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Cited by 177MicroRNA in disease regulationCancer-related molecular mechanisms researchExtracellular vesicles in disease

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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

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Yong, Fung Lin, Law, Chee Wei, Wang, Chee Woon·2013·BMC Cancer
DOI 10.1186/1471-2407-13-280PMC PMC3691634
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Abstract

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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Figure 1 Hierarchical clustering and PCA analyses. (A) Tissue miRNA array. Data were expressed as fold change of cancer tissue versus adjacent normal mucosa. (B) Blood miRNA array. Data were expressed as fold change of TNM stages (I, II, III and IV) versus healthy controls. S1, stage I; S2, stage II; S3, stage III; S4, stage IV. Green: down-regulation; red: up-regulation. (C) PCA plot of paired cancer tissue and adjacent normal mucosa samples. Color by type, red: cancer tissue; blue: adjacent normal mucosa. (D) PCA plot of whole blood samples. Color by type, red: control; blue: stage I; brown: stage II; grey: stage III; green: stage IV.
Figure 1 Hierarchical clustering and PCA analyses. (A) Tissue miRNA array. Data were expressed as fold change of cancer tissue versus adjacent normal mucosa. (B) Blood miRNA array. Data were expressed as fold change of TNM stages (I, II, III and IV) versus healthy controls. S1, stage I; S2, stage II; S3, stage III; S4, stage IV. Green: down-regulation; red: up-regulation. (C) PCA plot of paired cancer tissue and adjacent normal mucosa samples. Color by type, red: cancer tissue; blue: adjacent normal mucosa. (D) PCA plot of whole blood samples. Color by type, red: control; blue: stage I; brown: stage II; grey: stage III; green: stage IV.CC BY · PubMed Central
Figure 2 Venn diagram of differentially expressed miRNAs in tissue and blood arrays. Down-regulated miRNAs were indicated in green while up-regulated miRNAs were indicated in red.
Figure 2 Venn diagram of differentially expressed miRNAs in tissue and blood arrays. Down-regulated miRNAs were indicated in green while up-regulated miRNAs were indicated in red.CC BY · PubMed Central
Figure 3 Expression levels of circulating blood (A) miR-193a-3p, (B) miR-23a and (C) miR-338-5p. An increasing trend of expression was observed in the circulating blood miRNAs in the more advanced stages when compared with controls. Statistically significant differences were tested at *p?<?0.05. MiRNA expression was presented as fold change (2-∆∆CT); error bars represent mean?±?SEM.
Figure 3 Expression levels of circulating blood (A) miR-193a-3p, (B) miR-23a and (C) miR-338-5p. An increasing trend of expression was observed in the circulating blood miRNAs in the more advanced stages when compared with controls. Statistically significant differences were tested at *p?<?0.05. MiRNA expression was presented as fold change (2-∆∆CT); error bars represent mean?±?SEM.CC BY · PubMed Central
Figure 4 ROC curve analysis using the triple miRNA classifier of miR-193a-3p, miR-23a and miR-338-5p. The triple miRNA classifier yielded an AUC of 0.887 (95% CI: 0.821 - 0.953) with 80.0% sensitivity, 84.4% specificity and 83.3% accuracy.
Figure 4 ROC curve analysis using the triple miRNA classifier of miR-193a-3p, miR-23a and miR-338-5p. The triple miRNA classifier yielded an AUC of 0.887 (95% CI: 0.821 - 0.953) with 80.0% sensitivity, 84.4% specificity and 83.3% accuracy.CC BY · PubMed Central

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Research works printed but not linked: 2

  1. American Cancer Society: Cancer Facts & Figures 2012. 2012, Atlanta: American Cancer Society
  2. Zainal Ariffin O, Nor Saleha IT: National Cancer Registry Report 2007. 2011, Malaysia: Ministry of Healthy

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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
Publisher
Springer Science and Business Media LLC
Published
2013-06-08
Volume
13
Issue
1
Pages
280-280
ISSN
1471-2407 (ISSN-L)
DOI
10.1186/1471-2407-13-280
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
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

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