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Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
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Detection of Prostate Cancer Biomarker PCA3 by Using Aptasensors.

Bruno P Crulhas1, Caroline R Basso1, Gustavo R Castro1

  • 1Department of Chemistry and Biochemistry, Institute of Bioscience, UNESP, Botucatu, SP, Brazil.

Current Medicinal Chemistry
|June 8, 2022
PubMed
Summary

This study developed a novel aptasensor for detecting PCA3, a key prostate cancer biomarker. The sensor offers sensitive and specific detection, paving the way for earlier and more cost-effective prostate cancer diagnosis.

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Area of Science:

  • Biomedical Engineering
  • Molecular Diagnostics
  • Cancer Biomarkers

Background:

  • Prostate cancer is characterized by elevated PCA3 (Prostate Cancer Antigen 3) messenger RNA levels.
  • PCA3 is recognized as a significant biomarker for prostate cancer prognosis and diagnosis.

Purpose of the Study:

  • To develop a novel aptasensor for detecting PCA3 released by prostate cancer cells.
  • To establish a sensitive and specific platform for early prostate cancer diagnosis.

Main Methods:

  • A DNA hairpin aptamer targeting PCA3 was synthesized and functionalized with a methylene blue (MB) redox probe.
  • The aptasensor was immobilized on a gold electrode via self-assembly for label-free detection.
  • PCA3 release was monitored in different prostate cell lines.
Keywords:
AptasensorPCA3aptamerbiomarkercancer cellreleasing protein

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Main Results:

  • The developed aptasensor demonstrated stable and sensitive performance with a wide linear detection range (0-150 ng/mL).
  • Significantly higher PCA3 expression was observed in LNCaP and PC-3 prostate cancer cells.
  • The sensor provides a powerful platform for understanding prostate cancer dynamics.

Conclusions:

  • This strategy offers a sensitive, specific, and simple methodology for PCA3 detection.
  • The aptasensor is a promising tool for early, cost-effective prostate cancer diagnosis.
  • Monitoring PCA3 release aids in understanding prostate cancer heterogeneity.