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Background <p>Lung cancer remains a leading cause of cancer-related mortality worldwide, highlighting the urgent need for rapid, accurate, and affordable diagnostic strategies. UBA6-specific E2 conjugating enzyme 1 (USE1) is overexpressed in lung cancer and contributes to tumorigenesis, yet no clinically applicable method exists for its detection.</p> Results <p>We developed an AI-assisted aptamer biosensing platform for antibody-free detection of USE1. High-affinity candidates (Aptamer 1e) were identified through systematic SELEX and rational truncation, and AlphaFold3-based modeling was subsequently applied post hoc to provide a structural hypothesis for the observed binding. For signal amplification and visualization, we engineered a nanostructured detection system composed of rolling-circle–amplified DNA microspheres (DNAMS) conjugated with streptavidin–quantum dots (STA-QDs). The DNAMS–STA-QD biosensor enabled strong fluorescence signals in USE1-positive cancer cells and produced a clear visual distinction between tumor and matched normal lung tissues. In 30 paired tissue samples, the biosensor achieved AUC = 0.961, with 86.7% sensitivity and 93.3% specificity for detecting lung cancer. The assay requires no antibodies, enzymatic amplification, or specialized instrumentation, and offers a rapid, low-cost workflow.</p> Conclusions <p>This study presents a clinically oriented nanobiosensing platform that integrates AI-assisted aptamer structural modeling with quantum dot–enhanced DNA nanostructures for sensitive detection of USE1. The approach offers a robust, antibody-free method for lung cancer diagnosis and demonstrates the potential of combining deep learning with nanobiotechnology to accelerate biomarker detection tool development.</p> Graphical Abstract <p></p>

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Quantum dot–DNA microsphere aptamer biosensor with AI-assisted structural modeling for rapid detection of the lung cancer biomarker USE1

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月14日

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  • Min-Jee Kim,
  • Kyuha Yum,
  • Dajeong Kim,
  • Iksoo Jang,
  • Aron Park,
  • MinJun Jung,
  • Geun Dong Lee,
  • Jun-O Jin,
  • Wonpil Im,
  • Jong Bum Lee,
  • Peter Chang-Whan Lee

摘要

Background

Lung cancer remains a leading cause of cancer-related mortality worldwide, highlighting the urgent need for rapid, accurate, and affordable diagnostic strategies. UBA6-specific E2 conjugating enzyme 1 (USE1) is overexpressed in lung cancer and contributes to tumorigenesis, yet no clinically applicable method exists for its detection.

Results

We developed an AI-assisted aptamer biosensing platform for antibody-free detection of USE1. High-affinity candidates (Aptamer 1e) were identified through systematic SELEX and rational truncation, and AlphaFold3-based modeling was subsequently applied post hoc to provide a structural hypothesis for the observed binding. For signal amplification and visualization, we engineered a nanostructured detection system composed of rolling-circle–amplified DNA microspheres (DNAMS) conjugated with streptavidin–quantum dots (STA-QDs). The DNAMS–STA-QD biosensor enabled strong fluorescence signals in USE1-positive cancer cells and produced a clear visual distinction between tumor and matched normal lung tissues. In 30 paired tissue samples, the biosensor achieved AUC = 0.961, with 86.7% sensitivity and 93.3% specificity for detecting lung cancer. The assay requires no antibodies, enzymatic amplification, or specialized instrumentation, and offers a rapid, low-cost workflow.

Conclusions

This study presents a clinically oriented nanobiosensing platform that integrates AI-assisted aptamer structural modeling with quantum dot–enhanced DNA nanostructures for sensitive detection of USE1. The approach offers a robust, antibody-free method for lung cancer diagnosis and demonstrates the potential of combining deep learning with nanobiotechnology to accelerate biomarker detection tool development.

Graphical Abstract