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Nanotechnology-Assisted Molecular Profiling: Emerging Advances in Circulating Tumor DNA Detection.

Jiayi Kang1,2,3, Xing Ke3, Yanan Zhao1

  • 1College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.

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Nanotechnology enhances the detection of circulating tumor DNA (ctDNA) for non-invasive cancer diagnostics. Combining nanotechnology with artificial intelligence (AI) promises to advance precision oncology through improved liquid biopsy techniques.

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Area of Science:

  • Biomedical Engineering
  • Molecular Oncology
  • Nanotechnology

Background:

  • Circulating tumor DNA (ctDNA) is a key biomarker for non-invasive cancer management.
  • Low ctDNA abundance and degradation necessitate highly sensitive detection methods.
  • Nanotechnology offers advanced solutions for ctDNA analysis.

Purpose of the Study:

  • To review recent nanotechnology-assisted strategies for ctDNA detection.
  • To highlight the integration of artificial intelligence (AI) in nano-assisted liquid biopsy.
  • To discuss challenges and future perspectives for clinical translation.

Main Methods:

  • Surface-engineered nanomaterials for ctDNA enrichment.
  • Nano-enabled signal amplification techniques.
  • Integrated platforms: CRISPR, microfluidics, nanopore technologies.
  • Nanostructure-based analysis of ctDNA methylation and fragmentation profiles.
  • AI for nanostructure characterization, probe design, and data integration.

Main Results:

  • Nanotechnology significantly improves sensitivity and robustness in ctDNA detection.
  • AI integration streamlines various aspects of nano-assisted liquid biopsy.
  • Nanostructure approaches enable multi-omics ctDNA analysis for enhanced diagnostics.
  • Review consolidates advancements in nanotechnology for ctDNA-based precision oncology.

Conclusions:

  • Converging nanotechnology and AI innovations are revolutionizing ctDNA analysis.
  • These advancements hold significant potential for early cancer detection and real-time treatment monitoring.
  • Addressing challenges in standardization, biocompatibility, and automation is crucial for clinical translation.