METHODS: In this study, plasma miRNA profiles from eight early-stage breast cancer patients and nine age-matched (± 2 years) healthy controls were characterized by miRNA array-based approach, followed by differential gene expression analysis, Independent T-test and construction of Receiver Operating Characteristic (ROC) curve to determine the capability of the assays to discriminate between breast cancer and the healthy control.
RESULTS: Based on the 372-miRNAs microarray profiling, a set of 40 differential miRNAs was extracted regarding to the fold change value at 2 and above. We further sub grouped 40 miRNAs of breast cancer patients that were significantly expressed at 2-fold change and higher. In this set, we discovered that 24 miRNAs were significantly upregulated and 16 miRNAs were significantly downregulated in breast cancer patients, as compared to the miRNA expression of healthy subjects. ROC curve analysis revealed that seven miRNAs (miR-125b-5p, miR-142-3p, miR-145-5p, miR-193a-5p, miR-27b-3p, miR-22-5p and miR-423-5p) had area under curve (AUC) value > 0.7 (AUC p-value < 0.05). Overlapping findings from differential gene expression analysis, ROC analysis, and Independent T-Test resulted in three miRNAs (miR-27b-3p, miR-22-5p, miR-145-5p). Cohen's effect size for these three miRNAs was large with d value are more than 0.95.
CONCLUSION: miR-27b-3p, miR-22-5p, miR-145-5p could be potential biomarkers to distinguish breast cancer patients from healthy controls. A validation study for these three miRNAs in an external set of samples is ongoing.
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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.