Abstract
Pancreatic cancer is highly lethal, and survival chances improve only with early detection at a precancerous stage. However, there remains a significant gap in developing tools for large-scale, rapid screening. To this end, a high-throughput On-Target Array Extraction Platform (OTAEP) by direct sintering of a series of metal-organic frameworks (MOFs) for dual in situ extraction, encompassing both exosomes and their metabolic profiles, is developed. Based on the principle of geometry-dependent photothermal conversion efficiency and standard testing, the appropriate MOF functional unit is identified. This unit enables exosome enrichment within 10 min and metabolic fingerprint extraction in under 1 s of laser irradiation, with over five reuse. To further accelerate and enhance the quality of metabolic profile analysis, the application of Surrogate Variable Analysis to eliminate hidden confounding factors within the profiles is proposed, and five biomarkers demonstrated by MS/MS experiments are identified. These biomarkers enable early diagnosis, risk stratification, and staging of pancreatic cancer simultaneously, with sensitivity of 94.1%, specificity of 98.8%, and precision of 94.9%. This work represents a breakthrough for overcoming throughput challenges in large-scale testing and for addressing confounding factors in big data analysis.
Published Version
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