The DOI matches its Crossref record; 118 of the 118 references it cites were found in a registry or an index.
Circulating MicroRNAs: a novel class of biomarkers to diagnose and monitor human cancers
Abstract
Specific and sensitive non‐invasive biomarkers for the detection of human epithelial malignancies are urgently required to reduce the worldwide morbidity and mortality caused by cancer. MicroRNAs (miRNAs) are 19–24 nt noncoding RNAs that are frequently dysregulated in cancer and have shown great promise as tissue‐based markers for cancer classification. Once thought to be unstable RNA molecules, miRNAs are now shown to be stably expressed in serum, plasma, urine, saliva, and other body fluids. Moreover, the unique expression patterns of these circulating miRNAs are correlated with certain human diseases, including various types of cancer. Therefore, tumor‐derived miRNAs in serum or plasma are emerging as novel blood‐based fingerprints for the detection of human cancers, especially at an early stage. This review presented newly uncovered cellular and molecular mechanisms of the sources and stability of circulating miRNAs, revealing their great potential as a class of highly specific and sensitive biomarkers for tumor classification and prognostication. Meanwhile, this review also addressed certain critical issues that hinder the wide application of this new approach. Some potential challenges for the transition of circulating miRNAs from a research setting to a clinical application were also highlighted, with a future perspective of the incorporation of circulating miRNAs in the field of clinical oncology, especially their great potential from diagnostic to prognostic and predictive applications. © 2010 Wiley Periodicals, Inc. Med Res Rev
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1 retracted
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Machine Learning Applications in Cancer Prognosis and Prediction
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Serum miR-21 as a Diagnostic and Prognostic Biomarker in Colorectal Cancer
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Metadata
- Authors
- Zen, K., & Zhang, C.
- Venue
- Medicinal Research Reviews
- Publisher
- Wiley
- Published
- 2010-11-09
- Volume
- 32
- Issue
- 2
- Pages
- 326-348
- ISSN
- 0198-6325 (ISSN-L)
- 1098-1128
- OpenAlex
- W1519433744
- Cited by
- 502
- References
- 118
- FWCI
- 10.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Funders
- National Natural Science Foundation of China (30225037, 30471991, 30570731, 30730080, 30772484)
- National Basic Research Program of China (2006CB503909)
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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