networks of interactions that ncRNAs coordinate would provide a unique opportunity to design better therapeutic interventions.
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
The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14
Lee, R. C., Feinbaum, R. L., & Ambros, V. (1993) · Cell · doi:10.1016/0092-8674(93)90529-y · Cited by 12,948
Circular RNAs are a large class of animal RNAs with regulatory potency
Memczak, S., Jens, M., Elefsinioti, A., Torti, F., Krueger, J., Rybak, A., Maier, L., Mackowiak, S. D., Gregersen, L. H., Munschauer, M., et al. (2013) · Nature · doi:10.1038/nature11928 · Cited by 7,990
Natural RNA circles function as efficient microRNA sponges
Hansen, T. B., Jensen, T. I., Clausen, B. H., Bramsen, J. B., Finsen, B., Damgaard, C. K., & Kjems, J. (2013) · Nature · doi:10.1038/nature11993 · Cited by 7,985
Network biology: understanding the cell's functional organization
Barabási, A.-L., & Oltvai, Z. N. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1272 · Cited by 7,903
A ceRNA Hypothesis: The Rosetta Stone of a Hidden RNA Language?
Salmena, L., Poliseno, L., Tay, Y., Kats, L., & Pandolfi, P. P. (2011) · Cell · doi:10.1016/j.cell.2011.07.014 · Cited by 7,262
Landscape of transcription in human cells
Djebali, S., Davis, C. A., Merkel, A., Dobin, A., Lassmann, T., Mortazavi, A., Tanzer, A., Lagarde, J., Lin, W., Schlesinger, F., et al. (2012) · Nature · doi:10.1038/nature11233 · Cited by 5,187
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 multilayered complexity of ceRNA crosstalk and competition
Tay, Y., Rinn, J., & Pandolfi, P. P. (2014) · Nature · doi:10.1038/nature12986 · Cited by 3,910
Central Dogma of Molecular Biology
CRICK, F. (1970) · Nature · doi:10.1038/227561a0 · Cited by 3,444
Network motifs: theory and experimental approaches
Alon, U. (2007) · Nature Reviews Genetics · doi:10.1038/nrg2102 · Cited by 3,279
Cited by
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
Self-citationmiRNA interplay: mechanisms and consequences in cancer
Hill, M., & Tran, N. (2021) · Disease Models & Mechanisms · doi:10.1242/dmm.047662 · Cited by 674
Altered metabolism in cancer: insights into energy pathways and therapeutic targets
Tufail, M., Jiang, C.-H., & Li, N. (2024) · Molecular Cancer · doi:10.1186/s12943-024-02119-3 · Cited by 534
Roles and mechanisms of exosomal non-coding RNAs in human health and diseases
Li, C., Ni, Y.-Q., Xu, H., Xiang, Q.-Y., Zhao, Y., Zhan, J.-K., He, J.-Y., Li, S., & Liu, Y.-S. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00779-x · Cited by 406
Epigenetics in hepatocellular carcinoma
Nagaraju, G. P., Dariya, B., Kasa, P., Peela, S., & El-Rayes, B. F. (2022) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2021.07.017 · Cited by 339
Metadata
- Authors
- Anastasiadou, E., Jacob, L. S., & Slack, F. J.
- Venue
- Nature Reviews Cancer
- Published
- 2017-11-24
- Volume
- 18
- Issue
- 1
- Pages
- 5-18
- ISSN
- 1474-175X (ISSN-L)
- 1474-1768
- OpenAlex
- W2768096340
- Cited by
- 1,884
- References
- 22
- FWCI
- 13.20
- 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: Non-coding RNA networks in cancer. https://app.cochat.ai/papers/10.1038/nrc.2017.99
- The paper
- Anastasiadou, E., Jacob, L. S., & Slack, F. J. (2018). Non-coding RNA networks in cancer. Nature Reviews Cancer. https://doi.org/10.1038/nrc.2017.99
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.
