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Updated: Aug 3, 2025
Surface-enhanced Resonance Raman Scattering Nanoprobe Ratiometry for Detecting Microscopic Ovarian Cancer via Folate Receptor Targeting
Published on: March 25, 2019
Next Generation of Ovarian Cancer Detection Using Aptamers
Rayane da Silva Abreu1, Deborah Antunes1, Aline Dos Santos Moreira1
1Laboratório de Genômica Funcional e Bioinformática, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 21040-900, Brazil.
Abstract:
Ovarian cancer is among the seven most common types of cancer in women, being the most fatal gynecological tumor, due to the difficulty of detection in early stages. Aptamers are important tools to improve tumor diagnosis through the recognition of specific molecules produced by tumors. Here, aptamers and their potential targets in ovarian cancer cells were analyzed by in silico approaches. Specific aptamers were selected by the Cell-SELEX method using Caov-3 and OvCar-3 cells. The five most frequent aptamers obtained from the last round of selection were computationally modeled. The potential targets for those aptamers in cells were proposed by analyzing proteomic data available for the Caov-3 and OvCar-3 cell lines. Overexpressed proteins for each cell were characterized as to their three-dimensional model, cell location, and electrostatic potential. As a result, four specific aptamers for ovarian tumors were selected: AptaC2, AptaC4, AptaO1, and AptaO2. Potential targets were identified for each aptamer through Molecular Docking, and the best complexes were AptaC2-FXYD3, AptaC4-ALPP, AptaO1-TSPAN15, and AptaO2-TSPAN15. In addition, AptaC2 and AptaO1 could detect different stages and subtypes of ovarian cancer tissue samples. The application of this technology makes it possible to propose new molecular biomarkers for the differential diagnosis of epithelial ovarian cancer.
Insights
Researchers identified four aptamers that can recognize ovarian cancer cells. These aptamers, AptaC2 and AptaO1, show potential for detecting various ovarian cancer stages and subtypes, aiding in early diagnosis.
Area of Science:
- Biotechnology
- Oncology
- Bioinformatics
Background:
- Ovarian cancer is a leading cause of cancer death in women due to late-stage diagnosis.
- Aptamers offer a promising avenue for improving early tumor detection by targeting cancer-specific molecules.
Purpose of the Study:
- To computationally identify and characterize aptamers targeting ovarian cancer cells.
- To propose novel molecular biomarkers for the differential diagnosis of epithelial ovarian cancer.
Main Methods:
- In silico selection of aptamers using Cell-SELEX on Caov-3 and OvCar-3 cell lines.
- Computational modeling and proteomic data analysis to identify potential aptamer targets.
- Molecular Docking to validate aptamer-target interactions.
Main Results:
- Four specific aptamers (AptaC2, AptaC4, AptaO1, AptaO2) were selected for ovarian tumors.
- Potential targets identified: AptaC2-FXYD3, AptaC4-ALPP, AptaO1-TSPAN15, AptaO2-TSPAN15.
- AptaC2 and AptaO1 demonstrated potential in detecting different ovarian cancer stages and subtypes.
Conclusions:
- The study successfully selected aptamers with potential for ovarian cancer diagnosis.
- Identified aptamer-target complexes and validated aptamers' ability to detect cancer subtypes, proposing new diagnostic biomarkers.
