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Potentiality of a triple microRNA classifier: miR-193a-3p, miR-23a and miR-338-5p for early detection of colorectal cancer
Open accessAbstract
BACKGROUND: MicroRNAs (miRNAs) are short, non-coding RNA molecules that act as regulators of gene expression. Circulating blood miRNAs offer great potential as cancer biomarkers. The objective of this study was to correlate the differential expression of miRNAs in tissue and blood in the identification of biomarkers for early detection of colorectal cancer (CRC). METHODS: The study was divided into two phases: (I) Marker discovery by miRNA microarray using paired cancer tissues (n = 30) and blood samples (CRC, n = 42; control, n = 18). (II) Marker validation by stem-loop reverse transcription real time PCR using an independent set of paired cancer tissues (n = 30) and blood samples (CRC, n = 70; control, n = 32). Correlation analysis was determined by Pearson's test. Logistic regression and receiver operating characteristics curve analyses were applied to obtain diagnostic utility of the miRNAs. RESULTS: Seven miRNAs (miR-150, miR-193a-3p, miR-23a, miR-23b, miR-338-5p, miR-342-3p and miR-483-3p) have been found to be differentially expressed in both tissue and blood samples. Significant positive correlations were observed in the tissue and blood levels of miR-193a-3p, miR-23a and miR-338-5p. Moreover, increased expressions of these miRNAs were detected in the more advanced stages. MiR-193a-3p, miR-23a and miR-338-5p were demonstrated as a classifier for CRC detection, yielding a receiver operating characteristic curve area of 0.887 (80.0% sensitivity, 84.4% specificity and 83.3% accuracy). CONCLUSION: Dysregulations in circulating blood miRNAs are reflective of those in colorectal tissues. The triple miRNA classifier of miR-193a-3p, miR-23a and miR-338-5p appears to be a potential blood biomarker for early detection of CRC.
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“upregulation of miR-23 expression has been detected in both colorectal cancer and gastric cancer patients, such as in serum exosomes, blood tissues, and gastric cancer tissues [[78], [79], [80]].”
From Recent advances of miR-23 in human diseases and growth development (2025) · cites this paper as [79]
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Metadata
- Authors
- Yong, F. L., Law, C. W., & Wang, C. W.
- Affiliations
- University of Malaya (MY)
- Mahsa University (MY)
- Corresponding author
- Yong, Fung Lin
- Venue
- BMC Cancer
- Published
- 2013-06-08
- Volume
- 13
- Issue
- 1
- Pages
- 280-280
- ISSN
- 1471-2407 (ISSN-L)
- PMC
- PMC3691634
- OpenAlex
- W2057318887
- Cited by
- 176
- References
- 65
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 5 · 2023: 7 · 2022: 6 · 2021: 9 · 2020: 17 · 2019: 20 · 2018: 17 · 2017: 23 · 2016: 23 · 2015: 20 · 2014: 22 · 2013: 4
- FWCI
- 8.09
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Cancer (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Universiti Malaya (PV020-2011A, RG313-11HTM)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Extracellular vesicles in disease
- Keywords
- colorectal cancer, early cancer detection, circulating microRNAs, blood-based biomarkers, miR-193a-3p, miR-23a, miR-338-5p, miRNA expression profiling, tumor staging, diagnostic accuracy
- MeSH terms
- Aged, Colonic Neoplasms, Female, Humans, Male, Middle Aged, ROC Curve, Sensitivity and Specificity, Biomarkers, Tumor, Reverse Transcriptase Polymerase Chain Reaction, Oligonucleotide Array Sequence Analysis, MicroRNAs, Early Detection of Cancer, Real-Time Polymerase Chain Reaction
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 ›
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