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Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing
Published on: September 25, 2011
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Aptasensors in colorectal Cancer: Emerging tools for precision diagnostics
Qamar Abuhassan1, Ali M Atoom2, R Roopashree3
1Department of Pharmaceutics and Pharmaceutical Technology, School of Pharmacy, University of Jordan, Amman, 11942, Jordan.
Clinica Chimica Acta; International Journal of Clinical Chemistry
|December 6, 2025
Summary
Nanomaterials enhance aptasensor detection of colorectal cancer (CRC) biomarkers for early diagnosis. Further research is needed for standardization and clinical validation of these advanced biosensors.
Area of Science:
- Biomedical Engineering
- Nanotechnology
- Analytical Chemistry
Background:
- Aptasensors are crucial for colorectal cancer (CRC) biomarker detection.
- Nanomaterials significantly improve aptasensor sensitivity, stability, and signal transduction.
- Existing aptasensors face challenges in clinical translation and standardization.
Purpose of the Study:
- To review the role of various nanomaterials in CRC aptasensor development.
- To analyze the advantages and limitations of different nanomaterial classes.
- To identify future directions for clinical application of aptasensors.
Main Methods:
- Comprehensive literature review of nanomaterial integration in CRC aptasensors.
- Analysis of nanomaterial properties (AuNPs, carbon-based, MOFs, COFs, etc.) for biosensing.
- Evaluation of DNA amplification techniques (HCR, enzymatic recycling) for enhanced detection.
Main Results:
- Gold nanoparticles (AuNPs) offer versatile platforms but have variability issues.
- Carbon nanomaterials provide excellent conductivity for detecting CRC markers like CEA and CA19-9.
- MOFs and COFs enable multiplexing but face stability challenges.
- DNA amplification techniques achieve high sensitivity but are complex for point-of-care use.
Conclusions:
- Nanomaterial-enhanced aptasensors show promise for early CRC diagnosis.
- Critical gaps exist in standardization, scalability, and clinical validation.
- Future work should focus on simplified, reproducible designs for real-world applications.

