MicroRNA-21 Concentrations in Breast Cancer

Direct Serum Assay for MicroRNA-21 Concentrations in Early and Advanced Breast Cancer


Background – Small noncoding RNA molecules known as microRNAs (miRs) are involved in the regulation of gene expression. The hypothesis was based on the biomarker, miR-21 present in the serum, which related to the presence and stage of breast cancer. The direct application of reverse-transcription quantitative real-time PCR (RT-qPCR) in a direct serum assay has been used for the quantification and detection of the miR-21 in breast cancer patients.

Methods – A total of 102 breast cancer patients with varying stages of breast cancer and 20 healthy female patients were tested by the RT-qPCR applied directly in serum assay for miR-21.

Results – Detection for RT-qPCR-DS was limited to 0.625µl of serum. miR-21 levels detected in the healthy donors were comparatively lower with respect to breast cancer patients with different stage of the disease. A significantly higher levels of miR-21 was detected in patients with stage IV breast cancer compared to patients with other stages of the disease. The odds ratio was 1.796 and area under the curve was 0.721 for the distinction of loco regional breast cancers and healthy donors. Multivariate analysis confirmed that a correlation of miR-21 concentrations and stage of breast cancer existed.

Conclusion- The novel RT-qPCR-DS serves as a better technique in detecting circulating miR. miR-21 proves to be a significant biomarker for breast cancer, which could also probably detect the progression of the disease. Further research could lead to improved breast cancer care by this serum biomarker as a key tool.


Traditional methods

Mammography (also known as film mammography) is a traditional method for screening breast cancer (Boyd et al., 2007). Its principle lies in the use of low-dose x-rays. Soft tissue such as fat is radiographically lucent, which appears dark on a mammogram. In contrast, stroma and epithelial tissue are radiographically dense, which is termed mammographic density, appearing light on a mammogram (Boyd et al., 2007). It has been established that the more immense the density, the more association it had with regard to the greater risk of breast cancer. A dense tissue present in 75% or more of the breast poses a risk of breast cancer (Boyd et al., 2007).  A limitation of this method revolves around the fact that expansive mammographic density may be difficult to detect by mammography, thereby indicating a false negative (Boyd et al., 2007). Cancers may be masked by surrounding dense breast tissue, limiting the sensitivity of the screening (Boyd et al., 2007), thereby increasing the risk of breast cancer (Pisano et al., 2005). High false positive results and costs are drawbacks of mammography (Asaga et al., 2010).  An alternative breast cancer screening technique is the MRI, which is sensitive, but its limitations include the lack of cost-effectiveness and specificity (Esserman et al., 2007).

Digital mammography, an upgrade to film mammography allowed the manipulation of the degree of contrast on digital images. This allowed the differentiation of dense breast tissues from malignant cells (Pisano et al., 2005). Women under 50 years of age, with dense breast tissue or those who are pre-menopausal or peri-menopausal were mostly detected by digital mammography (Pisano et al., 2005). In comparison to the film mammography method, digital mammography has an increased cost (1.5-4 times more), but is quicker at developing the image (Pisano et al., 2005).

BRCA1 and BRCA2 are tumour markers used to identify individuals who are at risk of developing breast cancer via inheritance (Duffy, 2001). Only 5-10% cases of breast cancers are hereditary. 80-85% risk of developing breast cancer was reported in individuals carrying either the BRCA1 or BRCA2 gene (Duffy, 2001).

Cancer antigen 15-3 (CA 15-3) is a gene product of the MUC1 gene. Overexpression of MUC1 gene in malignant breast tumours allows CA 15-3 to be used as a tumour marker for breast cancer (Kabel, 2017). False positive results were reported in benign breast and benign liver diseases (Kabel, 2017). The serum concentration of patients with elevated levels of CA 15-3 became more detectable as the size of tumour and severity of the disease increased. Therefore, this is suitable as a prognostic and pharmacokinetic biomarker (Kabel, 2017). The lack of sensitivity for women with early disease have been a main limitation of CA 15-3 biomarker (Duffy et al., 2010).

Rising levels of another extensively used biomarker, carcinoembryonic antigen (CEA) indicated poor treatment or the risk of recurrence following treatment (Kabel, 2017). The lack of disease sensitivity and specificity prevents the use of CEA as predictive biomarker (Kabel, 2017). Estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER-2) serve as pharmacokinetic biomarkers (Kabel, 2017).

Relevance to current article

Elevated levels of miR-21 was observed in breast cancer patients (N = 102) compared to healthy females (N = 20) in the study done by Asaga et al., (2010). Detection of circulating miR by RT-qPCR-DS was robust and effective (Asaga et al., 2010). The differentiation of patients with stage I, stage II or stage III from patients with stage IV breast cancer was possible with the direct assay, but not by the standard RT-qPCR (Asaga et al., 2010). The assay had a sensitivity and specificity of 67% and 75% respectively in distinguishing loco regional breast cancer patients from healthy patients. The specificity and sensitivity in distinguishing patients with stage IV breast cancer from the earlier stages was 86% and 70% respectively (Asaga et al., 2010). The use of the novel RT-qPCR in direct serum assay reduced mechanical and human errors and minimized the time and overall cost (Asaga et al., 2010).

