The analysis of estrogen receptor (ER) expression in breast carcinomas plays a crucial role in determining the endocrine responsiveness of tumors for systemic adjuvant therapy. Conventionally, the ER levels in breast carcinomas had been detected using the dextran-coated charcoal assay and radioimmunoassay, which are now substituted with safer and economic antibody-based assays such as immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA). Despite a gold (Au) standard method, the IHC has been criticized for factors such as tissue fixation, antibody selection, and threshold staining for result interpretation that could falsify test accuracy and reproducibility. The quest for alternative methods of ER quantification in tissue samples paved the way for aptamer-based diagnostics. Previously, we have isolated a DNA aptamer against human ER alpha (ERα) using an in vitro evolution system. In this study, we developed an electrochemical sensor using the 76-nucleotide DNA ERα- aptamer for rapid, precise, and cost-effective detection of ERα expression in human breast cancer patients. The aptasensor was constructed by covalently immobilizing the thiolated ERα- aptamer onto a screen-printed Au electrode. Construction of aptasensors was confirmed through atomic force microscopy and differential pulse voltammetry measurements. A detection limit of 0.001 ng/ml was calculated for full-length ERα (66.2 kDa) in a detection time of 10 min. Analysis of the cancerous breast tissue samples using the ELISA and aptasensor methods enabled distinctive classification of samples into the categories of ER −ve, weak ER +ve, and strong ER +ve samples. The current change of this aptasensor lies within 5% after a storage of 60 days at 4°C. Further studies on a reasonably large sample size are required to realize the clinical potential of the sensor.
CITATION STYLE
Ahirwar, R., Dalal, A., Sharma, J. G., Yadav, B. K., Nahar, P., Kumar, A., & Kumar, S. (2019). An aptasensor for rapid and sensitive detection of estrogen receptor alpha in human breast cancer. Biotechnology and Bioengineering, 116(1), 227–233. https://doi.org/10.1002/bit.26819
Mendeley helps you to discover research relevant for your work.