ArticleJournal of nanobiotechnology2026
Quantum dot-DNA microsphere aptamer biosensor with AI-assisted structural modeling for rapid detection of the lung cancer biomarker USE1.
Article in Journal of nanobiotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundLung 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.
resultsWe 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.
conclusionsThis 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.
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