CA 15-3 and CEA are low in sensitivity and specificity, therefore cannot be used as a diagnostic marker (Ng et al., 2013). Comparatively, miR-21 shows a better specificity and sensitivity (Asaga et al., 2010).

Current methods

3D mammography is an evolution of the mammography technology (Houssami et al., 2017). 3D mammography improves cancer visibility by reducing the images of overlapping breast tissue, leading to the visualization of benign and malignant breast lesions which would have been masked in traditional mammography (Houssami et al., 2016). It may also decrease the false positive recall. Cost and time-taken to read a 3D mammography are limitations of this method (Houssami et al., 2017).

A study by Ng et al., (2013) detected elevation in miR-451, miR-16 and miR-21, while a reduction in miR-145 was observed in the plasma of breast cancer patients. The combination of miR-451 and miR-145 served as the best biomarkers for breast cancer with an optimal specificity of 92% and optimal sensitivity of 90% in distinguishing breast cancer patients from control subjects of other types of cancers (gastric cancer, lung cancer) recruited in the study (Ng et al., 2013). This study by Ng et al., (2013) recognized a combination of miRNAs specific to breast cancer and not the other cancers. Drawbacks include the lack of information regarding whether these miRNAs can be used to distinguish between the subtypes of breast cancer and between sporadic and familial forms (Ng et al., 2013). The study done by Asaga et al., (2010) only focused on miR-21 as a predictive marker in breast cancer, but miR-21 has been implicated in other types of cancer too. Comparatively the study done by Ng et al., (2013) has identified biomarkers specific to breast cancer.

In conclusion, the use of miR-21 as a biomarker in breast cancer presented a correlation of circulating miR-21 with the stage of breast cancer. More research is required to establish miR-21 as an important biomarker in breast cancer (Asaga et al., 2010). A combined expression analysis of miR-21 and miR-191 increased the specificity to 100% and sensitivity to 92% (Chen and Wang, 2013). The study done by Chen and Wang (2013) proved that a combination of miRNAs were better as a predictive biomarker for breast cancer.





Asaga, S., Kuo, C., Nguyen, T., Terpenning, M., Giuliano, A. and Hoon, D. (2010). Direct Serum Assay for MicroRNA-21 Concentrations in Early and Advanced Breast Cancer. Clinical Chemistry, 57(1), pp.84-91.
Boyd, N., Guo, H., Martin, L., Sun, L., Stone, J., Fishell, E., Jong, R., Hislop, G., Chiarelli, A., Minkin, S. and Yaffe, M. (2007). Mammographic Density and the Risk and Detection of Breast Cancer. The New England Journal of Medicine, 356(3), pp.227-236.

Chen, J. and Wang, X. (2013). MicroRNA-21 in breast cancer: diagnostic and prognostic potential. Clinical and Translational Oncology, 16(3), pp.225-233.

Duffy, M. (2001). Biochemical markers in breast cancer: which ones are clinically useful?. Clinical Biochemistry, 34(5), pp.347-352.

Duffy, M., Evoy, D. and McDermott, E. (2010). CA 15-3: Uses and limitation as a biomarker for breast cancer. Clinica Chimica Acta, 411(23-24), pp.1869-1874.

Esserman, L., Shieh, Y., Park, J. and Ozanne, E. (2007). A role for biomarkers in the screening and diagnosis of breast cancer in younger women. Expert Review of Molecular Diagnostics, 7(5), pp.533-544.

Houssami, N., Lång, K., Bernardi, D., Tagliafico, A., Zackrisson, S. and Skaane, P. (2016). Digital breast tomosynthesis (3D-mammography) screening: A pictorial review of screen-detected cancers and false recalls attributed to tomosynthesis in prospective screening trials. The Breast, 26, pp.119-134.

Houssami, N., Bernardi, D., Pellegrini, M., Valentini, M., Fantò, C., Ostillio, L., Tuttobene, P., Luparia, A. and Macaskill, P. (2017). Breast cancer detection using single-reading of breast tomosynthesis (3D-mammography) compared to double-reading of 2D-mammography: Evidence from a population-based trial. Cancer Epidemiology, 47, pp.94-99.

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Ng, E., Li, R., Shin, V., Jin, H., Leung, C., Ma, E., Pang, R., Chua, D., Chu, K., Law, W., Law, S., Poon, R. and Kwong, A. (2013). Circulating microRNAs as Specific Biomarkers for Breast Cancer Detection. PLoS ONE, 8(1), p.e53141.

Pisano, E., Gatsonis, C., Hendrick, E., Yaffe, M., Baum, J., Acharyya, S., Conant, E., Fajardo, L., Bassett, L., D’Orsi, C., Jong, R. and Rebner, M. (2005). Diagnostic Performance of Digital versus Film Mammography for Breast-Cancer Screening. New England Journal of Medicine, 353(17), pp.1773-1783.

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