Advances in Electrochemical Biosensor Technologies for the Detection of Nucleic Acid Breast Cancer Biomarkers

Sensors (Basel). 2023 Apr 20;23(8):4128. doi: 10.3390/s23084128.

Abstract

Breast cancer is the second leading cause of cancer deaths in women worldwide; therefore, there is an increased need for the discovery, development, optimization, and quantification of diagnostic biomarkers that can improve the disease diagnosis, prognosis, and therapeutic outcome. Circulating cell-free nucleic acids biomarkers such as microRNAs (miRNAs) and breast cancer susceptibility gene 1 (BRCA1) allow the characterization of the genetic features and screening breast cancer patients. Electrochemical biosensors offer excellent platforms for the detection of breast cancer biomarkers due to their high sensitivity and selectivity, low cost, use of small analyte volumes, and easy miniaturization. In this context, this article provides an exhaustive review concerning the electrochemical methods of characterization and quantification of different miRNAs and BRCA1 breast cancer biomarkers using electrochemical DNA biosensors based on the detection of hybridization events between a DNA or peptide nucleic acid probe and the target nucleic acid sequence. The fabrication approaches, the biosensors architectures, the signal amplification strategies, the detection techniques, and the key performance parameters, such as the linearity range and the limit of detection, were discussed.

Keywords: BRCA1; breast cancer; cancer biomarker; electrochemical biosensor; electrochemistry; mi-RNA; miR-155; miR-21; microRNA.

Publication types

  • Review

MeSH terms

  • Biomarkers, Tumor / genetics
  • Biosensing Techniques* / methods
  • Breast Neoplasms* / diagnosis
  • Breast Neoplasms* / genetics
  • DNA / chemistry
  • Electrochemical Techniques / methods
  • Female
  • Humans
  • MicroRNAs* / genetics
  • Nucleic Acid Hybridization
  • Nucleic Acids*

Substances

  • Nucleic Acids
  • Biomarkers, Tumor
  • MicroRNAs
  • DNA

Grants and funding

This research was sponsored by FEDER funds through the program COMPETE–Programa Operacional Factores de Competitividade, and by national funds through FCT–Fundação para a Ciência e a Tecnologia, under the projects UID/EMS/00285/2020, UIDB/00285/2020 and LA/P/0112/2020.